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Dynamic Network Analysis (DyNA) and Dynamic Hypergraphs (DyHyp) were used to define protein-level inflammatory networks at the local (wound effluent) and systemic circulation (serum) levels from 140 active-duty, injured service members (59 with TBI and 81 non-TBI). Interleukin (IL)-17A was the only biomarker elevated significantly in both serum and effluent in TBI vs. non-TBI casualties, and the mediator with the most DyNA connections in TBI wounds. DyNA combining serum and effluent data to define cross-compartment correlations suggested that IL-17A bridges local and systemic circulation at late time points. DyHyp suggested that systemic IL-17A upregulation in TBI patients was associated with tumor necrosis factor-α, while IL-17A downregulation in non-TBI patients was associated with interferon-γ. Correlation analysis suggested differential upregulation of pathogenic Th17 cells, non-pathogenic Th17 cells, and memory/effector T cells. This was associated with reduced procalcitonin in both effluent and serum of TBI patients, in support of an antibacterial effect of Th17 cells in TBI patients. Dysregulation of Th17 responses following TBI may drive cross-compartment inflammation following combat injury, counteracting wound infection at the cost of elevated systemic inflammation. [ABSTRACT FROM AUTHOR]

Introduction: Invasive fungal infections (IFI) are associated with high morbidity and mortality. A better method of risk stratifying trauma patients for combat-related IFI is needed to improve clinical outcomes while minimizing morbidity related to overtreatment. We sought to develop combat-related IFI clinical decision support (CDS) tools to assist providers to make treatment decisions both near the point of injury and subsequently at definitive treatment centers.Materials and Methods: We utilized a training dataset containing information from 227 combat-injured military personnel to build a Bayesian belief network (BBN) to predict the likelihood of developing IFI using information available at the point of initial resuscitation (THEATER model) and in the tertiary care setting (MEDCEN model). After selecting BBN models, external validation used a separate test dataset of 350 wounded warriors. Furthermore, the performance of the BBN models was compared with a "two-rule model" alone (based on physician experience) and combinations of the BBN models plus the two-rule model. The two-rule model contains plausible IFI criteria, but it has not been formally evaluated, and they are not currently actual clinical guidelines.Results: We found receiver operating characteristic areas under the curve (AUC) of 0.70 (95% CI: [0.62, 0.77]) and 0.68 (95% CI: [0.59, 0.76]) for the THEATER and MEDCEN BBN models, respectively, on cross-validation. External validation with the highest AUC BBN models produced THEATER AUC of 0.68 (95% CI: [0.58, 0.78]) and MEDCEN AUC of 0.67 (95% CI: [0.57, 0.78]). With the incorporation of two-rule model in low IFI-prevalence populations, external validation AUC increased to 0.77 (95% CI: [0.69, 0.84]) for the THEATER model and 0.76 (95% CI:[0.68, 0.85]) for the LRMC model. The two-rule model alone has an AUC of 0.72 (95% CI: [0.63, 0.81]).Conclusions: Overall, the IFI tools produced clinically useful, robust models. However, the clinical utility of these models is highly dependent upon the clinician's individual risk tolerance. The threshold probability for optimal clinical use of this CDS tool is currently being evaluated in an ongoing clinical utilization study. CDS tools, such as these, may facilitate early diagnosis of patients with or at risk for IFI, permitting early or prophylactic treatment with the aim of improving outcomes. [ABSTRACT FROM AUTHOR]

Background: Objective means of estimating survival can be used to guide surgical decision-making and to risk-stratify patients for clinical trials. Although a free, online tool () can estimate 3- and 12-month survival, recent work, including a survey of the Musculoskeletal Tumor Society, indicated that estimates at 1 and 6 months after surgery also would be helpful. Longer estimates help justify the need for more durable and expensive reconstructive options, and very short estimates could help identify those who will not survive 1 month and should not undergo surgery. Thereby, an important use of this tool would be to help avoid unsuccessful and expensive surgery during the last month of life. Questions/Purposes: We seek to provide a reliable, objective means of estimating survival in patients with metastatic bone disease. After generating models to derive 1- and 6-month survival estimates, we determined suitability for clinical use by applying receiver operator characteristic (ROC) (area under the curve [AUC] > 0.7) and decision curve analysis (DCA), which determines whether using PATHFx can improve outcomes, but also discerns in which kinds of patients PATHFx should not be used. Methods: We used two, existing, skeletal metastasis registries chosen for their quality and availability. Data from Memorial Sloan-Kettering Cancer Center (training set, n = 189) was used to develop two Bayesian Belief Networks trained to estimate the likelihood of survival at 1 and 6 months after surgery. Next, data from eight major referral centers across Scandinavia (n = 815) served as the external validation set-that is, as a means to test model performance in a different patient population. The diversity of the data between the training set from Memorial Sloan-Kettering Cancer Center and the Scandinavian external validation set is important to help ensure the models are applicable to patients in various settings with differing demographics and treatment philosophies. We considered disease-specific, laboratory, and demographic information, and the surgeon's estimate of survival. For each model, we calculated the area under the ROC curve (AUC) as a metric of discriminatory ability and the Net Benefit using DCA to determine whether the models were suitable for clinical use. Results: On external validation, the AUC for the 1- and 6-month models were 0.76 (95% CI, 0.72-0.80) and 0.76 (95% CI, 0.73-0.79), respectively. The models conferred a positive net benefit on DCA, indicating each could be used rather than assume all patients or no patients would survive greater than 1 or 6 months, respectively. Conclusions: Decision analysis confirms that the 1- and 6-month Bayesian models are suitable for clinical use. Clinical Relevance: These data support upgrading with the algorithms described above, which is designed to guide surgical decision-making, and function as a risk stratification method in support of clinical trials. This updating has been done, so now surgeons may use any web browser to generate survival estimates at 1, 3, 6, and 12 months after surgery, at no cost. Just as short estimates of survival help justify palliative therapy or less-invasive approaches to stabilization, more favorable survival estimates at 6 or 12 months are used to justify more durable, complicated, and expensive reconstructive options. [ABSTRACT FROM AUTHOR]

The article offers information on the clinical importance of incidental findings on staging Computed tomography (CT) scans in patients with sarcoma. Further discusses the presence of metastatic disease in patients with soft tissue and bone sarcomas remains the single most important determining factor of long-term survival; and detection of the indeterminate nodules during staging represented metastatic disease.

Background: After a decade of war in Iraq and Afghanistan, we have observed an increase in combat-related injury survival and a paradoxical increase in injury severity, mainly because of the effects of blasts. These severe injuries have a devastating effect on each patient's immune system resulting in massive upregulation of the systemic inflammatory response. By examining inflammatory mediators, preliminary data suggest that it may be possible to correlate complications such as wound failure and heterotopic ossification (HO) with distinct systemic and local inflammatory profiles, but this is a relatively new topic. Questions/purposes: We asked whether systemic or local markers of inflammation could be used as an objective means, independent of demographic and subjective factors, to estimate the likelihood of (1) HO and/or (2) wound failure (defined as wounds requiring surgical débridement after definitive closure, or wounds that were not closed or covered within 21 days of injury) in patients sustaining combat wounds. Methods: Two hundred combat wounded active-duty service members who sustained high-energy extremity injuries were prospectively enrolled between 2008 and 2012. Of these 200 patients, 189 had adequate followups to determine the presence or absence of HO, and 191 had adequate followups to determine the presence or absence of wound failure. In addition to injury-specific and demographic data, we quantified 24 cytokines and chemokines during each débridement. Patients were followed clinically for 6 weeks, and radiographs were obtained 3 months after definitive wound closure. Associations were investigated between these markers and wound failure or HO, while controlling for known confounders. Results: The presence of an amputation (p < 0.001; odds ratio [OR], 6.1; 95% CI. 1.63-27.2), Injury Severity Score (p = 0.002; OR, 33.2; 95% CI, 4.2-413), wound surface area (p = 0.001; OR, 1.01; 95% CI, 1.002-1.009), serum interleukin (IL)-3 (p = 0.002; OR, 2.41; 95% CI, 1.5-4.5), serum IL-12p70 (p = 0.01; OR, 0.49; 95% CI, 0.27-0.81), effluent IL-3 (p = 0.02; OR, 1.75; 95% CI, 1.2-2.9), and effluent IL-13 (p = 0.006; OR, 0.67; 95% CI, 0.50-0.87) were independently associated with HO formation. Injury Severity Score (p = 0.05; OR, 18; 95% CI, 5.1-87), wound surface area (p = 0.05; OR, 28.7; 95% CI, 1.5-1250), serum procalcitonin ([ProCT] (p = 0.03; OR, 1596; 95% CI, 5.1-1,758,613) and effluent IL-6 (p = 0.02; OR, 83; 95% CI, 2.5-5820) were independently associated with wound failure. Conclusions: We identified associations between patients' systemic and local inflammatory responses and wound-specific complications such as HO and wound failure. However, future efforts to model these data must account for their complex, time dependent, and nonlinear nature. Level of Evidence: Level II, prognostic study. See the Instructions for Authors for a complete description of levels of evidence. [ABSTRACT FROM AUTHOR]

Background: Heterotopic ossification is the ectopic formation of mature lamellar bone in nonosseous tissue. The prevalence of heterotopic ossification following combat injuries is much higher than civilian data would suggest. In certain cases, the aberrant bone formation can envelop major neurovascular structures in the lower extremity, leading to symptomatic neurovascular entrapment. Methods: We describe five consecutive cases of heterotopic ossification leading to symptomatic neurovascular entrapment in the lower extremity as a result of blast trauma and present our method of patient assessment, preoperative planning, and surgical excision. Results: Heterotopic bone was successfully excised without neurovascular injury in all patients. At a mean of twenty months (range, eight to forty-five months) postoperatively, all patients demonstrated continued improvement of their preexcision function. All patients who had neuropathic pain had a decrease in the pain. Those with decreased joint motion regained motion once their wounds were stable. Sensory deficits resolved before motor deficits did. There was no recurrence of clinically relevant heterotopic ossification in this series. Conclusions: Excision of heterotopic bone, particularly with concurrent neurovascular entrapment, can be associated with major short-term and long-term complications. With use of our treatment algorithm, involving careful preoperative planning and meticulous operative excision, heterotopic bone entrapping major neurovascular structures following severe extremity trauma can be safely excised with subsequent clinical improvement. Level of Evidence: Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence. [ABSTRACT FROM AUTHOR]

