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We lack knowledge about prognostic factors of resective epilepsy surgery (RES) in older adults (≥60 years), especially the role of comorbidities, which are a major consideration in managing the care of people with epilepsy (PWE). We analyzed a single‐center cohort of 94 older adults (median age = 63.5 years, 52% females) who underwent RES between 2000 and 2021 with at least 6 months of postsurgical follow‐up. Three fourths of the study cohort had lesional magnetic resonance imaging and underwent temporal lobectomy. Fifty‐four (57%) PWE remained seizure‐free during a median follow‐up of 3.5 years. Cox proportional hazard multivariable analysis showed that aura (hazard ratio [HR] = .52, 95% confidence interval [CI] = .27–1.00), single ictal electroencephalographic pattern (HR = .33, 95% CI = .17–.660), and Elixhauser Comorbidity Index (HR = 1.05, 95% CI = 1.00–1.10) were independently associated with seizure recurrence at last follow‐up. A sensitivity analysis using the Charlson Combined Score (HR = 1.38, 95% CI = 1.03–1.84, p = .027) confirmed the association of comorbidities with worse seizure outcome. Our findings provide a framework for a better informed discussion about RES prognosis in older adults. More extensive, multicenter cohort studies are needed to validate our findings and reduce hesitancy in pursuing RES in suitable older adults. [ABSTRACT FROM AUTHOR]

Objective: This investigation examines burden of comorbidity measured by the Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Index (ECI) among inpatients based on age, sex, and race. Methods: Cross-sectional analysis of 2012-2018 US NIS datasets. Participants were inpatients 55y+. ICD-9/10 codes for admitting diagnoses were used to calculate disease burden using the CCI and ECI. Unweighted mean CCI and ECI scores were compared across demographic variables. Results: An increase in mean CCI and ECI scores across age, sex, and races (p<.001) was identified. Compared to the youngest age group (55-59y), all age groups had higher mean CCI and ECI adjusting for time (p<.001). Increases were greatest in older age groups until age 80-84 for CCI and 85-89 for ECI. The female group had lower CCI adjusting for time (p<.001) compared to males. There was no difference between sex groups in mean ECI (p=.409). Compared with the White group, all other race groups had higher mean CCI adjusting for time (p<.001). Black inpatients had the highest CCI followed by Native American inpatients. Findings were similar for ECI, but with no difference between Hispanic and White groups (p=.434). Conclusions: Growing multimorbidity burden among adult inpatients across age, sex, and race supports the continued need for programs for preventing and reducing multimorbidity, especially among communities that experience health inequity including older, Black, and Native American patients. [ABSTRACT FROM AUTHOR]

Aim: This study was designed to investigate the association between Charlson Comorbidity Index (CCI) and in‐hospital mortality and other clinical outcomes among patients with hyperglycemic crises. Method: This retrospective cohort study was conducted using data from electric medical records. A total of 1668 diabetic patients with hyperglycemic crises from six tertiary hospitals met the inclusion criteria. CCI < 4 was defined as low CCI and CCI ≥ 4 was defined as high CCI. Propensity score matching (PSM) with the 1:1 nearest neighbour matching method and the caliper value of 0.02 was used to match the baseline characteristics of patients with high CCI and low CCI to reduce the confounding bias. In‐hospital mortality, ICU admission, hypoglycemia, hypokalemia, acute kidney injury, length of stay (LOS), and hospitalisation expense between low CCI and high CCI were compared and assessed. Univariate and multivariate regression were applied to estimate the impact of CCI on in‐hospital and other clinical outcomes. Outcome: One hundred twenty‐one hyperglycemic crisis (HC) patients died with a mortality rate of 7.3%. After PSM, compared with low CCI, patients with high CCI suffered higher in‐hospital mortality, ICU admission, LOS, and hospitalisation expenses. After multivariate regression, age (aOR: 1.12, 95% confidence interval [CI]: 1.06−1.18, p < 0.001), CCI(aOR: 4.42, 95% CI: 1.56−12.53, p = 0.005), uninsured (aOR: 22.32, 95% CI: 4.26−116.94, p < 0.001), shock (aOR: 10.57, 95% CI: 1.41−79.09, p = 0.022), mechanical ventilation (aOR: 75.29, 95% CI: 12.37−458.28, p < 0.001), and hypertension (aOR: 4.34, 95% CI: 1.37−13.82, p = 0.013) were independent risk factors of in‐hospital mortality of HC patients. Besides, high CCI was an independent risk factor for higher ICU Admission (aOR: 5.91, 95% CI: 2.31−15.08, p < 0.001), hypoglycemia (aOR: 2.19, 95% CI:1.01−4.08, p = 0.049), longer LOS (aOR: 1.23, 95% CI: 1.19−2.27, p = 0.021), and higher hospitalisation expense (aOR: 2089.97, 95% CI: 193.33−3988.61, p = 0.031) of HC patients. Conclusion: CCI is associated with in‐hospital mortality, ICU admission, hypoglycemia, LOS, and hospitalisation expense of HC patients. CCI could be an ideal indicator to identify, monitor, and manage chronic comorbidities among HC patients. [ABSTRACT FROM AUTHOR]

Objective: Femoral neck fractures (FNF) are known to have significant morbidity and mortality rates. Multiple chronic conditions (MCC) are defined as the presence of two or more chronic diseases that greatly affect the quality of life in older adults. The aim of this study is to explore the impact of MCC and Charlson comorbidity index (CCI) on surgical outcomes in patients with FNF. Methods: Patients with FNF who underwent joint replacement surgery were selected for this study. Patients who had two or more diseases simultaneously were divided into two groups: the MCC group and the non-MCC (NMCC) group. The CCI was calculated to assess the severity of patients' comorbidities in the MCC group. Baseline data, surgical details, and prognosis-related indicators were analyzed and compared between the two patient groups. Spearman correlation analysis was performed to assess the relationship between CCI and length of hospital stay, Harris score, skeletal muscle index (SMI), and age. Univariate and multivariate logistic regression analysis was conducted to identify the risk factors for mortality in FNF patients at 1 and 5 years after surgery. Results: A total of 103 patients were included in the MCC group, while the NMCC group consisted of 40 patients. However, the patients in the MCC group were found to be older, had a higher incidence of sarcopenia, and lower SMI values (p < 0.001). Patients in the MCC group had longer hospitalization times, lower Harris scores, higher intensive care unit (ICU) admission rates, and higher complication rates (p = 0.045, p = 0.035, p = 0.019, p = 0.010). Spearman correlation analysis revealed that CCI was positively correlated with hospitalization and age (p < 0.001, p < 0.001), while it was negatively correlated with Harris score and SMI value (p < 0.001, p < 0.001). Univariate and multivariate logistic regression analysis demonstrated that MCC patients had higher 1-year and 5-year mortality rates. Hospitalization time was identified as a risk factor for death in FNF patients 1 year after joint replacement (p < 0.001), whereas CCI and age were identified as risk factors for death 5 years after surgery (p < 0.001, p < 0.001). Kaplan-Meier survival analysis results showed that the difference in death time between the two groups of patients with MCC and NMCC was statistically significant (p < 0.001). Cox proportional hazard model analysis showed that CCI, age and SMI were risk factors affecting patient death. Conclusion: The surgical prognosis of patients with MCC, CCI and FNF is related. The higher the CCI, the worse the patient's function and the higher the long-term risk of death. [ABSTRACT FROM AUTHOR]