Background: Successful treatment of pathologic femur fractures can preserve a patient's independence and quality of life. The choice of implant depends on several disease- and patient-specific variables; however, its durability must generally match the patient's estimated life expectancy. Failures do occur, however, it is unclear which implants are associated with greater risk of failure. Questions/Purposes: We evaluated patients with femoral metastases in whom implants failed to determine (1) the rate of reoperation; (2) the timing of and most common causes for failure; and (3) incidence of perioperative complications and death. Methods: From a prospectively collected registry, we identified 93 patients operated on for failed treatment of femoral metastases from 1990 to 2010. We excluded five patients who subsequently underwent amputations leaving 88 who underwent salvage procedures. These included intramedullary nails (n = 11), endoprostheses (n = 61), and plate fixation (n = 16). The primary outcome was reoperation after salvage treatment. Results: Seventeen of the 88 patients (19%) required subsequent reoperation a median of 10 months (interquartile range, 4-14) from the time of salvage surgery: 15 for material failure, one for local progression of tumor, and one for a combination of these. Five patients died within 4 weeks of surgery. Although perioperative complications were higher in the endoprosthesis group and dislocations occurred, overall treatment failures after salvage surgery were lower in the that group (four of 61) compared the group with plate fixation (eight of 16) and intramedullary nail groups (five of 11). Conclusions: Despite relatively common perioperative complications, salvage using endoprostheses may be associated with fewer treatment failures as compared with internal fixation. Level of Evidence: Level III, therapeutic study. See Guidelines for Authors for a complete description of levels of evidence. [ABSTRACT FROM AUTHOR]

Background : To avoid complications associated with under- or overtreatment of patients with skeletal metastases, doctors need accurate survival estimates. Unfortunately, prognostic models for patients with skeletal metastases of the extremities are lacking, and physician-based estimates are generally inaccurate. Questions/purposes: We developed three types of prognostic models and compared them using calibration plots, receiver operating characteristic (ROC) curves, and decision curve analysis to determine which one is best suited for clinical use. Methods: A training set consisted of 189 patients who underwent surgery for skeletal metastases. We created models designed to predict 3- and 12-month survival using three methods: an Artificial Neural Network (ANN), a Bayesian Belief Network (BBN), and logistic regression. We then performed crossvalidation and compared the models in three ways: calibration plots plotting predicted against actual risk; area under the ROC curve (AUC) to discriminate the probability that a patient who died has a higher predicted probability of death compared to a patient who did not die; and decision curve analysis to quantify the clinical consequences of over- or undertreatment. Results: All models appeared to be well calibrated, with the exception of the BBN, which underestimated 3-month survival at lower probability estimates. The ANN models had the highest discrimination, with an AUC of 0.89 and 0.93, respectively, for the 3- and 12-month models. Decision analysis revealed all models could be used clinically, but the ANN models consistently resulted in the highest net benefit, outperforming the BBN and logistic regression models. Conclusions: Our observations suggest use of the ANN model to aid decisions about surgery would lead to better patient outcomes than other alternative approaches to decision making. Level of Evidence: Level II, prognostic study. See Instructions for Authors for a complete description of levels of evidence. [ABSTRACT FROM AUTHOR]

Background: Surgical site infections (SSIs) represent a major complication following oncologic reconstructions. Our objectives were (1) to assess whether the use of postoperative drains and/or negative pressure wound therapy (NPWT) were associated with SSIs following lower-extremity oncologic reconstruction and (2) to identify factors associated with the duration of postoperative drains and with the duration of NPWT. Methods: This is a secondary analysis of the Prophylactic Antibiotic Regimens in Tumor Surgery (PARITY) trial, a multi-institution randomized controlled trial of lower-extremity oncologic reconstructions. Data were recorded regarding the use of drains alone, NPWT alone, or both NPWT and drains, including the total duration of each postoperatively. We analyzed postoperative drain duration and associations with tourniquet use, intraoperative thromboprophylaxis or antifibrinolytic use, incision length, resection length, and total operative time, through use of a linear regression model. A Cox proportional hazards model was used to evaluate the independent predictors of SSI. Results: Overall, 604 patients were included and the incidence of SSI was 15.9%. Postoperative drains alone were used in 409 patients (67.7%), NPWT alone was used in 15 patients (2.5%), and both postoperative drains and NPWT were used in 68 patients (11.3%). The median (and interquartile range [IQR]) duration of drains and of NPWT was 3 days (IQR, 2 to 5 days) and 6 days (IQR, 4 to 8 days), respectively. The use of postoperative drains alone, NPWT alone, or both drains and NPWT was not associated with SSI (p = 0.14). Increased postoperative drain duration was associated with longer operative times and no intraoperative tourniquet use, as shown on linear regression analysis (p < 0.001 and p = 0.03, respectively). A postoperative drain duration of ‡14 days (hazard ratio [HR], 3.6; 95% confidence interval [CI], 1.3 to 9.6; p = 0.01) and an operative time of ‡8 hours (HR, 4.5; 95% CI, 1.7 to 11.9; p = 0.002) were independent predictors of SSI following lower-extremity oncologic reconstruction. Conclusions: A postoperative drain duration of ‡14 days and an operative time of ‡8 hours were independent predictors of SSI following lower-extremity oncologic reconstruction. Neither the use of postoperative drains nor the use of NPWT was a predictor of SSI. Future research is required to delineate the association of the combined use of postoperative drains and NPWT with SSI. [ABSTRACT FROM AUTHOR]

Background: The aim of the present study was to assess the incidence of and risk factors for thromboembolic events—including assessment of the intraoperative use of tranexamic acid and postoperative use of chemical thromboprophylaxis—in patients undergoing operative treatment of primary bone or soft-tissue sarcoma or oligometastatic bone disease. Methods: This study was performed as a secondary analysis of prospective data collected from the Prophylactic Anti)biotic Regimens in Tumor Surgery (PARITY) randomized controlled trial, which included 604 patients ‡12 years old who underwent surgical resection and endoprosthetic reconstruction for either primary bone or soft-tissue sarcoma or oligo)metastatic disease of the femur or tibia. We determined the incidence of thromboembolic events in these patients and evaluated potential risk factors, including patient age, sex, antibiotic treatment group, type of tumor (i.e., primary bone or soft-tissue sarcoma or metastatic bone disease), intraoperative tranexamic acid, tourniquet use, operative time, path)ologic characteristics (i.e., American Joint Committee on Cancer grade, vascular invasion, and percent necrosis), post)operative chemical thromboprophylaxis regimen, and surgical site infection. Continuous variables were assessed with use of the Student t test. Categorical variables were assessed with use of the Pearson chi-square test, except when the expected cell counts were <5, in which case the Fisher exact test was utilized. Significance was set at 0.05. Results: Postoperative thromboembolic events occurred in 11 (1.8%) of 604 patients. Patients who experienced a thromboembolic event had a significantly higher mean (± standard deviation) age (59.6 ± 17.5 years) than those who did not experience a thromboembolic event (40.9 ± 21.8; p = 0.002). Patients randomized to the long-term antibiotic group had a significantly higher incidence of thromboembolic events (9 of 293; 3.1%) than those randomized to the short-term antibiotic group (2 of 311; 0.64%; p = 0.03). Neither intraoperative tranexamic acid nor postoperative chemical thromboprophylaxis were significantly associated with the occurrence of a thromboembolic event. Conclusions: Although relatively rare in the PARITY cohort, thromboembolic events were more likely to occur in older patients and those receiving long-term prophylactic antibiotics. Intraoperative tranexamic acid and postoperative chemical thromboprophylaxis were not associated with a greater incidence of thromboembolic events. [ABSTRACT FROM AUTHOR]

Purpose Skeletal metastases are common in patients with prostate cancer, and they can be a source of considerable morbidity. We analyzed patient survival after surgery for skeletal metastases and identified risk factors for reoperation and complications. Patients and methods This study included 306 patients with prostate cancer operated for skeletal metastases during 1989-2010. Kaplan-Meier analysis was used to calculate survival. Cox multiple regression analysis was performed to study risk factors, and results were expressed as hazard ratios (HRs). Results The median age at surgery was 72 (49-94) years. The median survival after surgery was 0.5 (0-16) years. The cumulative 1-, 2-, and 3-year survival after surgery was 29% (95% CI: 24-34), 14% (10-18), and 8% (5-11). Age over 70 years (HR 1.4), generalized metastases (HR 2.4), and multiple skeletal metastases (HR 2.3) resulted in an increased risk of death after surgery. Patients with lesions in the humerus (HR 0.6) had a lower death rate. The reoperation rate was 9% (n == 31). The reasons for reoperation were deep wound infection (n == 10), hematoma (n == 7), material (implant) failure (n == 3), wound dehiscence (n == 3), increasing neurological symptoms (n == 2), prosthetic dislocation (n == 2), and others (n == 4). Interpretation This study involves the largest reported cohort of patients operated for skeletal lesions from prostate cancer. Our survival data and analysis of predictors for survival help to set appropriate expectations for the patients, families, and medical staff. [ABSTRACT FROM AUTHOR]

Background: We recently developed two Bayesian networks, referred to as the Bayesian-Estimated Tools for Survival (BETS) models, capable of estimating the likelihood of survival at 3 and 12 months following surgery for patients with operable skeletal metastases (BETS-3 and BETS-12, respectively). In this study, we attempted to externally validate the BETS-3 and BETS-12 models using an independent, international dataset. Methods: Data were collected from the Scandinavian Skeletal Metastasis Registry for patients with extremity skeletal metastases surgically treated at eight major Scandinavian referral centers between 1999 and 2009. These data were applied to the BETS-3 and BETS-12 models, which generated a probability of survival at 3 and 12 months for each patient. Model robustness was assessed using the area under the receiver-operating characteristic curve (AUC). An analysis of incorrect estimations was also performed. Results: Our dataset contained 815 records with adequate follow-up information to establish survival at 12 months. All records were missing data including the surgeon’s estimate of survival, which was previously shown to be a first-degree associate of survival in both models. The AUCs for the BETS-3 and BETS-12 models were 0.79 and 0.76, respectively. Incorrect estimations by both models were more commonly optimistic than pessimistic. Conclusions: The BETS-3 and BETS-12 models were successfully validated using an independent dataset containing missing data. These models are the first validated tools for accurately estimating postoperative survival in patients with operable skeletal metastases of the extremities and can provide the surgeon with valuable information to support clinical decisions in this patient population. [ABSTRACT FROM AUTHOR]

Background: Accurate estimations of life expectancy are important in the management of patients with metastatic cancer affecting the extremities, and help set patient, family, and physician expectations. Clinically, the decision whether to operate on patients with skeletal metastases, as well as the choice of surgical procedure, are predicated on an individual patient's estimated survival. Currently, there are no reliable methods for estimating survival in this patient population. Bayesian classification, which includes Bayesian belief network (BBN) modeling, is a statistical method that explores conditional, probabilistic relationships between variables to estimate the likelihood of an outcome using observed data. Thus, BBN models are being used with increasing frequency in a variety of diagnoses to codify complex clinical data into prognostic models. The purpose of this study was to determine the feasibility of developing Bayesian classifiers to estimate survival in patients undergoing surgery for metastases of the axial and appendicular skeleton. Methods: We searched an institution-owned patient management database for all patients who underwent surgery for skeletal metastases between 1999 and 2003. We then developed and trained a machine-learned BBN model to estimate survival in months using candidate features based on historical data. Ten-fold cross-validation and receiver operating characteristic (ROC) curve analysis were performed to evaluate the BNN model's accuracy and robustness. Results: A total of 189 consecutive patients were included. First-degree predictors of survival differed between the 3-month and 12-month models. Following cross validation, the area under the ROC curve was 0.85 (95% CI: 0.80-0.93) for 3-month probability of survival and 0.83 (95% CI: 0.77-0.90) for 12-month probability of survival. Conclusions: A robust, accurate, probabilistic naïve BBN model was successfully developed using observed clinical data to estimate individualized survival in patients with operable skeletal metastases. This method warrants further development and must be externally validated in other patient populations. [ABSTRACT FROM AUTHOR]

The article presents a research study on the development of heterotopic ossification following combat-related trauma. Various clinical factors and biological markers are identified that are prognostic of the formation of combat-related heterotropic ossification which include systemic wound inflammation, traumatic brain injury and amputation surgery. It also adds that computed tomography is needed in the evaluation, treatment and operative excision of combat-related heterotopic ossification.