Care for patients with cancer is more challenging when they have concurrent, complex comorbidities. Risk assessment tools may help to enhance care assessment and predict poor clinical outcomes for these patients. This article provides information for the nurse caring for patients with cancer who have common comorbidities throughout the care continuum. [ABSTRACT FROM AUTHOR]

Short-term outcomes of pulmonary embolism are closely related to right ventricular dysfunction and patient's hemodynamic status, but also to individual comorbidity profile. However, the impact of patients' comorbidities on survival during pulmonary embolism might be underrated. Although the Charlson Comorbidity Index (CCI) is the most extensively studied comorbidity index for detecting comorbidity burden, studies analyzing the impact of CCI on pulmonary embolism patients' survival are limited. We used the German nationwide inpatient sample to analyze all hospitalized patients with pulmonary embolism in Germany 2005-2020 and calculated CCI for each patient, compared the CCI classes (very low: CCI = 0 points, mild: CCI = 1-2 points, moderate: CCI = 3-4, high severity: CCI >4 points) and impact of CCI class on outcomes. Overall, 1,373,145 hospitalizations of patients with acute pulmonary embolism (53.0% females, 55.9% aged ≥70 years) were recorded in Germany between 2005 and 2020; the CCI class stratified them. Among these, 100,156 (7.3%) were categorized as very low; 221,545 (16.1%) as mild; 394,965 (28.8%) as moderate; and 656,479 (47.8%) as patients with a high comorbidity burden according to CCI class. In-hospital case fatality increased depending on the CCI class: 3.6% in very low, 6.5% in mild, 12.1% in moderate, and 22.1% in high CCI class (P <.001). CCI class was associated with increased in-hospital case fatality (odds ratio 2.014; 95% confidence interval, 2.000-2.027; P <.001). Our study results may help practitioners to better understand and measure the association between an aggravated comorbidity profile and increased in-hospital case fatality in patients with pulmonary embolism. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to determine the impact of mortality and morbidity indices on the diagnosis and prognosis of patients suffering from necrotizing fasciitis. Methods: A retrospective analysis was performed on 41 patients (26 females, 15 males) with necrotizing fasciitis (NF). The SII (Systemic Immune-Inflammation Index) was computed using the formula SII = (P × N)/L, where P, N, and L measure the counts of peripheral platelets, neutrophils, and lymphocytes, respectively. This study evaluated the clinicopathological characteristics and follow-up information to assess the comparative effectiveness of SII, CCI (Charlson Comorbidity Index), and LRINEC (Laboratory Risk Indicator for Necrotizing Fasciitis) scores as mortality and morbidity indices for patients with NF. Results: The optimal cut-off for SII was determined to be 455. The SII value in the group with mortality was significantly higher compared to the group without mortality (p < 0.05). The CCI value in the group with mortality was significantly higher than the group without mortality (p < 0.05). The SII and CCI values were found to be effective in distinguishing between patients who suffered mortality and those who did not. Conclusion: SII is a powerful tool for predicting mortality in patients with necrotizing fasciitis (NF). The SII index provides a novel, easily accessible, and inexpensive indicator for monitoring the progress and predicting the survival of patients with NF. [ABSTRACT FROM AUTHOR]

Radical cystectomy (RC) remains a mainstay surgical treatment for non-metastatic muscle-invasive and BCG-unresponsive bladder cancer. Various perioperative scoring tools assess comorbidity burden, complication risks, and cancer-specific mortality (CSM) risk. We investigated the prognostic value of these scores in patients who underwent RC between 2015 and 2021. Cox proportional hazards were used in survival analyses. Risk models' accuracy was assessed with the concordance index (C-index) and area under the curve. Among 215 included RC patients, 63 (29.3%) died, including 53 (24.7%) cancer-specific deaths, with a median follow-up of 39 months. The AJCC system, COBRA score, and Charlson comorbidity index (CCI) predicted CSM with low accuracy (C-index: 0.66, 0.65; 0.59, respectively). Multivariable Cox regression identified the AJCC system and CCI > 5 as significant CSM predictors. Additional factors included the extent of lymph node dissection, histology, smoking, presence of concomitant CIS, and neutrophil-to-lymphocyte ratio, and model accuracy was high (C-index: 0.80). The internal validation of the model with bootstrap samples revealed its slight optimism of 0.06. In conclusion, the accuracy of the AJCC staging system in the prediction of CSM is low and can be improved with the inclusion of other pathological data, CCI, smoking history and inflammatory indices. [ABSTRACT FROM AUTHOR]

Chronic obstructive pulmonary disease (COPD) patients are particularly susceptible to respiratory infections like influenza, which exacerbate symptoms and increase healthcare utilization. While smoking cessation and influenza vaccination are recommended preventive measures, their combined impact on healthcare resource utilization is underexplored. The Charlson Comorbidity Index (CCI) assesses comorbidity burden in COPD patients and may influence healthcare outcomes. We conducted a retrospective analysis of 357 COPD patients, evaluating smoking cessation success over one year and influenza vaccination receipt, stratifying patients by CCI scores. Healthcare utilization outcomes included emergency room visits, hospitalizations, and medical expenses. Results showed that 51.82% of patients quit smoking and 59.66% received influenza vaccination, with higher comorbidity prevalence in advanced COPD stages (p = 0.002). Both smoking cessation and influenza vaccination independently correlated with decreased emergency room visits, hospital admissions, days, and costs. Patients who both quit smoking and received influenza vaccination exhibited the lowest healthcare utilization rates. In conclusion, smoking cessation and influenza vaccination significantly reduce healthcare resource utilization in COPD patients, with the combination yielding synergistic benefits, particularly in those with lower CCI scores. Integrating these interventions and comorbidity management in COPD strategies is essential for optimizing patient outcomes and healthcare efficiency. [ABSTRACT FROM AUTHOR]

Abstract Objective Femoral neck fractures (FNF) are known to have significant morbidity and mortality rates. Multiple chronic conditions (MCC) are defined as the presence of two or more chronic diseases that greatly affect the quality of life in older adults. The aim of this study is to explore the impact of MCC and Charlson comorbidity index (CCI) on surgical outcomes in patients with FNF. Methods Patients with FNF who underwent joint replacement surgery were selected for this study. Patients who had two or more diseases simultaneously were divided into two groups: the MCC group and the non-MCC (NMCC) group. The CCI was calculated to assess the severity of patients’ comorbidities in the MCC group. Baseline data, surgical details, and prognosis-related indicators were analyzed and compared between the two patient groups. Spearman correlation analysis was performed to assess the relationship between CCI and length of hospital stay, Harris score, skeletal muscle index (SMI), and age. Univariate and multivariate logistic regression analysis was conducted to identify the risk factors for mortality in FNF patients at 1 and 5 years after surgery. Results A total of 103 patients were included in the MCC group, while the NMCC group consisted of 40 patients. However, the patients in the MCC group were found to be older, had a higher incidence of sarcopenia, and lower SMI values (p

Relevance. To investigate the prognostic value of the Charlson Comorbidity Index (CCI) and its components in assessing outcomes related to in-hospital and 18‑month mortality and to determine additional prognostic value when incorporating them into the GRACE score among patients with acute myocardial infarction (MI). Material and methods. A prospective study enrolled 712 patients diagnosed with acute MI who underwent coronary angiography within 24 hours of hospitalization. Results and Discussion. Of the patients, 61 % were male, median age 65 (interquartile range [IQR] 56–74years). In-hospital and 18‑month mortality rates were 5.1 % (n = 36) and 12.1 % (n = 86), respectively. Median GRACE, CCI scores were 117 (IQR: 98–141), and 4 (IQR: 3–6) respectively. Common comorbidities within the CCI components included previous MI (21.8 %), diabetes mellitus (21.1 %), chronic pulmonary disease (16.2 %), dementia (9.2 %), peptic ulcer disease (9.1 %), renal failure (8.6 %). Factors associated with in-hospital and 18‑month mortality included chronic lung disease (odds ratio [OR] = 4.21 and 2.04, respectively) and renal failure (OR = 3.51 and 1.99, respectively) after adjusting for GRACE score. Dementia (OR 2.10; 95 % confidence interval [CI] 1.11–3.97) was a significant risk factor for 18‑month mortality. CCI was associated with in-hospital and 18‑month mortality (GRACE-adjusted OR 1.29, 95 % CI:1.07–1.57, p = 0.001 and 1.37, 95 % CI (1.20–1.57, p = 0.001, respectively). CCI demonstrated good predictive ability for in-hospital mortality (area under the ROC Curve [AUC]: 0.826) and modest performance for 18‑month mortality (AUC: 0.797). Adding chronic lung disease, renal failure in the GRACE score significantly improved the predictive efficacy for in-hospital mortality, with an AUC of 0.932 (95 % CI: 0.905–0.959, p = 0.001). Including CCI in the GRACE score enhanced the prediction efficiency for 18‑month mortality (AUC 0.819, 95 % CI: 0.768–0.871, p = 0.001). Conclusion. The CCI demonstrated moderate prognostic value in assessing in-hospital mortality among patients with acute MI and good predictive ability for long-term mortality. The CCI and its components (chronic lung disease, renal failure) added prognostic significance in addition to the GRACE score for predicting both short-term and long-term adverse outcomes.

Abstract Background Machine learning (ML) can be promising for stratifying patients into homogeneous groups and assessing mortality based on score combination. Using ML, we compared mortality prediction performance for clustered and non-clustered models and tried to develop a simple decision algorithm to predict the patient’s cluster membership with classification and regression trees (CART). Methods Retrospective study involving patients requiring ICU admission (1st January 2011–16th September 2022). Clusters were identified by combining Charlson Comorbidity Index (CCI) plus Simplified Acute Physiology Score II (SAPS II) or Sequential Organ Failure Assessment (SOFA). Intercluster and survival analyses were performed. We analyzed the relationship with mortality with multivariate logistic regressions and receiver operating characteristic curves (ROC) for models with and without clusters. Nested models were compared with Likelihood Ratio Tests (LRT). Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) were compared for non-nested models. With the best model, we used CART to build a decision tree for patient’s membership. Results Our sample consisted of 2605 patients (mortality 59.7%). For both score combinations, we identified two clusters (A and B for CCI + SAPS II, α and β for CCI + SOFA). Belonging to cluster B/β was associated with shorter survival times (Peto-Peto p-values

Sarcopenia in Elderly Patients: What are the Contributing Risk Factors?. Sarcopenia is the gradual loss of muscle mass associated with aging. The process by which sarcopenia occurs is not fully understood. Many factors are at risk of causing sarcopenia, such as age, gender, and physical activity. Early detection with the SARC-F questionnaire is needed to prevent sarcopenia. This study is a descriptive observational study with a cross-sectional approach with total sampling to see the description of sarcopenia and risk factors in elderly patients at the Geriatric Polyclinic of Dr. Mohammad Hoesin Hospital Palembang. Primary data were collected through interviews using a questionnaire, and then analyzed univariately. A total of 48.4% of the elderly at the Geriatric Polyclinic of Dr. Mohammad Hoesin Hospital Palembang had sarcopenia findings. Patients in the sarcopenia group were mostly aged 70-79 years (41.9%), female (64.5%), married (58.1%), history of primary education (32.3%), had worked (58.1%), had mild comorbidities (58.1%), sedentary physical activity (74.2%), and at risk of malnutrition (54.8%).

Many patients with idiopathic normal pressure hydrocephalus (iNPH) have medical comorbidities requiring anticoagulation that could negatively impact outcomes. This study evaluated the safety of ventriculoperitoneal shunt placement in iNPH patients on systemic anticoagulation versus those not on anticoagulation. Patients >60 years of age with iNPH who underwent shunting between 2018 and 2022 were retrospectively reviewed. Baseline demographics, comorbidities (quantified by modified frailty index and Charlson comorbidity index), anticoagulant/antiplatelet agent use (other than aspirin), operative details, and complications were collected. Outcomes of interest were the occurrence of postoperative hemorrhage and overdrainage. A total of 234 patients were included in the study (mean age 75.22 ± 6.04 years; 66.7% male); 36 were on anticoagulation/antiplatelet therapy (excluding aspirin). This included 6 on Warfarin, 19 on direct Xa inhibitors, 10 on Clopidogrel, and 1 on both Clopidogrel and Warfarin. Notably, 70% of patients (164/234) used aspirin alone or combined with anticoagulation or clopidogrel. Baseline modified frailty index was similar between groups, but those on anticoagulant/antiplatelet therapy had a higher mean Charlson comorbidity index (2.67 ± 1.87 vs. 1.75 ± 1.84; P = 0.001). Patients on anticoagulants were more likely to experience tract hemorrhage (11.1 vs. 2.5%; P = 0.03), with no significant difference in the rates of intraventricular hemorrhage or overdrainage-related subdural fluid collection. Anticoagulant and antiplatelet agents are common in the iNPH population, and patients on these agents experienced higher rates of tract hemorrhage following ventriculoperitoneal shunt placement; however, overall hemorrhagic complication rates were similar. [ABSTRACT FROM AUTHOR]