Background: Heterotopic ossification in the extremities remains a common complication in the setting of high-energy wartime trauma, particularly in blast-injured amputees and in those in whom the definitive amputation was performed within the zone of injury. The purposes of this cohort study were to report the experience of one major military medical center with high-energy wartime extremity wounds, to define the prevalence of heterotopic ossification in these patients, and to explore the relationship between heterotopic ossification and other potential independent predictors. Methods: We retrospectively reviewed the records and radiographs of all combat-wounded patients admitted to this institution between March 1, 2003, and December 31, 2006. Patients with a minimum of two months of radiographic follow-up who underwent at least one orthopaedic procedure on an extremity constituted our study group; those who underwent at least one orthopaedic procedure but had not had heterotopic ossification develop constituted the control group. Variables recorded for each study subject included age and sex, location and mechanism of injury, method(s) of fracture fixation, number of débridement procedures, duration of negative pressure therapy, location of heterotopic ossification, presence and severity of traumatic brain injury, and Injury Severity Scores. Results: During the study period, 1213 war-wounded patients were admitted. Of those patients, 243 (157 in the heterotopic ossification group and eighty-six controls) met the inclusion criteria. The observed rate of heterotopic ossification was 64.6%. A significant relationship was detected between heterotopic ossification and the presence (p = 0.006) and severity (p = 0.003) of a traumatic brain injury. Risk factors forthe development of heterotopic ossification were found to be an age of less than thirty years (p = 0.007, odds ratio = 3.0), an amputation (p = 0.048, odds ratio = 2.9), multiple extremity injuries (p = 0.002, odds ratio = 3.9), and an Injury Severity Score of ≥16 (p = 0.02, odds ratio = 2.2). Conclusions: The prevalence of heterotopic ossification in war-wounded patients is higher than that in civilian trauma. Although trends associated with local wound conditions were identified, the risk factors for the development of heterotopic ossification found in this study suggest that systemic causes predominate. Level of Evidence: Prognostic Level II. See Instructions to Authors for a complete description of levels of evidence. [ABSTRACT FROM AUTHOR]

Background: Despite technological advances in the treatment of severe extremity trauma, the timing of wound closure remains the subjective clinical decision of the treating surgeon. Traditional serum markers are poor predictors of wound-healing. The objective of this study was to evaluate the cytokine and chemokine profiles of severe extremity wounds prior to closure to determine if wound effluent markers can be used to predict healing. Methods: Serum and effluent (exudate) samples were collected prospectively from adult volunteers with multiple high-energy penetrating extremity wounds sustained during military combat. Samples were collected prior to definitive wound closure or flap coverage. Wounds were followed clinically for six weeks. The primary clinical outcome measures were wound-healing and dehiscence. Control serum samples were collected from normal age and sex-matched adult volunteers. All samples were analyzed for the following cytokines and chemokines: procalcitonin; eotaxin; granulocyte macrophage colony stimulating factor; interferon (IFN)-γ interleukin (IL)-1 through 8, 10, 12, 13, and 15; IFN-γ inducible protein-10; monocyte chemotactic protein-1; macrophage inflammatory protein-1α; the protein regulated on activation, normal T expressed and secreted (RANTES); and tumor necrosis factor (TNF)-α. Results: Fifty wounds were analyzed in twenty patients. Four of the fifty wounds dehisced. An increased rate of wound dehiscence was observed in patients with a concomitant closed head injury as well as in those with an associated arterial injury of the affected limb (p < 0.05). Among the serum chemokines and cytokines, only serum procalcitonin levels correlated with wound dehiscence (p < 0.05). Effluent analysis showed that, compared with wounds that healed, wounds that dehisced were associated with elevated procalcitonin, decreased RANTES protein, and decreased IL-13 concentrations (p < 0.05). [ABSTRACT FROM AUTHOR]

Background: Pathologic fracture of the long bones is a common complication of bone metastases. Intramedullary nail stabilization can be used prophylactically (for impending fractures) or therapeutically (for completed fractures) to preserve mobility and quality of life. However, local disease progression may occur after such treatment, and there is concern that surgical instrumentation and the intramedullary nail itself may seed tumor cells along the intramedullary tract, ultimately leading to loss of structural integrity of the construct. Identifying factors associated with local disease progression after intramedullary nail stabilization would help surgeons predict which patients may benefit from alternative surgical strategies.Questions/purposes: (1) Among patients who underwent intramedullary nail stabilization for impending or completed pathologic fractures of the long bones, what is the risk of local progression, including progression of the existing lesion and development of a new lesion around the nail? (2) Among patients who experience local progression, what proportion undergo reoperation? (3) What patient characteristics and treatment factors are associated with postoperative local progression? (4) What is the difference in survival rates between patients who experienced local progression and those with stable local disease?Methods: Between January 2013 and December 2019, 177 patients at our institution were treated with an intramedullary nail for an impending or completed pathologic fracture. We excluded patients who did not have a pathologic diagnosis of metastasis before fixation, who were younger than 18 years of age, who presented with a primary soft tissue mass that eroded into bone, and who experienced nonunion from radiation osteitis or an avulsion fracture rather than from metastasis. Overall, 122 patients met the criteria for our study. Three fellowship-trained orthopaedic oncology surgeons involved in the care of these patients treated an impending or pathologic fracture with an intramedullary nail when a long bone lesion either fractured or was deemed to be of at least 35% risk of fracture within 3 months, and in patients with an anticipated duration of overall survival of at least 6 weeks (fractured) or 3 months (impending) to yield palliative benefit during their lifetime. The most common primary malignancy was multiple myeloma (25% [31 of 122]), followed by lung carcinoma (16% [20 of 122]), breast carcinoma (15% [18 of 122]), and renal cell carcinoma (12% [15 of 122]). The most commonly involved bone was the femur (68% [83 of 122]), followed by the humerus (27% [33 of 122]) and the tibia (5% [6 of 122]). A competing risk analysis was used to determine the risk of progression in our patients at 1 month, 3 months, 6 months, and 12 months after surgery. A proportion of patients who ultimately underwent reoperation due to progression was calculated. A univariate analysis was performed to determine whether lesion progression was associated with various factors, including the age and sex of the patient, use of adjuvant therapies (radiation therapy at the site of the lesion, systemic therapy, and antiresorptive therapy), histologic tumor type, location of the lesion, and fracture type (impending or complete). Patient survival was assessed with a Kaplan-Meier curve. A p value < 0.05 was considered significant.Results: The cumulative incidence of local tumor progression (with death as a competing risk) at 1 month, 3 months, 6 months, and 12 months after surgery was 1.9% (95% confidence interval 0.3% to 6.1%), 2.9% (95% CI 0.8% to 7.5%), 3.9% (95% CI 1.3% to 8.9%), and 4.9% (95% CI 1.8% to 10.3%), respectively. Of 122 patients, 6% (7) had disease progression around the intramedullary nail and 0.8% (1) had new lesions at the end of the intramedullary nail. Two percent (3 of 122) of patients ultimately underwent reoperation because of local progression. The only factors associated with progression were a primary tumor of renal cell carcinoma (odds ratio 5.1 [95% CI 0.69 to 29]; p = 0.03) and patient age (difference in mean age 7.7 years [95% CI 1.2 to 14]; p = 0.02). We found no associations between local disease progression and the presence of visceral metastases, other skeletal metastases, radiation therapy, systemic therapy, use of bisphosphonate or receptor activator of nuclear factor kappa-B ligand inhibitor, type of fracture, or the direction of nail insertion. There was no difference in survivorship curves between those with disease progression and those with stable local disease (= 0.36; p = 0.54).Conclusion: Our analysis suggests that for this population of patients with metastatic bone disease who have a fracture or impeding fracture and an anticipated survival of at least 6 weeks (completed fracture) or 3 months (impending fracture), the risk of experiencing local progression of tumor growth and reoperations after intramedullary nail stabilization seems to be low. Lesion progression was not associated with the duration of survival, although this conclusion is limited by the small number of patients in the current study and the competing risks of survival and local progression. Based on our data, patients who present with renal cell carcinoma should be cautioned against undergoing intramedullary nailing because of the risk of postoperative lesion progression.Level Of Evidence: Level III, therapeutic study. [ABSTRACT FROM AUTHOR]

Objective: Accurate determination of life expectancy becomes very important when determining the treatment of patients with pathologic fractures. We aimed to investigate the predictive role of the PATHFx model in Turkish patients by estimating the area under curve (AUC) of the receiver operator characteristic (ROC) and externally validating the results of PATHFx on the Turkish population. Methods: The data of 122 patients who presented to one of four orthopaedic oncology referral centres in Istanbul (2010–2017) and underwent surgical management of pathologic fractures were retrospectively collected. Patients were evaluated according to age, sex, type of pathologic fracture, presence of organ metastasis, presence of lymph node metastasis, haemoglobin concentration at presentation, primary oncologic diagnosis, number of bone metastases, and Eastern Cooperative Oncology Group (ECOG) status. Estimations of the PATHFx program by months were statistically evaluated using ROC analysis. Results: In our study population (122 patients), all survived the first month, 102 survived the third month, 89 were alive at 6 months, and 58 patients survived at 12 months. At 18 and 24 months, 39 and 27 patients were alive, respectively. The AUC value was 0.677 at 3 months, 0.695 at 6 months, 0.69 at 12 months, 0.674 at 18 months, and 0.693 at 24 months. The 3-, 6-, 12-, 18-, and 24-month survival rates were statistically significant (P < 0.01 and P < 0.05). ECOG performance status was 0–2 points in 33 patients (Memorial Sloan-Kettering Cancer Center (MSKCC) data set: 93 cases, our data set: 33 cases). ECOG performance status was 3–4 points in 89 patients (MSKCC data set: 96 cases, our data set: 89 cases). Conclusions: The objective data used by PATHFx for prediction provided statistically accurate estimates on Turkish patients, who are presumed to have mixed genomes through history from both Europe and Asia, and demonstrates its applicability to the Turkish population. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the author discusses papers presented in the tenth Extremity War Injuries and Disaster Preparedness Symposium regarding the advance of science and technology of combat casualty care.

The article presents the authors' comments on the study "Wait-and-See Policy as a First-Line Management for Extra-Abdominal Desmoid Tumors," by Sylvain Briand. It is commented that one of the limitations of the study is the retrospective nature of the review and the modest total number of patients with primary or recurrent extra-abdominal desmoid tumors included.

The authors comment on a report within the issue, "Are Dropped Osteoarticular Bone Fragments Safely Reimplantable in Vivo?" by Benjamin Bruce and colleagues. The study looks at the effectiveness of methods of decontamination of bone fragments in inhibiting environmental Staphylococcus and Bacillus bacteria and preserving chondrocyte viability. The decontamination techniques include disinfectant or saline solutions, bulb syringe irrigation rinse, and mechanical scrubbing with bristled sponges.

Background: Objective means of estimating survival can be used to guide surgical decision-making and to risk-stratify patients for clinical trials. Although a free, online tool ( www.pathfx.org ) can estimate 3- and 12-month survival, recent work, including a survey of the Musculoskeletal Tumor Society, indicated that estimates at 1 and 6 months after surgery also would be helpful. Longer estimates help justify the need for more durable and expensive reconstructive options, and very short estimates could help identify those who will not survive 1 month and should not undergo surgery. Thereby, an important use of this tool would be to help avoid unsuccessful and expensive surgery during the last month of life.Questions/purposes: We seek to provide a reliable, objective means of estimating survival in patients with metastatic bone disease. After generating models to derive 1- and 6-month survival estimates, we determined suitability for clinical use by applying receiver operator characteristic (ROC) (area under the curve [AUC] > 0.7) and decision curve analysis (DCA), which determines whether using PATHFx can improve outcomes, but also discerns in which kinds of patients PATHFx should not be used.Methods: We used two, existing, skeletal metastasis registries chosen for their quality and availability. Data from Memorial Sloan-Kettering Cancer Center (training set, n = 189) was used to develop two Bayesian Belief Networks trained to estimate the likelihood of survival at 1 and 6 months after surgery. Next, data from eight major referral centers across Scandinavia (n = 815) served as the external validation set-that is, as a means to test model performance in a different patient population. The diversity of the data between the training set from Memorial Sloan-Kettering Cancer Center and the Scandinavian external validation set is important to help ensure the models are applicable to patients in various settings with differing demographics and treatment philosophies. We considered disease-specific, laboratory, and demographic information, and the surgeon's estimate of survival. For each model, we calculated the area under the ROC curve (AUC) as a metric of discriminatory ability and the Net Benefit using DCA to determine whether the models were suitable for clinical use.Results: On external validation, the AUC for the 1- and 6-month models were 0.76 (95% CI, 0.72-0.80) and 0.76 (95% CI, 0.73-0.79), respectively. The models conferred a positive net benefit on DCA, indicating each could be used rather than assume all patients or no patients would survive greater than 1 or 6 months, respectively.Conclusions: Decision analysis confirms that the 1- and 6-month Bayesian models are suitable for clinical use.Clinical Relevance: These data support upgrading www.pathfx.org with the algorithms described above, which is designed to guide surgical decision-making, and function as a risk stratification method in support of clinical trials. This updating has been done, so now surgeons may use any web browser to generate survival estimates at 1, 3, 6, and 12 months after surgery, at no cost. Just as short estimates of survival help justify palliative therapy or less-invasive approaches to stabilization, more favorable survival estimates at 6 or 12 months are used to justify more durable, complicated, and expensive reconstructive options. [ABSTRACT FROM AUTHOR]

Background: The complexity and severity of traumatic wounds in military and civilian trauma demands improved wound assessment, before, during, and after treatment. Here, we explore the potential of 3 charge-coupled device (3CCD) imaging values to distinguish between traumatic wounds that heal following closure and those that fail. Previous studies demonstrate that normalized 3CCD imaging values exhibit a high correlation with oxygen saturation and allow for comparison of values between diverse clinical settings, including utilizing different equipment and lighting. Methods: We screened 119 patients at Walter Reed National Military Medical Center and at Grady Memorial Hospital with at least one traumatic extremity wound of ≥ 75 cm2. We collected images of each wound during each débridement surgery for a total of 66 patients. An in-house written computer application selected a region of interest in the images, separated the pixel color values, calculated relative values, and normalized them. We followed patients until the enrolled wounds were surgically closed, quantifying the number of wounds that dehisced (defined as wound failure or infection requiring return to the operating room after closure) or healed. Results: Wound failure occurred in 20% (19 of 96) of traumatic wounds. Normalized intensity values for patients with wounds that healed successfully were, on average, significantly different from values for patients with wounds that failed (p ≤ 0.05). Simple thresholding models and partial least squares discriminant analysis models performed poorly. However, a hierarchical cluster analysis model created with 17 variables including 3CCD data, wound surface area, and time from injury predicts wound failure with 76.9% sensitivity, 76.5% specificity, 76.6% accuracy, and a diagnostic odds ratio of 10.8 (95% confidence interval: 2.6–45.9). Conclusions: Imaging using 3CCD technology may provide a non-invasive and cost-effective method of aiding surgeons in deciding if wounds are ready for closure and could potentially decrease the number of required débridements and hospital days. The process may be automated to provide real-time feedback in the operating room and clinic. The low cost and small size of the cameras makes this technology attractive for austere and shipboard environments where space and weight are at a premium. [ABSTRACT FROM AUTHOR]

Background: Objective survival estimates are important when treating or studying outcomes in patients with skeletal metastases. One decision-support tool, PATHFx (www.pathfx.org) is designed to predict each patient's postsurgical survival trajectory at 1, 3, 6, and 12 months in patients undergoing stabilization for skeletal metastases. PATHFx has been externally validated in various western centers, but it is unknown whether it may be useful in Asian patient populations.Questions/purposes: We asked (1) whether the PATHFx models are as predictive in Japanese patients by estimating the area under the receiver operator characteristic curve (AUC); we considered an AUC greater than 0.7 as an adequate predictive value. We also (2) performed decision curve analysis at various times to determine whether and how PATHFx should be used clinically at those times.Patients and Methods: A Bayesian model is a statistical method to explore conditional, probabilistic relationships between variables to estimate the likelihood of an outcome using observed data. We applied the PATHFx Bayesian models to an independent dataset containing the records of patients who underwent skeletal stabilization for metastatic bone disease at one of five Japanese referral centers and had a followup longer than 12 months for survivors. Of 270 patients in the database, we excluded nine patients from analysis because their followup was less than 12 months, and finally we included 261 patients in the analysis. Data examined included age at the time of surgery, sex, indication for surgery (impending fracture or completed pathologic fracture), number of bone metastases (solitary or multiple), presence or absence of visceral or lymph node metastases, preoperative hemoglobin concentration, absolute lymphocyte count, and the primary oncologic diagnosis. We performed receiver operating characteristic curve analysis and estimated the AUC as a measure of discriminatory ability. Decision curve analysis was performed to determine if and how the models should be used in the clinical setting.Results: The AUCs for the 1-, 3-, 6-, and 12-month models were 0.77 (95% CI, 0.63-0.86), 0.80 (95% CI, 0.72-0.87), 0.83 (95% CI, 0.77-0.89), and 0.80 (95% CI, 0.75-0.86), respectively. Decision analysis indicated that the models conferred a positive net benefit (above the lines assuming none or all survive at each time) although the CIs of the AUC for 1 month were wide, suggesting that this dataset could not adequately predict 1-month survival.Conclusions: Our findings show PATHFx is suitable for clinical use in Japan and may be used to guide surgical decision making or as a risk stratification method in support of clinical trials involving Japanese patients at 3, 6, and 12 months. More studies will be necessary to confirm the validity of the 1-month survival predictions of this mode. Other patient populations will need to be studied to confirm its usefulness in other non-Western and non-Japanese populations.Level Of Evidence: Level II, prognostic study. [ABSTRACT FROM AUTHOR]

Background: Extremity sarcoma has a preponderance to present late with advanced stage at diagnosis. It is important to know why these patients die early from sarcoma and to predict those at high risk. Currently we have mid- to long-term outcome data on which to counsel patients and support treatment decisions, but in contrast to other cancer groups, very little on short-term mortality. Bayesian belief network modeling has been used to develop decision-support tools in various oncologic diagnoses, but to our knowledge, this approach has not been applied to patients with extremity sarcoma.Questions/purposes: We sought to (1) determine whether a Bayesian belief network could be used to estimate the likelihood of 1-year mortality using receiver operator characteristic analysis; (2) describe the hierarchal relationships between prognostic and outcome variables; and (3) determine whether the model was suitable for clinical use using decision curve analysis.Methods: We considered all patients treated for primary bone sarcoma between 1970 and 2012, and excluded secondary metastasis, presentation with local recurrence, and benign tumors. The institution's database yielded 3499 patients, of which six (0.2%) were excluded. Data extracted for analysis focused on patient demographics (age, sex), tumor characteristics at diagnosis (size, metastasis, pathologic fracture), survival, and cause of death. A Bayesian belief network generated conditional probabilities of variables and survival outcome at 1 year. A lift analysis determined the hierarchal relationship of variables. Internal validation of 699 test patients (20% dataset) determined model accuracy. Decision curve analysis was performed comparing net benefit (capped at 85.5%) for all threshold probabilities (survival output from model).Results: We successfully generated a Bayesian belief network with five first-degree associates and describe their conditional relationship with survival after the diagnosis of primary bone sarcoma. On internal validation, the resultant model showed good predictive accuracy (area under the curve [AUC] = 0.767; 95% CI, 0.72-0.83). The factors that predict the outcome of interest, 1-year mortality, in order of relative importance are synchronous metastasis (6.4), patient's age (3), tumor size (2.1), histologic grade (1.8), and presentation with a pathologic fracture (1). Patient's sex, tumor location, and inadvertent excision were second-degree associates and not directly related to the outcome of interest. Decision curve analysis shows that clinicians can accurately base treatment decisions on the 1-year model rather than assuming all patients, or no patients, will survive greater than 1 year. For threshold probabilities less than approximately 0.5, the model is no better or no worse than assuming all patients will survive.Conclusions: We showed that a Bayesian belief network can be used to predict 1-year mortality in patients presenting with a primary malignancy of bone and quantified the primary factors responsible for an increased risk of death. Synchronous metastasis, patient's age, and the size of the tumor had the largest prognostic effect. We believe models such as these can be useful as clinical decision-support tools and, when properly externally validated, provide clinicians and patients with information germane to the treatment of bone sarcomas.Clinical Relevance: Bone sarcomas are difficult to treat requiring multidisciplinary input to strategize management. An evidence-based survival prediction can be a powerful adjunctive to clinicians in this scenario. We believe the short-term predictions can be used to evaluate services, with 1-year mortality already being a quality indicator. Mortality predictors also can be incorporated in clinical trials, for example, to identify patients who are least likely to experience the side effects of experimental toxic chemotherapeutic agents. [ABSTRACT FROM AUTHOR]