Background: Machine learning (ML) can be promising for stratifying patients into homogeneous groups and assessing mortality based on score combination. Using ML, we compared mortality prediction performance for clustered and non-clustered models and tried to develop a simple decision algorithm to predict the patient's cluster membership with classification and regression trees (CART). Methods: Retrospective study involving patients requiring ICU admission (1st January 2011–16th September 2022). Clusters were identified by combining Charlson Comorbidity Index (CCI) plus Simplified Acute Physiology Score II (SAPS II) or Sequential Organ Failure Assessment (SOFA). Intercluster and survival analyses were performed. We analyzed the relationship with mortality with multivariate logistic regressions and receiver operating characteristic curves (ROC) for models with and without clusters. Nested models were compared with Likelihood Ratio Tests (LRT). Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) were compared for non-nested models. With the best model, we used CART to build a decision tree for patient's membership. Results: Our sample consisted of 2605 patients (mortality 59.7%). For both score combinations, we identified two clusters (A and B for CCI + SAPS II, α and β for CCI + SOFA). Belonging to cluster B/β was associated with shorter survival times (Peto-Peto p-values < 0.0001) and increased mortality (Odds-ratio 4.65 and 5.44, respectively). According to LRT and ROC analysis, clustered models performed better, and CCI + SOFA showed the lowest AIC and BIC values (AIC = 3021.21, BIC = 3132.65). Using CART (β cluster positive case) the accuracy of the decision tree was 94.8%. Conclusion: Clustered models significantly improved mortality prediction. The CCI + SOFA clustered model showed the best balance between complexity and data fit and should be preferred. Developing a user-friendly decision-making algorithm for cluster membership with CART showed high accuracy. Further validation studies are needed to confirm these findings. [ABSTRACT FROM AUTHOR]

Follow-up (FU) strategies after endoscopic eradication therapy (EET) for Barrett's neoplasia do not consider the risk of mortality from causes other than esophageal adenocarcinoma (EAC). We aimed to evaluate this risk during long-term FU, and to assess whether the Charlson Comorbidity Index (CCI) can predict mortality. We included all patients with successful EET from the nationwide Barrett registry in the Netherlands. Data were merged with National Statistics for accurate mortality data. We evaluated annual mortality rates (AMRs, per 1000 person-years) and standardized mortality ratio for other-cause mortality. Performance of the CCI was evaluated by discrimination and calibration. We included 1154 patients with a mean age of 64 years (±9). During median 59 months (p25–p75 37–91; total 6375 person-years), 154 patients (13%) died from other causes than EAC (AMR, 24.1; 95% CI, 20.5–28.2), most commonly non-EAC cancers (n = 58), cardiovascular (n = 31), or pulmonary diseases (n = 26). Four patients died from recurrent EAC (AMR, 0.5; 95% CI, 0.1–1.4). Compared with the general Dutch population, mortality was significantly increased for patients in the lowest 3 age quartiles (ie, age <71 years). Validation of CCI in our population showed good discrimination (Concordance statistic, 0.78; 95% CI, 0.72–0.84) and fair calibration. The other-cause mortality risk after successful EET was more than 40 times higher (48; 95% CI, 15–99) than the risk of EAC-related mortality. Our findings reveal that younger post-EET patients exhibit a significantly reduced life expectancy when compared with the general population. Furthermore, they emphasize the strong predictive ability of CCI for long-term mortality after EET. This straightforward scoring system can inform decisions regarding personalized FU, including appropriate cessation timing. (NL7039) [Display omitted] After treatment for Barrett's neoplasia, the risk of dying from other causes than esophageal cancer is 40 times higher and predictable. This risk should therefore be considered in guidelines on follow-up after treatment. [ABSTRACT FROM AUTHOR]

Objectives This study aimed to support the implementation of the 11th Revision of the International Classification of Diseases (ICD-11). We used common comorbidity indices as a case study for proactively assessing the impact of transitioning to ICD-11 for mortality and morbidity statistics (ICD-11-MMS) on real-world data analyses. Materials and Methods Using the MIMIC IV database and a table of mappings between the clinical modification of previous versions of ICD and ICD-11-MMS, we assembled a population whose diagnosis can be represented in ICD-11-MMS. We assessed the impact of ICD version on cross-sectional analyses by comparing the populations' distribution of Charlson and Elixhauser comorbidity indices (CCI, ECI) across different ICD versions, along with the adjustment in comorbidity weighting. Results We found that ICD versioning could lead to (1) alterations in the population distribution and (2) changes in the weight that can be assigned to a comorbidity category in a reweighting initiative. In addition, this study allowed the creation of the corresponding ICD-11-MMS codes list for each component of the CCI and the ECI. Discussion In common with the implementations of previous versions of ICD, implementation of ICD-11-MMS potentially hinders comparability of comorbidity burden on health outcomes in research and clinical settings. Conclusion Further research is essential to enhance ICD-11-MMS usability, while mitigating, after identification, its adverse effects on comparability of analyses. [ABSTRACT FROM AUTHOR]

Background: This study investigates the risk factors associated with postoperative complications in musculoskeletal tumor surgeries and evaluates the impact of benchmarking in enhancing surgical outcomes. Methods: Conducted at a tertiary referral center, this retrospective analysis included 196 patients who underwent surgeries for various musculoskeletal tumors, ranging from soft tissue to bone sarcomas. Patient and tumor characteristics, along with surgical interventions and outcomes, were comprehensively assessed using the Charlson Comorbidity Index and the Clavien-Dindo classification. Results: Key findings indicate that surgical reconstruction, ASA 3 status, bone tumor presence, and the need for multiple erythrocyte transfusions significantly increase postoperative morbidity. Notably, no significant correlation was found between the Charlson Comorbidity Index scores and the occurrence or severity of complications, challenging the utility of this index in predicting short-term surgical outcomes. Conclusions: This study highlights the importance of tailored surgical approaches and emphasizes rigorous preoperative assessments to mitigate risks and enhance patient care. Despite its insights, limitations include its retrospective nature and single-center scope, suggesting a need for broader, multicenter studies to generalize findings. Overall, our results underscore the necessity of integrating clinical assessments with benchmarking data to optimize outcomes in the complex field of musculoskeletal tumor surgery. [ABSTRACT FROM AUTHOR]

Simple Summary: Surgery is the most effective treatment for early-stage lung cancer, but it poses a heavy physical burden. Accordingly, understanding the perioperative daily life conditions of patients is important to maintain their health status and to provide appropriate treatment. We performed a prospective study to examine the socioclinical factors associated with the physical quality of life of patients who underwent surgery for lung cancer at Shonan Kamakura General Hospital, Kanagawa, Japan. In the preoperative setting, living alone and lower performance status were independently associated with worse physical quality of life. In the postoperative setting at 6 months, later smoking cessation, lower performance status, living alone, and higher comorbid burden were independently associated with worse physical quality of life. In order to maintain quality of life and provide enough treatment, perioperative management should include taking care of the patient's physical condition, lifestyle, smoking, and comorbid status. Surgery is the most effective treatment for early-stage lung cancer; however, it poses a higher physical burden than other treatment options. Therefore, understanding the perioperative course of patients is important. Using the Short Form Health Survey 36, we prospectively measured the physical quality of life of patients who underwent anatomical pulmonary resection for non-small cell lung cancer at Shonan Kamakura General Hospital, Kanagawa, Japan (n = 87). In the preoperative setting, patients who had lower performance status and lived alone had significantly worse physical quality of life scores on multivariate analysis (regression coefficient (95% confidence interval), −9.37 (−13.43–−5.32) and −10.22 (−13.74–−7.40), respectively, p < 0.0001 for both). At 6 months postoperatively, patients who stopped smoking within 1 year preoperatively (stopped smoking within 1 year vs. remote or never smokers, 41.0 ± 10.5 vs. 48.6 ± 7.2, p = 0.002), had lower performance status (0 vs. 1–2, 49.3 ± 6.6 vs. 38.6 ± 9.6, p < 0.0001), lived alone (living alone vs. living with somebody, 41.6 ± 9.7 vs. 48.1 ± 7.9, p = 0.021), and had higher comorbid burden (Charlson comorbidity index <3 vs. ≥3, 48.2 ± 6.9 vs. 39.1 ± 14.7, p = 0.003) had significantly worse physical quality of life scores on univariate analysis. More recent smoking (regression coefficient (95% confidence interval), −4.90 (−8.78–1.0), p = 0.014), lower performance status (8.90 (5.10–12.70), p < 0.0001), living alone (5.76 (1.39–10.13), p = 0.01), and higher comorbid burden (−6.94 (−11.78–−2.10), p = 0.006) were significant independent predictors of worse postoperative physical quality of life on multivariate analysis. Therefore, patients with these conditions might need additional support to maintain their physical condition after anatomical lung cancer surgery. [ABSTRACT FROM AUTHOR]

Background: Vitamin‐D is essential for musculoskeletal health. We aimed to determine whether patients with fecal incontinence (FI): (1) are more likely to have vitamin‐D deficiency and, (2) have higher rates of comorbid medical conditions. Methods: We examined 18‐ to 90‐year‐old subjects who had 25‐hydroxy vitamin‐D levels, and no vitamin‐D supplementation within 3 months of testing, in a large, single‐institutional electronic health records dataset, between 2017 and 2022. Cox proportional hazards survival analysis was used to assess association of vitamin‐D deficiency on FI. Key Results: Of 100,111 unique individuals tested for serum 25‐hydroxy vitamin‐D, 1205 (1.2%) had an established diagnosis of FI. Most patients with FI were female (75.9% vs. 68.7%, p = 0.0255), Caucasian (66.3% vs. 52%, p = 0.0001), and older (64.2 vs. 53.8, p < 0.0001). Smoking (6.56% vs. 2.64%, p = 0.0001) and GI comorbidities, including constipation (44.9% vs. 9.17%, p = 0.0001), irritable bowel syndrome (20.91% vs. 3.72%, p = 0.0001), and diarrhea (28.55% vs. 5.2%, p = 0.0001) were more common among FI patients. Charlson Comorbidity Index score was significantly higher in patients with FI (5.5 vs. 2.7, p < 0.0001). Significantly higher proportions of patients with FI had vitamin‐D deficiency (7.14% vs. 4.45%, p < 0.0001). Moreover, after propensity‐score matching, rate of new FI diagnosis was higher in patients with vitamin‐D deficiency; HR 1.9 (95% CI [1.14–3.15]), p = 0.0131. Conclusion & Inferences: Patients with FI had higher rates of vitamin‐D deficiency along with increased overall morbidity. Future research is needed to determine whether increased rate of FI in patients with vitamin‐D deficiency is related to frailty associated with increased medical morbidities. [ABSTRACT FROM AUTHOR]

Comorbidity and health status indices aid in preoperative risk stratification with respect to postoperative morbidity. We performed a standardized complication assessment in 468 patients undergoing radical cystectomy for bladder cancer. We found that comorbidity and health status indices are unable to reliably predict 30-day postoperative complications. This emphasizes that procedure-specific comorbidity assessments could improve patient counseling regarding the actual risk of postoperative complications. Background: In the era of standardized outcome reporting, it remains unclear if widely used comorbidity and health status indices can enhance predictive accuracy for morbidity and long-term survival outcomes after radical cystectomy (RC). Patients and Methods: In this monocentric study, we included 468 patients undergoing open RC with pelvic lymph node dissection for bladder cancer between January 2009 and December 2017. Postoperative complications were meticulously assessed according to the EAU guideline criteria for standardized outcome reporting. Multivariable regression models were fitted to evaluate the ability of ASA physical status (ASA PS), Charlson comorbidity index (± age-adjustment) and the combination of both to improve prediction of (A) 30-day morbidity key estimates (major complications, readmission, and cumulative morbidity as measured by the Comprehensive Complication index [CCI]) and (B) secondary mortality endpoints (overall [OM], cancer-specific [CSM], and other-cause mortality [OCM]). Results: Overall, 465 (99%) and 52 (11%) patients experienced 30-day complications and major complications (Clavien-Dindo grade =IIIb), respectively. Thirty-seven (7.9%) were readmitted within 30 days after discharge. Comorbidity and health status indices did not improve the predictive accuracy for 30-day major complications and 30-day readmission of a reference model but were associated with 30-day CCI (all P < .05). When ASA PS and age-adjusted Charlson index were combined, ASA PS was no longer associated with 30-day CCI (P = .1). At a median follow-up of 56 months (IQR 37-86), OM, CSM, and 90-day mortality were 37%, 24%, and 2.9%, respectively. Both Charlson and age-adjusted Charlson index accurately predicted OCM (all P < .001) and OM (all P ≤ .002) but not CSM (all P ≥ .4) and 90-day mortality (all P > .05). ASA PS was not associated with oncologic outcomes (all P ≥ .05). Conclusion: While comorbidity and health status indices have a role in predicting OCM and OM after RC, their importance in predicting postoperative morbidity is limited. Especially ASA PS performed poorly. This highlights the need for procedure-specific comorbidity assessment rather than generic indices. [ABSTRACT FROM AUTHOR]