Background: Patients with complex polytrauma in the military and civilian settings are often exposed to substantial diagnostic medical radiation because of serial imaging studies for injury diagnosis and subsequent management. This cumulative radiation exposure may increase the risk of subsequent malignancy. This is particularly true for combat-injured servicemembers who receive care at a variety of facilities worldwide. Currently, there is no coordinated effort to track the amount of radiation exposure each servicemember receives, nor a surveillance program to follow such patients in the long term. It is important to assess whether military servicemembers are exposed to excessive diagnostic radiation to mitigate or prevent such occurrences and monitor for carcinogenesis, when necessary. The cumulative amount of radiation exposure for combat-wounded and noncombat-wounded servicemembers has not been described, and it remains unknown whether diagnostic radiation exposure meets thresholds for an increased risk of carcinogenesis. Questions/purposes: We performed this study to (1) quantify the amount of exposure for combat-wounded servicemembers based on medical imaging in the first year after injury and compare those exposures with noncombat-related trauma, and (2) determine whether the cumulative dose of radiation correlates to the Injury Severity Score (ISS) across the combat-wounded and noncombat-wounded population combined. Methods: We performed a retrospective study of servicemembers who sustained combat or noncombat trauma and were treated at Walter Reed National Military Medical Center from 2005 to 2018. We evaluated patients using the Department of Defense Trauma Registry. After consolidating redundant records, the dataset included 3812 unique servicemember encounters. Three percent (104 of 3812) were excluded because of missing radiation exposure data in the electronic medical record. The final cohort included 3708 servicemembers who had combat or noncombat injury trauma, with a mean age at the time of injury of 26 ± 6 years and a mean ISS of 18 ± 12. The most common combat trauma mechanisms of injury were blast (in 65% [2415 of 3708 patients]), followed by high-velocity gunshot wounds (in 22% [815 of 3708 patients]). We calculated the cumulative diagnostic radiation dose exposure at 1 year post-traumatic injury in patients with combat-related trauma and those with noncombat trauma. We did this by multiplying the number of imaging studies by the standardized effective radiation dose for each imaging study type. We then performed analysis of variance for four data subsets (battle combat trauma, nonbattle civilian trauma, high ISS, and high radiation exposure [> 50 mSv]) independently. To evaluate whether the total number of imaging studies, radiation exposure, and ISS values differed between battle-wounded and nonbattle-wounded patients, we performed a pairwise t-test. Results: The mean radiation exposure for combat-related injuries was 35 ± 26 mSv while the mean radiation exposure for noncombat-related injuries was 22 ± 33 mSv in the first year after injury. In the first year after trauma, 44% of patients (1626 of 3708) were exposed to high levels of radiation that were greater than 20 mSv, and 23% (840 of 3708) were exposed to very high levels of radiation that were greater than 50 mSv. Servicemembers with combat trauma-related injuries had eight more imaging studies than those who sustained noncombat injuries. Servicemembers with combat trauma injuries (35 ± 26 mSv) were exposed to more radiation (approximately 4 mSv) than patients treated for noncombat injuries (22 ± 33 mSv) (p = 0.01). We found that servicemembers with combat injuries had a higher ISS than servicemembers with noncombat trauma (p < 0.001). We found a positive correlation between radiation exposure and ISS for servicemembers. The positive relationship between radiation exposure and ISS held for combat trauma (r2 = 0.24; p < 0.001), noncombat trauma (r2 = 0.20; p < 0.001), servicemembers with a high ISS (r2 = 0.10; p < 0.001), and servicemembers exposed to high doses of radiation (r2 = 0.09; p < 0.001). Conclusion: These data should be used during clinical decision-making and patient counseling at military treatment facilities and might provide guidance to the Defense Health Agency. These recommendations will help determine whether the benefits of further imaging outweigh the risk of carcinogenesis. If not, we need to develop interdisciplinary clinical practice guidelines to reduce or minimize radiation exposure. It is important for treating physicians to seriously weigh the risk and benefits of every imaging study ordered because each test does not come without a cumulative risk. Level of Evidence: Level III, therapeutic study. [ABSTRACT FROM AUTHOR]

Background: We recently developed a clinical decision support tool, capable of estimating the likelihood of survival at 3 and 12 months following surgery for patients with operable skeletal metastases. After making it publicly available on www.PATHFx.org, we attempted to externally validate it using independent, international data. Methods: We collected data from patients treated at 13 Italian orthopaedic oncology referral centers between 2010 and 2013, then applied to PATHFx, which generated a probability of survival at three and 12-months for each patient. We assessed accuracy using the area under the receiver-operating characteristic curve (AUC), clinical utility using Decision Curve Analysis (DCA), and compared the Italian patient data to the training set (United States) and first external validation set (Scandinavia). Results: The Italian dataset contained 287 records with at least 12 months follow-up information. The AUCs for the three-month and 12-month estimates was 0.80 and 0.77, respectively. There were missing data, including the surgeon's estimate of survival that was missing in the majority of records. Physiologically, Italian patients were similar to patients in the training and first validation sets. However notable differences were observed in the proportion of those surviving three and 12-months, suggesting differences in referral patterns and perhaps indications for surgery. Conclusions: PATHFx was successfully validated in an Italian dataset containing missing data. This study demonstrates its broad applicability to European patients, even in centers with differing treatment philosophies from those previously studied. [ABSTRACT FROM AUTHOR]

Background Blast wounds often involve diverse tissue types and require substantial time and treatment for appropriate healing. Some of these subsequent wounds become colonized with bacteria requiring a better understanding of how the host responds to these bacteria and what proteomic factors contribute wound healing outcome. In addition, using reliable and effective proteomic sample preparation procedures can lead to novel biomarkers for improved diagnosis and therapy. Results To address this need, suitable sample preparation for 2-D DIGE proteomic characterization of wound effluent and serum samples from combat-wounded patients was investigated. Initial evaluation of crude effluent and serum proved the necessity of high abundant protein depletion. Subsequently, both samples were successfully depleted using Agilent Multiple Affinity Removal system and showed greatly improved 2-D spot maps, comprising 1,800 and 1,200 protein spots, respectively. Conclusion High abundant protein removal was necessary for both wound effluent and serum. This is the first study to show a successful method for high abundant protein depletion from wound effluent which is compatible with downstream 2-D DIGE analysis. This development allows for improved biomarker discovery in wound effluent and serum samples. [ABSTRACT FROM AUTHOR]

Background The ability to forecast whether a wound will heal after closure without further debridement(s), would provide substantial benefits to patients with severe extremity trauma. Methods Wound effluent is a readily available material which can be collected without disturbing healthy tissue. For analysis of potential host response biomarkers, forty four serial combat wound effluent samples from 19 patients with either healing or failing traumatic- and other combat-related wounds were examined by 2-D DIGE. Spot map patterns were correlated to eventual wound outcome (healed or wound failure) and analyzed using DeCyder 7.0 and differential proteins identified via LC-MS/MS. Results This approach identified 52 protein spots that were differentially expressed and thus represent candidate biomarkers for this clinical application. Many of these proteins are intimately involved in inflammatory and immune responses. Furthermore, discriminate analysis further refined the 52 differential protein spots to a smaller subset of which successfully differentiate between wounds that will heal and those that will fail and require further surgical intervention with greater than 83% accuracy. Conclusion These results suggest candidates for a panel of protein biomarkers that may aid traumatic wound care prognosis and treatment. We recommend that this strategy be refined, and then externally validated, in future studies of traumatic wounds. [ABSTRACT FROM AUTHOR]

Background: The impact of local recurrence and surgical resection margin status on survival in extremity soft-tissue sarcomas remains to be clearly defined. Our aim was to conduct a retrospective analysis of prospectively collected data to determine the prognostic relavance of positive resection margins and local recurrence for extremity soft-tissue sarcomas for survival. Methods: Three hundred and sixty-three patients who underwent resection of localized primary extremity soft-tissue sarcomas with curative intent were selected from the United States Department of Defense Automated Central Tumor Registry. Outcomes for local recurrence, distant recurrence, disease-specific survival, and overall survival were analyzed according to clinical, pathological, and treatment variables with use of the Kaplan-Meier method (log-rank test) and the multivariate Cox regression model. Results: Positive margins (hazard ratio, 1.99 [95% confidence interval, 1.15 to 3.45]), local recurrence (hazard ratio, 2.93 [95% confidence interval, 1.38 to 6.23]), and distant recurrence (hazard ratio, 12.13 [95% confidence interval, 5.97 to 24.65]) were significantly associated with overall survival on multivariate Cox regression analysis. However, for disease-specific survival, local recurrence was not significant and tumor size of >10 cm (hazard ratio, 2.83 [95% confidence interval, 1.15 to 6.95]), positive margins (hazard ratio, 1.95 [95% confidence interval, 1.05 to 3.63]), and distant recurrence (hazard ratio, 9.46 [95% confidence interval, 4.37 to 20.47]) were independent adverse prognostic factors. The disease-specific survival rate for patients with localized soft-tissue sarcomas was 89% (95% confidence interval, 85% to 92%) for five years and 75% (95% confidence interval, 70% to 81%) for ten years. Conclusions: Positive surgical margins are consistently associated with adverse survival-related outcomes in localized soft-tissue sarcomas of the extremity. Local recurrence had a significant impact on overall survival, but not on diseasespecific survival. Level of Evidence: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence. [ABSTRACT FROM AUTHOR]

Background: The prevalence of penetrating wartime trauma to the extremities has increased in recent military conflicts. Substantial controversy remains in the orthopaedic and prosthetic literature regarding which surgical technique should be performed to obtain the most functional transtibial amputation. We compared self-reported functional outcomes associated with two surgical techniques for transtibial amputation: bridge synostosis (modified Ertl) and non-bone-bridging (modified Burgess). Methods: A review of the prospective military amputee database was performed to identify patients who had undergone transtibial amputation between June 2003 and December 2010 at three military institutions receiving the majority of casualties from the most recent military conflicts; two of those institutions, Walter Reed Army Medical Center and National Naval Medical Center, have since been consolidated. Short Form-36, Prosthesis Evaluation Questionnaire, and functional data questions were completed by twenty-seven modified Ertl and thirty-eight modified Burgess isolated transtibial amputees. Results: The average duration of follow-up after amputation (and standard deviation) was 32 ± 22.7 months, which was similar between groups. Residual limb length was significantly longer in the modified Ertl cohort by 2.5cm (p <0.005), and significantly more modified Ertl patients had delayed amputations (p < 0.005). There were no significant differences between groups with regard to any of the Short Form-36 domains or Prosthesis Evaluation Questionnaire subsections. Conclusions: The modified Ertl and Burgess techniques offer similar functional outcomes in the young, active-duty military population managed with transtibial amputation. Level of Evidence: Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence. [ABSTRACT FROM AUTHOR]