Abstract Background Multimorbidity is becoming an increasingly serious public health challenge in the aging population. The impact of nutrients on multimorbidity remains to be determined and was explored using data from a UK cohort study. Method Our research analysis is mainly based on the data collected by the United Kingdom Women’s Cohort Study (UKWCS), which recruited 35,372 women aged 35–69 years at baseline (1995 to 1998), aiming to explore potential associations between diet and chronic diseases. Daily intakes of energy and nutrients were estimated using a validated 217-item food frequency questionnaire at recruitment. Multimorbidity was assessed using the Charlson comorbidity index (CCI) through electronic linkages to Hospital Episode Statistics up to March 2019. Cox’s proportional hazards models were used to estimate associations between daily intakes of nutrients and risk of multimorbidity. Those associations were also analyzed in multinomial logistic regression as a sensitivity analysis. In addition, a stratified analysis was conducted with age 60 as the cutoff point. Results Among the 25,389 participants, 7,799 subjects (30.7%) were confirmed with multimorbidity over a median follow-up of 22 years. Compared with the lowest quintile, the highest quintile of daily intakes of energy and protein were associated with 8% and 12% increased risk of multimorbidity respectively (HR 1.08 (95% CI 1.01, 1.16), p-linearity = 0.022 for energy; 1.12 (1.04, 1.21), p-linearity = 0.003 for protein). Higher quintiles of daily intakes of vitamin C and iron had a slightly lowered risk of multimorbidity, compared to the lowest quintile. A significantly higher risk of multimorbidity was found to be linearly associated with higher intake quintiles of vitamin B12 and vitamin D (p-linearity = 0.001 and 0.002, respectively) in Cox models, which became insignificant in multinomial logistic regression. There was some evidence of effect modification by age in intakes of iron and vitamin B1 associated with the risk of multimorbidity (p-interaction = 0.006 and 0.025, respectively). Conclusions Our findings highlight a link between nutrient intake and multimorbidity risk. However, there is uncertainty in our results, and more research is needed before definite conclusions can be reached.

Introduction: Estimating intensive care admission of orthopedic patients is challenging because of patient variance and multiple comorbidities, primarily in geriatrics, and not yet standardized for the planned and qualified utility of hospital services. This study aimed to reveal the perioperative risk scores of orthopedic patients followed postoperatively in intensive care to investigate the efficacy of these scores in predicting intensive care admission and mortality. Methods: Patients transferred from the orthopedic ward to the intensive care unit (ICU) at any time during their postoperative follow-up from 2022 to 2023 were investigated. Primarily searched scores were the Surgical Apgar, Wells for pulmonary embolism, Charlson Comorbidity Index, ARISCAT for Postoperative Pulmonary Complications preoperatively, and Simplified Acute Physiology III, Sequential Organ Failure Assessment (SOFA), quick-SOFA, and Acute Physiology and Chronic Health Evaluation postoperatively. These scores were evaluated in relation to total intensive care and hospital stay with mortality. Results: The majority of the study population was found to be ASA-2 (45%). Ninety-eight percent of the patients were admitted to the ICU within three postoperative days, with the indication of planned postoperative follow-up mainly after proximal femoral nailing (24%). Among preoperative scores, wells had a significant positive correlation with ICU readmission and length of ICU stay (r=0.32, p=0.001). 62.7% of the patients had severe Charlson Comorbidity Risk Index. Up to postoperative scores, SAPS3 had a significant positive correlation with total ICU and hospital stay, with a significant difference in mortality (p=

Hospital readmission involves the unplanned emergency admission of patients within 30 days from discharge after the previous admission. According to the Canadian Health Institute (CIHI), 1 in 11 patients were readmitted within 30 days of leaving the hospital in 2021. In the USA, nearly 20% of Medicare patients were readmitted after discharge, where the average cost of readmission was approximately USD 15,000, as reported by the Agency for Healthcare Research and Quality (AHQR) in 2018. To tackle this issue, we first conducted a descriptive analysis study to understand the risk factors associated with hospital readmission, and then we applied machine learning approaches to predict hospital readmission by using patients’ demographic and clinical data extracted from the Electronic Health Record of the MIMIC-III clinical database. The results showed that the number of previous admissions during the last 12 months, hyperosmolar imbalance and comorbidity index were the top three significant factors for hospital readmission. The predictive model achieved a performance of 95.6% AP and an AUC = 97.3% using the Gradient Boosting algorithm trained on all features.

Introduction: Functional status is one of the surrogates of advanced age, an established risk factor for Clostridioides difficile infection (CDI). We aimed to investigate the usefulness of functional status in the clinical management of CDI. Methods: We enrolled all hospitalized adult patients receiving antibiotics from a retrospective hospital-based cohort in Japan between 2016 and 2020. Using the Barthel index (BI), which is an objective scale of functional status, we investigated the association of BI with developing CDI and its impact on inhospital mortality in patients with CDI. Results: We enrolled 17,131 patients with 100 cases of CDI. Multivariable analysis revealed that lower BI (≤25) was an independent risk factor for developing CDI (adjusted odds ratio, 4.11; 95% confidence interval, 2.62–6.46). Furthermore, a combination of BI and Charlson comorbidity index (CCI) showed an adjusted odds ratio of 36.40 (95% confidence interval, 17.30–76.60) in the highest risk group. A high-risk group according to the combination of BI and CCI was estimated to have significantly higher inhospital mortality in patients with CDI using the Kaplan-Meier method (p = 0.017). A combination of lower BI and higher CCI was an independent predictor of inhospital mortality even in the multivariable Cox regression model (adjusted hazard ratio, 3.00; 95% confidence interval, 1.01–8.88). Conclusions: Assessment of functional status, especially combined with comorbidities, was significantly associated with developing CDI and may also be useful in predicting inhospital mortality. [ABSTRACT FROM AUTHOR]

(1) Background: Patients' comorbidities play an immanent role in perioperative risk assessment. It is unknown how Charlson Comorbidity Indices (CCIs) from different sources compare. (2) Methods: In this prospective observational study, we compared the CCIs of patients derived from patients' self-reports and from physicians' assessments with hospital administrative data. (3) Results: The data of 1007 patients was analyzed. Agreement between the CCI from patients' self-report compared to administrative data was fair (kappa 0.24 [95%CI 0.2–0.28]). Agreement between physicians' assessment and the administrative data was also fair (kappa 0.28 [95%CI 0.25–0.31]). Physicians' assessment and patients' self-report had the best agreement (kappa 0.33 [95%CI 0.30–0.37]). The CCI calculated from the administrative data showed the best predictability for in-hospital mortality (AUROC 0.86 [95%CI 0.68–0.91]), followed by equally good prediction from physicians' assessment (AUROC 0.80 [95%CI 0.65–0.94]) and patients' self-report (AUROC 0.80 [95%CI 0.75–0.97]). (4) Conclusions: CCIs derived from patients' self-report, physicians' assessments, and administrative data perform equally well in predicting postoperative in-hospital mortality. [ABSTRACT FROM AUTHOR]

Research on variables associated with chronic subdural hematoma (cSDH) resolution following middle meningeal artery embolization (MMAE) is limited. This study investigated the clinical utility of age-adjusted Charlson Comorbidity Index (ACCI) and modified 5-item Frailty Index (mFI - 5) for predicting cSDH resolution following MMAE. We identified patients who underwent MMAE at our institution between January 2018 and December 2022, with at least 20 days of follow-up and one radiographic follow-up study. Patient demographics, characteristics, and outcomes were collected. Complete resolution was defined as absence of subdural collections on CT-scan at last follow-up. Nonage adjusted CCI (CCI), ACCI, and mFI - 5 scores were calculated. Univariate and multivariable logistic regression analyzed the relationship between cSDH resolution and variables. A receiver operating characteristic (ROC) curve established the utility of ACCI and mFI - 5 in predicting hematoma resolution. The study included 85 MMAE procedures. In univariate analysis, patients without resolution were older, had higher CCI, higher ACCI, higher mFI - 5, and were more likely to have diabetes mellitus. In multivarible analysis, CCI (OR: 0.66, 95% CI: 0.48, 0.91) was independently associated with resolution controlling for age and antithrombotic resumption. The area under the ROC (AUROC) curve was 0.75 (95% CI: 0.65–0.85) for ACCI and 0.64 (95% CI: 0.52–0.76) for mFI - 5. The optimal cutoffs for predicting resolution were ACCI ≥5 (sensitivity = 0.63, specificity = 0.77), and mFI - 5 > 0 (sensitivity = 0.84, specificity = 0.43). ACCI and mFI - 5 moderately predict MMAE resolution and may aid in medical decision-making. [ABSTRACT FROM AUTHOR]

Hospital readmission involves the unplanned emergency admission of patients within 30 days from discharge after the previous admission. According to the Canadian Health Institute (CIHI), 1 in 11 patients were readmitted within 30 days of leaving the hospital in 2021. In the USA, nearly 20% of Medicare patients were readmitted after discharge, where the average cost of readmission was approximately USD 15,000, as reported by the Agency for Healthcare Research and Quality (AHQR) in 2018. To tackle this issue, we first conducted a descriptive analysis study to understand the risk factors associated with hospital readmission, and then we applied machine learning approaches to predict hospital readmission by using patients' demographic and clinical data extracted from the Electronic Health Record of the MIMIC-III clinical database. The results showed that the number of previous admissions during the last 12 months, hyperosmolar imbalance and comorbidity index were the top three significant factors for hospital readmission. The predictive model achieved a performance of 95.6% AP and an AUC = 97.3% using the Gradient Boosting algorithm trained on all features. [ABSTRACT FROM AUTHOR]

Total shoulder arthroplasty (TSA) is a common orthopedic procedure for glenohumeral osteoarthritis, rotator cuff arthropathy, and other degenerative conditions. The current standard hospital length of stay (LOS) commonly accepted following TSA is 1-2 days before discharge to home or a private facility. To evaluate the association between LOS and readmissions, revisions, and outcomes. Additionally, risk factors for increased LOS (> 24 hours) following TSA will be determined. A retrospective review identified all patients who underwent TSA between 2010 and 2019. Patients were excluded for chronic kidney disease requiring dialysis, preoperative corticosteroid use, revision TSA, undergoing a TSA for a fracture, or having no recorded outcome measures. Demographic information, operative details, medical comorbidities, length of hospital stay, complications, location of discharge, readmissions, revisions, and outcome scores were collected. Patients were categorized into two groups: discharge within 24 hours of TSA and discharge over 24 hours after TSA. Patients discharged within 24 hours had an average LOS of 0.96 ± 0.19 days, and patients discharged after 24 hours had an average LOS of 2.71 ± 1 day (P <.001). There were no significant differences in the groups with regard to race, sex, and body mass index. Patients discharged within 24 hours were younger at the time of surgery compared to patients discharged after 24 hours (66.7 ± 8.10 years and 70.1 ± 10.4 years, respectively [ P =.030]). There was a significant difference in discharge location between the groups with 86.2% of patients in the under-24 hour group being discharged to home compared to only 66.0% in the over-24 hour group (P =.006). There were no significant differences between the groups with regard to postoperative complication rate, 90-day readmission rate, and need for revision procedures. There was a significant difference in the Charlson comorbidity index between the groups with those discharged within 24 hours averaging an index score of 2.78 ± 1.33 and those discharged after 24 hours averaging an index score of 4.02 ± 2.07 (P <.001). No significant differences were found between preoperative and postoperative American Shoulder and Elbow Surgeons Shoulder Survey, Single Assessment Numeric Evaluation, or Simple Shoulder Test scores between the groups. Patients who had a hospital LOS over 24 hours following TSA were significantly older and discharged to nonhome locations at a higher rate. Patients with Charlson comorbidity index scores over 3 are more likely to have a LOS over 24 hours following TSA. Postoperative outcome measures were not affected by LOS with no significant differences in readmission rate, revision rates, and complications. [ABSTRACT FROM AUTHOR]

(1) Background: Unruptured intracranial aneurysm (UIA) occurs in 1–2% of the population and is being increasingly detected. Patients with UIA are treated with close observation, endovascular coiling or surgical clipping. The proportion of endovascular coiling has been rising. However, complications such as cerebral infarction (CI), intracranial hemorrhage (ICRH), and death remain crucial issues after coil treatment. (2) Methods: We analyzed the incidence and risk factors of complications after the use of coil in patients with UIA based on the patients' characteristics. We utilized the Health Insurance Review and Assessment (HIRA) database. Patients treated with coils for UIA between 1 January 2015 and 1 December 2021 were retrospectively analyzed. (3) Results: Of the total 35,140 patients, 1062 developed ICRH, of whom 87 died, with a mortality rate of 8.2%. Meanwhile, 749 patients developed CI, of whom 29 died, with a mortality rate of 3.9%. The overall mortality rate was 1.8%. In a univariate analysis of the risk factors, older age, males, a higher Charlson Comorbidity Index (CCI) score, and diabetes increase the risk of CI. Meanwhile, males with higher CCI scores and hemiplegia or paraplegia show increased ICRH risk. Older age, males and metastatic solid tumors relate to increased mortality risk. (4) Conclusions: This study is significant in that the complications based on the patient's underlying medical condition were analyzed. [ABSTRACT FROM AUTHOR]

(1) Background: The Charlson comorbidity index allocates two points for chronic kidney disease (CKD) if serum creatinine is above 3.0 mg/dL (270 µmol/L). However, contemporary CKD staging is based on the estimated glomerular filtration rate (eGFR) derived from population-based equations. The aim of this study was to determine the correlation between eGFR and the creatinine threshold of the Charlson comorbidity index for defining CKD. (2) Methods: We conducted a cross-sectional study of 664 patients with established CKD attending general nephrology clinics over 6 months. Dialysis patients and kidney transplant recipients were excluded. (3) Results: The median age was 68 years, and 58% of the participants were male. By modeling with fractional polynomial regression, we estimated that a creatinine of 270 µmol/L corresponded with an eGFR of 14.8 mL/min/1.73 m2 for females and 19.4 mL/min/m2 for males. We also estimated that an eGFR of 15 mL/min/1.73 m2 (threshold which defines Stage 5 CKD) corresponded to a serum creatinine of 275 µmol/L for females and 342 µmol/L for males. After applying these sex-specific creatinine thresholds, 39% of males and 3% of females in our CKD study population who scored points for CKD in the Charlson comorbidity index had not yet reached Stage 5 CKD. (4) Conclusions: There is a significant difference in the creatinine threshold to define Stage 5 CKD between males and females, with a bias for greater allocation of Charlson index points for CKD to males despite similar eGFR levels between the sexes. Further research could examine if replacing creatinine with eGFR improves the performance of the Charlson comorbidity index as a prognostic tool. [ABSTRACT FROM AUTHOR]