Chondrosarcoma is the third most common primary malignant bone tumor. Currently, outcomes are based largely on a histologic grading scale described by the World Health Organization (WHO) Classification of Bone Tumors (2002). This classification scheme possesses evident utility in the evaluation and management of higher grade tumors, but it is often unable to distinguish enchondromas from low-grade chondrosarcomas. This is problematic when low-grade lesions that are histologically similar to enchondromas demonstrate aggressive imaging features. Because histologic classification alone often belies the clinical significance of chondroid lesions, it is also important to consider radiologic staging as part of the clinical decision making process. This article focuses onmedical decision support considerations relevant when confronted with this challenging subset of chondroid tumors, particularly differentiating the benign enchondroma from its notorious relative, the low-grade chondrosarcoma. In doing so, we present a review of the salient imaging features and discuss key differentiating characteristics. [ABSTRACT FROM AUTHOR]

Background: The complications of bone-bridging amputations remain ill defined. The purpose of this study was to compare the early and intermediate-term complications leading to reoperation between the modified Burgess and modified ErtI tibiofibular synostosis in combat-related transtibial amputations. Methods: We conducted a retrospective review of consecutive, contemporaneous cohorts of thirty-seven modified ErtI bone-bridge and 100 modified Burgess combat-related transtibial amputations. The primary outcome measure was the need for reoperation following definitive closure. Results: At a mean follow-up of two years (range, nine to forty-eight months), there was a 53% overall reoperation rate. The overall complications included infection (34%), neuroma excision (18%), heterotopic ossification excision (15%), myodesis failure (4%), and scar revision (7%). A significantly higher rate of overall complications (p = 0.008) was noted in the bone-bridge group. Additionally, there was an increased rate of noninfectious complications in the bone-bridge group (p = 0.02). A positive selection bias was also noted for performing bone-bridge amputations late (p = 0.0002) and outside the zone of injury (p < 0.0001). Bone-bridge-specific complications occurred in 32% of the modified ErtI group. Delayed union or nonunion of the synostosis (11%) and implant-related complications (27%) predominated. Three bone bridges were ultimately removed. Conclusions: Reoperations were needed at a significantly greater rate overall and for noninfectious complications following bone-bridge synostosis compared with modified Burgess transtibial amputations. Additionally, despite the positive selection bias favoring the bridge synostosis cohort, infection rates were not lower in that group. Detailed patient counseling and careful patient selection are indicated prior to performing modified ErtI amputations, particularly in the absence of convincing evidence regarding objective functional benefits from the procedure. [ABSTRACT FROM AUTHOR]

Background: Prognostic indicators, treatments, and survival estimates vary by cancer type. Therefore, disease-specific models are needed to estimate patient survival. Our primary aim was to develop models to estimate survival duration after treatment for skeletal-related events (SREs) (symptomatic bone metastasis, including impending or actual pathologic fractures) in men with metastatic bone disease due to prostate cancer. Such disease-specific models could be added to the PATHFx clinical-decision support tool, which is available worldwide, free of charge. Our secondary aim was to determine disease-specific factors that should be included in an international cancer registry.Methods: We analyzed records of 438 men with metastatic prostate cancer who sustained SREs that required treatment with radiotherapy or surgery from 1989-2017. We developed and validated 6 models for 1-, 2-, 3-, 4-, 5-, and 10-year survival after treatment. Model performance was evaluated using calibration analysis, Brier scores, area under the receiver operator characteristic curve (AUC), and decision curve analysis to determine the models' clinical utility. We characterized the magnitude and direction of model features.Results: The models exhibited acceptable calibration, accuracy (Brier scores < 0.20), and classification ability (AUCs > 0.73). Decision curve analysis determined that all 6 models were suitable for clinical use. The order of feature importance was distinct for each model. In all models, 3 factors were positively associated with survival duration: younger age at metastasis diagnosis, proximal prostate-specific antigen (PSA) < 10 ng/mL, and slow-rising alkaline phosphatase velocity (APV).Conclusions: We developed models that estimate survival duration in patients with metastatic bone disease due to prostate cancer. These models require external validation but should meanwhile be included in the PATHFx tool. PSA and APV data should be recorded in an international cancer registry. [ABSTRACT FROM AUTHOR]

Background: Transdermal osseointegrated prosthesis have relatively high infection rates leading to implant revision or failure. A principle cause for this complication is the absence of a durable impervious biomechanical seal at the interface of the hard structure (implant) and adjacent soft tissues. This study explores the possibility of recapitulating an analogous cellular musculoskeletal-connective tissue interface, which is present at naturally occurring integumentary tissues where a hard structure exits the skin, such as the nail bed, hoof, and tooth. Methods: Porcine mesenchymal stromal cells (pMSCs) were derived from nine different porcine integumentary and connective tissues: hoof-associated superficial flexor tendon, molar-associated periodontal ligament, Achilles tendon, adipose tissue and skin dermis from the hind limb and abdominal regions, bone marrow and muscle. For all nine pMSCs, the phenotype, multi-lineage differentiation potential and their adhesiveness to clinical grade titanium was characterized. Transcriptomic analysis of 11 common genes encoding cytoskeletal proteins VIM (Vimentin), cell–cell and cell–matrix adhesion genes (Vinculin, Integrin β1, Integrin β2, CD9, CD151), and for ECM genes (Collagen-1a1, Collagen-4a1, Fibronectin, Laminin-α5, Contactin-3) in early passaged cells was performed using qRT-PCR. Results: All tissue-derived pMSCs were characterized as mesenchymal origin by adherence to plastic, expression of cell surface markers including CD29, CD44, CD90, and CD105, and lack of hematopoietic (CD11b) and endothelial (CD31) markers. All pMSCs differentiated into osteoblasts, adipocytes and chondrocytes, albeit at varying degrees, under specific culture conditions. Among the eleven adhesion genes evaluated, the cytoskeletal intermediate filament vimentin was found highly expressed in pMSC isolated from all tissues, followed by genes for the extracellular matrix proteins Fibronectin and Collagen-1a1. Expression of Vimentin was the highest in Achilles tendon, while Fibronectin and Col1agen-1a1 were highest in molar and hoof-associated superficial flexor tendon bone marrow, respectively. Achilles tendon ranked the highest in both multilineage differentiation and adhesion assessments to titanium metal. Conclusions: These findings support further preclinical research of these tissue specific-derived MSCs in vivo in a transdermal osseointegration implant model. [ABSTRACT FROM AUTHOR]

Treatment decisions in patients with metastatic bone disease rely on accurate survival estimation. We developed the original PATHFx models using expensive, proprietary software and now seek to provide a more cost‐effective solution. Using open‐source machine learning software to create PATHFx version 2.0, we asked whether PATHFx 2.0 could be created using open‐source methods and externally validated in two unique patient populations. The training set of a well‐characterized, database records of 189 patients and the bnlearn package within R Version 3.5.1 (R Foundation for Statistical Computing), was used to establish a series of Bayesian belief network models designed to predict survival at 1, 3, 6, 12, 18, and 24 months. Each was externally validated in both a Scandinavian (n = 815 patients) and a Japanese (n = 261 patients) data set. Brier scores and receiver operating characteristic curves to assessed discriminatory ability. Decision curve analysis (DCA) evaluated whether models should be used clinically. DCA showed that the model should be used clinically at all time points in the Scandinavian data set. For the 1‐month time point, DCA of the Japanese data set suggested to expect better outcomes assuming all patients will survive greater than 1 month. Brier scores for each curve demonstrate that the models are accurate at each time point. Statement of Clinical Significance: we successfully transitioned to PATHFx 2.0 using open‐source software and externally validated it in two unique patient populations, which can be used as a cost‐effective option to guide surgical decisions in patients with metastatic bone disease. [ABSTRACT FROM AUTHOR]

Background: Revision TKA is a serious adverse event with substantial consequences for the patient. As the demand for TKA rises, reducing the risk of revision TKA is becoming increasingly important. Predictive tools based on machine-learning algorithms could reform clinical practice. Few attempts have been made to combine machine-learning algorithms with data from nationwide arthroplasty registries and, to the authors' knowledge, none have tried to predict the likelihood of early revision TKA.Question/purposes: We used the Danish Knee Arthroplasty Registry to build models to predict the likelihood of revision TKA within 2 years of primary TKA and asked: (1) Which preoperative factors were the most important features behind these models' predictions of revision? (2) Can a clinically meaningful model be built on the preoperative factors included in the Danish Knee Arthroplasty Registry?Methods: The Danish Knee Arthroplasty Registry collects patients' characteristics and surgical information from all arthroplasties conducted in Denmark and thus provides a large nationwide cohort of patients undergoing TKA. As training dataset, we retrieved all preoperative variables of 25,104 primary TKAs from 2012 to 2015. The same variables were retrieved from 6170 TKAs conducted in 2016, which were used as a hold-out year for temporal external validation. If a patient received bilateral TKA, only the first knee to receive surgery was included. All patients were followed for 2 years, with removal, exchange, or addition of an implant defined as TKA revision. We created four different predictive models to find the best performing model, including a regression-based model using logistic regression with least shrinkage and selection operator (LASSO), two classification tree models (random forest and gradient boosting model) and a supervised neural network. For comparison, we created a noninformative model predicting that all observations were unrevised. The four machine learning models were trained using 10-fold cross-validation on the training dataset after adjusting for the low percentage of revisions by over-sampling revised observations and undersampling unrevised observations. In the validation dataset, the models' performance was evaluated and compared by density plot, calibration plot, accuracy, Brier score, receiver operator characteristic (ROC) curve and area under the curve (AUC). The density plot depicts the distribution of probabilities and the calibration plot graphically depicts whether the predicted probability resembled the observed probability. The accuracy indicates how often the models' predictions were correct and the Brier score is the mean distance from the predicted probability to the observed outcome. The ROC curve is a graphical output of the models' sensitivity and specificity from which the AUC is calculated. The AUC can be interpreted as the likelihood that a model correctly classified an observation and thus, a priori, an AUC of 0.7 was chosen as threshold for a clinically meaningful model.Results: Based the model training, age, postfracture osteoarthritis and weight were deemed as important preoperative factors within the machine learning models. During validation, the models' performance was not different from the noninformative models, and with AUCs ranging from 0.57 to 0.60, no models reached the predetermined AUC threshold for a clinical useful discriminative capacity.Conclusion: Although several well-known presurgical risk factors for revision were coupled with four different machine learning methods, we could not develop a clinically useful model capable of predicting early TKA revisions in the Danish Knee Arthroplasty Registry based on preoperative data.Clinical Relevance: The inability to predict early TKA revision highlights that predicting revision based on preoperative information alone is difficult. Future models might benefit from including medical comorbidities and an anonymous surgeon identifier variable or may attempt to build a postoperative predictive model including intra- and postoperative factors as these may have a stronger association with early TKA revisions. [ABSTRACT FROM AUTHOR]

Background: Machine-learning methods such as the Bayesian belief network, random forest, gradient boosting machine, and decision trees have been used to develop decision-support tools in other clinical settings. Opioid abuse is a problem among civilians and military service members, and it is difficult to anticipate which patients are at risk for prolonged opioid use.Questions/purposes: (1) To build a cross-validated model that predicts risk of prolonged opioid use after a specific orthopaedic procedure (ACL reconstruction), (2) To describe the relationships between prognostic and outcome variables, and (3) To determine the clinical utility of a predictive model using a decision curve analysis (as measured by our predictive system's ability to effectively identify high-risk patients and allow for preventative measures to be taken to ensure a successful procedure process).Methods: We used the Military Analysis and Reporting Tool (M2) to search the Military Health System Data Repository for all patients undergoing arthroscopically assisted ACL reconstruction (Current Procedure Terminology code 29888) from January 2012 through December 2015 with a minimum of 90 days postoperative follow-up. In total, 10,919 patients met the inclusion criteria, most of whom were young men on active duty. We obtained complete opioid prescription filling histories from the Military Health System Data Repository's pharmacy records. We extracted data including patient demographics, military characteristics, and pharmacy data. A total of 3.3% of the data was missing. To curate and impute all missing variables, we used a random forest algorithm. We shuffled and split the data into 80% training and 20% hold-out sets, balanced by outcome variable (Outcome90Days). Next, the training set was further split into training and validation sets. Each model was built on the training data set, tuned with the validation set as applicable, and finally tested on the separate hold-out dataset. We chose four predictive models to develop, at the end choosing the best-fit model for implementation. Logistic regression, random forest, Bayesian belief network, and gradient boosting machine models were the four chosen models based on type of analysis (classification). Each were trained to estimate the likelihood of prolonged opioid use, defined as any opioid prescription filled more than 90 days after anterior cruciate reconstruction. After this, we tested the models on our holdout set and performed an area under the curve analysis concordance statistic, calculated the Brier score, and performed a decision curve analysis for validation. Then, we chose the method that produced the most suitable analysis results and, consequently, predictive power across the three calculations. Based on the calculations, the gradient boosting machine model was selected for future implementation. We systematically selected features and tuned the gradient boosting machine to produce a working predictive model. We performed area under the curve, Brier, and decision curve analysis calculations for the final model to test its viability and gain an understanding of whether it is possible to predict prolonged opioid use.Results: Four predictive models were successfully developed using gradient boosting machine, logistic regression, Bayesian belief network, and random forest methods. After applying the Boruta algorithm for feature selection based on a 100-tree random forest algorithm, features were narrowed to a final seven features. The most influential features with a positive association with prolonged opioid use are preoperative morphine equivalents (yes), particular pharmacy ordering sites locations, shorter deployment time, and younger age. Those observed to have a negative association with prolonged opioid use are particular pharmacy ordering sites locations, preoperative morphine equivalents (no), longer deployment, race (American Indian or Alaskan native) and rank (junior enlisted).On internal validation, the models showed accuracy for predicting prolonged opioid use with AUC greater than our benchmark cutoff 0.70; random forest were 0.76 (95% confidence interval 0.73 to 0.79), 0.76 (95% CI 0.73 to 0.78), 0.73 (95% CI 0.71 to 0.76), and 0.72 (95% CI 0.69 to 0.75), respectively. Although the results from logistic regression and gradient boosting machines were very similar, only one model can be used in implementation. Based on our calculation of the Brier score, area under the curve, and decision curve analysis, we chose the gradient boosting machine as the final model. After selecting features and tuning the chosen gradient boosting machine, we saw an incremental improvement in our implementation model; the final model is accurate, with a Brier score of 0.10 (95% CI 0.09 to 0.11) and area under the curve of 0.77 (95% CI 0.75 to 0.80). It also shows the best clinical utility in a decision curve analysis.Conclusions: These scores support our claim that it is possible to predict which patients are at risk of prolonged opioid use, as seen by the appropriate range of hold-out analysis calculations. Current opioid guidelines recommend preoperative identification of at-risk patients, but available tools for this purpose are crude, largely focusing on identifying the presence (but not relative contributions) of various risk factors and screening for depression. The power of this model is that it will permit the development of a true clinical decision-support tool, which risk-stratifies individual patients with a single numerical score that is easily understandable to both patient and surgeon. Probabilistic models provide insight into how clinical factors are conditionally related. Not only will this gradient boosting machine be used to help understand factors contributing to opiate misuse after ACL reconstruction, but also it will allow orthopaedic surgeons to identify at-risk patients before surgery and offer increased support and monitoring to prevent opioid abuse and dependency.Level Of Evidence: Level III, therapeutic study. [ABSTRACT FROM AUTHOR]

Background: PATHFx is a clinical decision-support tool based on machine learning capable of estimating the likelihood of survival after surgery for patients with skeletal metastases. The applicability of any machine-learning tool depends not only on successful external validation in unique patient populations but also on remaining relevant as more effective systemic treatments are introduced. With advancements in the treatment of metastatic disease, it is our responsibility to patients to ensure clinical support tools remain contemporary and accurate.Question/purposes: Therefore, we sought to (1) generate updated PATHFx models using recent data from patients treated at one large, urban tertiary referral center and (2) externally validate the models using two contemporary patient populations treated either surgically or nonsurgically with external-beam radiotherapy alone for symptomatic skeletal metastases for symptomatic lesions.Methods: After obtaining institutional review board approval, we collected data on 208 patients undergoing surgical treatment for pathologic fractures at Memorial Sloan Kettering Cancer Center between 2015 and 2018. These data were combined with the original PATHFx training set (n = 189) to create the final training set (n = 397). We then created six Bayesian belief networks designed to estimate the likelihood of 1-month, 3-month, 6-month, 12-month, 18-month, and 24-month survival after treatment. Bayesian belief analysis is a statistical method that allows data-driven learning to arise from conditional probabilities by exploring relationships between variables to estimate the likelihood of an outcome using observed data. For external validation, we extracted the records of patients treated between 2016 and 2018 from the International Bone Metastasis Registry and records of patients treated nonoperatively with external-beam radiation therapy for symptomatic skeletal metastases from 2012 to 2016 using the Military Health System Data Repository (radiotherapy-only group). From each record, we collected the date of treatment, laboratory values at the time of treatment initiation, demographic data, details of diagnosis, and the date of death. All records reported sufficient follow-up to establish survival (yes/no) at 24-months after treatment. For external validation, we applied the data from each record to the new PATHFx models. We assessed calibration (calibration plots), accuracy (Brier score), discriminatory ability (area under the receiver operating characteristic curve [AUC]).Results: The updated PATHFx version 3.0 models successfully classified survival at each time interval in both external validation sets and demonstrated appropriate discriminatory ability and model calibration. The Bayesian models were reasonably calibrated to the Memorial Sloan Kettering Cancer Center training set. External validation with 197 records from the International Bone Metastasis Registry and 192 records from the Military Health System Data Repository for analysis found Brier scores that were all less than 0.20, with upper bounds of the 95% confidence intervals all less than 0.25, both for the radiotherapy-only and International Bone Metastasis Registry groups. Additionally, AUC estimates were all greater than 0.70, with lower bounds of the 95% CI all greater than 0.68, except for the 1-month radiotherapy-only group. To complete external validation, decision curve analysis demonstrated clinical utility. This means it was better to use the PATHFx models when compared to the default assumption that all or no patients would survive at all time periods except for the 1-month models. We believe the favorable Brier scores (< 0.20) as well as DCA indicate these models are suitable for clinical use.Conclusions: We successfully updated PATHFx using contemporary data from patients undergoing either surgical or nonsurgical treatment for symptomatic skeletal metastases. These models have been incorporated for clinical use on PATHFx version 3.0 (https://www.pathfx.org). Clinically, external validation suggests it is better to use PATHFx version 3.0 for all time periods except when deciding whether to give radiotherapy to patients with the life expectancy of less than 1 month. This is partly because most patients survived 1-month after treatment. With the advancement of medical technology in treatment and diagnosis for patients with metastatic bone disease, part of our fiduciary responsibility is to the main current clinical support tools.Level Of Evidence: Level III, therapeutic study. [ABSTRACT FROM AUTHOR]

Background: Quantifying bone mineral density (BMD) on CT using commercial software demonstrates good-to-excellent correlations with dual-energy x-ray absorptiometry (DEXA) results. However, previous techniques to measure Hounsfield units (HUs) within the proximal femur demonstrate less successful correlation with DEXA results. An effective method of measuring HUs of the proximal femur from CT colonoscopy might allow for opportunistic osteoporosis screening.Questions/purposes: (1) Do proximal femur HU measurements from CT colonoscopy correlate with proximal femur DEXA results? (2) How effective is our single HU measurement technique in estimating the likelihood of overall low BMD? (3) Does the relationship between our comprehensive HU measurement and DEXA results change based on age, sex, or time between studies?Methods: This retrospective study investigated the measurement of HU of the femur obtained on CT colonoscopy studies compared with DEXA results. Between 2010 and 2017, five centers performed 9085 CT colonoscopy studies; of those, 277 (3%) also had available DEXA results and were included in this study, whereas 8809 (97%) were excluded for inadequate CT imaging, lack of DEXA screening, or lack of proximal femur DEXA results. The median number of days between CT colonoscopy and DEXA scan was 595 days; no patient was excluded based on time between scans because bone remodeling is a long-term process and this allowed subgroup analysis based on time between scans. Two reviewers performed HU measurements at four points within the proximal femur on the CT colonoscopy imaging and intraclass correlation coefficients were used to evaluate interrater reliability. We used Pearson correlation coefficients to compare the comprehensive (average of eight measurements) and a single HU measurement with each DEXA result-proximal femur BMD, proximal femur T-score, femoral neck BMD, and femoral neck T-score-to identify the best measurement technique within this study. Based on their lowest DEXA T-score, we stratified patients to a diagnosis of osteoporosis, osteopenia, or normal BMD. We then calculated the area under the receiver operator characteristic curves (AUCs) to evaluate the classification ability of a single HU value to identify possible threshold(s) for detecting low BMD. For each subgroup analysis, we calculated Pearson correlation coefficients between DEXA and HUs and evaluated each subgroup's contribution to the overall predictive model using an interaction test in a linear regression model.Results: The Pearson correlation coefficient between both the comprehensive and single HU measurements was highest compared with the proximal femur T-score at 0.75 (95% confidence interval [CI], 0.69-0.80) and 0.74 (95% CI, 0.68-0.79), respectively. Interobserver reliability, measured with intraclass correlation coefficients, for the comprehensive and single HU measurements was 0.97 (95% CI, 0.72-0.99) and 0.96 (95% CI, 0.89-0.98), respectively. Based on DEXA results, 20 patients were osteoporotic, 167 had osteopenia, and 90 patients had normal BMD. The mean comprehensive HU for patients with osteoporosis was 70 ± 30 HUs; for patients with osteopenia, it was 110 ± 36 HUs; and for patients with normal BMD, it was 158 ± 43 HUs (p < 0.001). The AUC of the single HU model was 0.82 (95% CI, 0.77-0.87). A threshold of 214 HUs is 100% sensitive and 59 HUs is 100% specific to identify low BMD; a threshold of 113 HUs provided 73% sensitivity and 76% specificity. When stratified by decade age groups, each decade age group demonstrated a positive correlation between the comprehensive HU and proximal femur T-score, ranging between 0.71 and 0.83 (95% CI, 0.59-0.91). Further subgroup analysis similarly demonstrated a positive correlation between the comprehensive HU and proximal femur T-score when stratified by > 6 months or < 6 months between CT and DEXA (0.75; 95% CI, 0.62-0.84) as well as when stratified by sex (0.70-0.76; 95% CI, 0.48-0.81). The linear regression model demonstrated that the overall positive correlation coefficient between HUs and the proximal femur T-score is not influenced by any subgroup.Conclusions: Our measurement technique provides a reproducible measurement of HUs within the proximal femur HUs on CT colonoscopy. Hounsfield units of the proximal femur based on this technique can predict low BMD. These CT scans are frequently performed before initial DEXA scans are done and therefore may lead to earlier recognition of low BMD. Future research is needed to validate these results in larger studies and to determine if these results can anticipate future fracture risk.Level Of Evidence: Level III, diagnostic study. [ABSTRACT FROM AUTHOR]

Background: Amputations sustained owing to combat-related blast injuries are at high risk for deep infection and development of heterotopic ossification, which can necessitate reoperation and place immense strain on the patient. Surgeons at our institution began use of intrawound antibiotic powder at the time of closure in an effort to decrease the rate of these surgical complications after initial and revision amputations, supported by compelling clinical evidence and animal models of blast injuries. Antibiotic powder may be useful in reducing the risk of these infections, but human studies on this topic thus far have been inconclusive.Purpose: We sought to determine whether administration of intrawound antibiotic powder at the time of closure would (1) decrease the risk of subsequent deep infections of major lower-extremity combat-related amputations, and (2) limit formation and decrease severity of heterotopic ossification common in the combat-related traumatic residual limb.Methods: Between 2009 and 2015, 252 major lower extremity initial and revision amputations were performed by a single surgeon. Revision cases were excluded if performed specifically to address deep infection, leaving 223 amputations (88.5%) for this retrospective analysis. We reviewed medical records to collect patient information, returns to the operating room for subsequent infection, and microbiologic culture results. We also reviewed radiographs taken at least 3 months after surgery to determine the presence and severity of heterotopic ossification using the Walter Reed classification system. We grouped cases according to whether limbs underwent initial or revision amputations, and whether the limbs had a history of a prior infection. Apart from the use of antibiotic powder and duration of followup, the groups did not differ in terms of age, mechanism of injury, or sex. We then calculated the absolute risk reduction for infection and heterotopic ossification and the number needed to treat to prevent an infection.Results: Overall, administration of antibiotic powder resulted in a 13% absolute risk reduction of deep infection (14 of 82 [17%] versus 42 of 141 [30%]; p = 0.03; 95% CI, 0.20%-24.72%). In revision amputation surgery, the absolute risk reduction of infection with antibiotic powder use was 16% overall (eight of 58 versus 17 of 57; 95% CI, 1.21%-30.86%), and 25% for previously infected limbs (eight of 46 versus 14 of 33; 95% CI, 4.93%-45.14%). The number needed to treat to prevent one additional deep infection in amputation surgery is eight in initial amputations, seven in revision amputations, and four for revision amputation surgery on previously infected limbs. With the numbers available, we observed no reduction in the risk of heterotopic ossification with antibiotic powder use, but severity was decreased in the treatment group in terms of the number of residual limbs with moderate or severe heterotopic ossification (three of 12 versus 19 of 34; p = 0.03).Conclusions: Our findings show that administration of intrawound antibiotic powder reduces deep infection in residual limbs of combat amputees, particularly in the setting of revision amputation surgery in apparently aseptic residual limbs at the time of the surgery. Furthermore, administration of antibiotic powder for amputations at time of initial closure decreases the severity of heterotopic ossification formation, providing a low-cost adjunct to decrease the risk of two complications common to amputation surgery.Level of Evidence Level III, therapeutic study. [ABSTRACT FROM AUTHOR]

Volume 479, Number 3 Reply to the Letter to the Editor 637 Letter to the Editor Copyright © 2020 by the Association of Bone and Joint Surgeons. Downloaded from http://journals.lww.com/clinorthop by BhDMf5ePHKbH4TTImqenVA+lpWIIBvonhQl60EtgtdlLYrLzSPu+hQedJnbNaXBf on 04/05/2021 Downloaded from http://journals.lww.com/clinorthop by BhDMf5ePHKbH4TTImqenVA+lpWIIBvonhQl60EtgtdlLYrLzSPu+hQedJnbNaXBf on 04/05/2021 Clin Orthop Relat Res (2021) 479:636-638 DOI 10.1097/CORR.0000000000001632 Letter to the Editor Published online: 4 January 2021 Copyright © 2020 by the Association of Bone and Joint Surgeons Reply to the Letter to the Editor: Can Predictive Modeling Tools Identify Patients at High Risk of Prolonged Opioid Use after ACL Reconstruction?. [Extracted from the article]

Post-traumatic heterotopic ossification (HO) is the formation of ectopic bone in non-osseous structures following injury. The precise mechanism for bone development following trauma is unknown; however, early onset of HO may involve the production of pro-osteogenic serum factors. Here we evaluated serum from a cohort of civilian and military patients post trauma to determine early induction gene signatures in orthopaedic trauma induced HO. To test this, human adipose derived stromal/stem cells (hASCs) were stimulated with human serum from patients who developed HO following trauma and evaluated for a gene panel with qPCR. Pathway gene analysis ontology revealed that hASCs stimulated with serum from patients who developed HO had altered gene expression in the activator protein 1 (AP1) and AP1 transcriptional targets pathways. Notably, there was a significant repression in FOS gene expression in hASCs treated with serum from individuals with HO. Furthermore, the mitogen-activated protein kinase (MAPK) signaling pathway was activated in hASCs following serum exposure from individuals with HO. Serum from both military and civilian patients with trauma induced HO had elevated downstream genes associated with the MAPK pathways. Stimulation of hASCs with known regulators of osteogenesis (BMP2, IL6, Forskolin, and WNT3A) failed to recapitulate the gene signature observed in hASCs following serum stimulation, suggesting non-canonical mechanisms for gene regulation in trauma induced HO. These findings provide new insight for the development of HO and support ongoing work linking the systemic response to injury with wound specific outcomes. [ABSTRACT FROM AUTHOR]

ABSTRACT: Heterotopic ossification (HO) develops in the extremities of wounded service members and is common in the setting of high‐energy penetrating injuries and blast‐related amputations. No safe and effective prophylaxis modality has been identified for this patient population. Palovarotene has been shown to reduce bone formation in traumatic and genetic models of HO. The purpose of this study was to determine the effects of Palovarotene on inflammation, progenitor cell proliferation, and gene expression following a blast‐related amputation in a rodent model (n = 72 animals), as well as the ability of Raman spectroscopy to detect early HO before radiographic changes are present. Treatment with Palovarotene was found to dampen the systemic inflammatory response including the cytokines IL‐6 (p = 0.01), TNF‐α (p = 0.001), and IFN‐γ (p = 0.03) as well as the local inflammatory response via a 76% reduction in the cellular infiltration at post‐operative day (POD)‐7 (p = 0.03). Palovarotene decreased osteogenic connective tissue progenitor (CTP‐O) colonies by as much as 98% both in vitro (p = 0.04) and in vivo (p = 0.01). Palovarotene treated animals exhibited significantly decreased expression of osteo‐ and chondrogenic genes by POD‐7, including BMP4 (p = 0.02). Finally, Raman spectroscopy was able to detect differences between the two groups by POD‐1 (p < 0.001). These results indicate that Palovarotene inhibits traumatic HO formation through multiple inter‐related mechanisms including anti‐inflammatory, anti‐proliferative, and gene expression modulation. Further, that Raman spectroscopy is able to detect markers of early HO formation before it becomes radiographically evident, which could facilitate earlier diagnosis and treatment. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:1135–1144, 2018. [ABSTRACT FROM AUTHOR]

Heterotopic ossification, the formation of bone in soft tissues, is a common complication of the high-energy extremity trauma sustained in modern armed conflict. In the past 15 years, military treatment facilities and aligned laboratories have been in a unique position to study and treat this process due to the high volume of patients with these injuries secondary to blast trauma. The devastating nature of these wounds has limited traditional therapeutic options, necessitating alternative solutions to prophylaxis and initial treatment producing substantial advances in modeling, prophylaxis, detection, and therapy. Specific developments include establishment of an animal model that reproduces the systemic and local tissue injury of blast injuries, the use of molecular assays and predictive modeling in clinical decision making, advances in early detection including Raman spectroscopy, and investigation of prophylactic and therapeutic pharmacotherapy targeting the molecular pathways of aberrant bone formation. In this review article, we will present the literature to date, ongoing studies, and future directions for investigation of heterotopic ossification, with a focus on military-specific research. [ABSTRACT FROM AUTHOR]

ABSTRACT Heterotopic ossification (HO) is a debilitating sequela of high-energy injuries. It frequently requires surgical excision once symptomatic and there is no practical prophylaxis for combat-injured patients. In this study, we examined the effect of local vancomycin powder on HO formation in a small animal model of blast-related, post-traumatic HO. Male Sprague-Dawley rats were subjected to a polytraumatic extremity injury and amputation with or without methicillin-resistant Staphylococcus aureus infection. Animals were randomized to receive a single local application of vancomycin (20 mg/kg) at the time of injury (POD-0, n = 34) or on postoperative day-3 (POD-3, n = 11). Quantitative volumetric measurement of ectopic bone was calculated at 12-weeks post-injury by micro-CT. Bone marrow and muscle tissues were also collected to determine the bacterial burden. Blood for serum cytokine analysis was collected at baseline and post-injury. Vancomycin treatment on POD-0 suppressed HO formation by 86% and prevented bone marrow and soft tissue infections. We concurrently observed a marked reduction histologically in nonviable tissue, chronic inflammatory cell infiltrates, bone infection, fibrous tissue, and areas of bone necrosis within this same cohort. Delayed treatment was significantly less efficacious. Neither treatment had a marked effect on the production of pro-inflammatory cytokines. Our study demonstrates that local vancomycin treatment at the time of injury significantly reduces HO formation in both the presence and absence of infection, with decreased efficacy if not given early. These findings further support the concept that the therapeutic window for prophylaxis is narrow, highlighting the need to develop early treatment strategies for clinical management. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:2397-2406, 2017. [ABSTRACT FROM AUTHOR]