Introduction: Increased mortality after acute and chronic spinal cord injury (SCI) remains a challenge and mandates a better understanding of the factors contributing to survival in these patients. This study investigated whether body mass index (BMI) measured after acute traumatic SCI is associated with a change in mortality. Methods: A prospective longitudinal cohort study was conducted with 742 patients who were admitted to the Acute Spine Unit of the Vancouver General Hospital between 2004 and 2016 with a traumatic SCI. An investigation of the association between BMI on admission and long-term mortality was conducted using classification and regression tree (CART) and generalized additive models (spline curves) from acute care up to 7.7 years after SCI (chronic phase). Multivariable models were adjusted for (i) demographic factors (e.g., age, sex, and Charlson Comorbidity Index) and (ii) injury characteristics (e.g., neurological level and severity and Injury Severity Score). Results: After the exclusion of incomplete datasets (n = 602), 643 patients were analyzed, of whom 102 (18.5%) died during a period up to 7.7 years after SCI. CART identified three distinct mortality risk groups: (i) BMI: > 30.5 kg/m2, (ii) 17.5-30.5 kg/m2, and (iii) < 17.5 kg/m2. Mortality was lowest in the high BMI group (BMI > 30.5 kg/m2), followed by the middle-weight group (17.5-30.5 kg/m2), and was highest in the underweight group (BMI < 17.5 kg/m2). High BMI had a mild protective effect against mortality after SCI (hazard ratio 0.28, 95% CI: 0.09-0.88, p = 0.029), concordant with a modest "obesity paradox". Moreover, being underweight at admission was a significant risk factor for mortality up to 7.7 years after SCI (hazard ratio 5.5, 95% CI: 2.34-13.17, p < 0.001). Discussion: Mortality risk (1 month to 7.7 years after SCI) was associated with differences in BMI at admission. Further research is needed to better understand the underlying mechanisms. Given an established association of BMI with metabolic determinants, these results may suggest unknown neuro-metabolic pathways that are crucial for patient survival. [ABSTRACT FROM AUTHOR]

• Five models assessed the ability of four indices to predict complication and discharge. • The SSS and mFI-5 were stronger predictors than the CCI and the ASD-CS. • The SSS and the mFI-5 are preferable to the CCI for risk stratification and outcomes. Several spine-specific comorbidity indices are available to help risk-stratify patients before they undergo invasive spine procedures. Studies of patients with adult spinal deformity (ASD) typically use the Charlson Comorbidity Index (CCI), which is not specific to spine patients. To compare the CCI with the Seattle Spine Score (SSS), the Adult Spinal Deformity-Comorbidity Score (ASD-CS), and the Modified 5-Item Frailty Index (mFI-5) and identify which tool more accurately predicted major perioperative complications and discharge disposition after ASD surgery. Retrospective review. Patients with ASD who underwent spinal arthrodesis of at least four levels at a single institution. Self-reported measures include SSS, ASD-CS, and mFI-5. Functional measures include the CCI. We retrospectively reviewed records of 164 patients with ASD who underwent spinal arthrodesis of ≥ four levels from January 2008 to February 2018 at our U.S. academic tertiary care center and who had available Oswestry Disability Index values. To assess the predictive ability of the comorbidity indices, we created five multivariable logistic regression models, with the presence of major complications and discharge disposition (home or inpatient rehabilitation) as the primary outcome variables. The base model used validated demographic and surgical factors that were predictors of complications and outcomes in those with ASD and within the broader spinal literature. The other four models used the base model along with one of the four indices. The predictive ability of each model was compared using goodness-of-fit testing, with higher pseudo-R2 values and lower Akaike information criteria (AIC) values indicating better model fit. Thirty-one patients (19%) experienced major perioperative complications, and 68 (42%) were discharged to inpatient rehabilitation facilities (vs home). The model using the SSS had the highest pseudo-R2 value and lowest AIC value for both major complications and discharge disposition. The mFI-5 had a similar predictive ability. The models using the CCI and ASD-CS were weaker predictors. Compared with the CCI and the ASD-CS, the SSS and the mFI-5 were strong predictors of major complications and discharge disposition after ASD surgery. These results suggest that the SSS and the mFI-5 are preferable to the CCI for clinical risk stratification and outcomes research in patients undergoing ASD surgery. [ABSTRACT FROM AUTHOR]

A nationwide population-based database was utilized in a nested case–control study to explore the association between ambient air pollution exposure and the likelihood of developing connective tissue sarcoma. The study examined 280 cases of connective tissue sarcoma diagnosed between 2000 and 2012. A random sample of 1120 control subjects was selected from a subpopulation of claim records without a connective tissue sarcoma diagnosis in a 1:4 ratio. The control subjects were selected based on similar characteristics as the connective tissue sarcoma patients, including gender, birth year, and the year of diagnosis of the case group with medical records. Risk factors for connective tissue sarcoma were collected for analysis. Our data on exposure to air pollutants was collected from Taiwan's Air Quality Monitoring Network, which has been gathering air quality data from a growing network of sampling stations (now 76) throughout the country since 1997. It was discovered that the risk of connective tissue sarcoma was significantly increased by the Charlson comorbidity index (CCI), elevated levels of specific air pollution indices (e.g., total hydrocarbons (THC), fine particulate matter (PM2.5), and O3_8 (the annual mean of the daily maximum 8-h average concentration of O3), the High Pollutant Standards Index (hPSI) (the percentage of days in a given year in Taiwan where the PSI exceeds 100), and an insurable monthly wage over US$1100. Further investigation is needed to explore the involvement of these air pollutants in the formation of connective tissue sarcoma. [ABSTRACT FROM AUTHOR]

Background: Despite advance in pharmacotherapy of lipid disorders, lipoprotein apheresis (LA) plays a leading role in the management of severe hypercholesterolemia and in atherosclerosis prevention. Methods: Aim of this study was to retrospectively evaluate Charlson Comorbidity Index (CCI), presence of major comorbidity, and/or concomitant polypharmacy (definite as 5+ drugs daily) in patients with inherited dyslipidemias on chronic LA. Results: Since 1994, we performed more than 500 LA treatment/year and followed a total of 83 patients (age 56 [47–65] years, male 75%). In subjects with more than 5 years of LA treatment (38 patients, age 54 [45–62] years, male 66%), at the end of the observation time (9 [7–16] years), patients had higher CCI, polypharmacy, anemia, heart failure, peptic ulcer disease, and benign prostatic hyperplasia. Discussion: Even in the era of new lipid‐lowering therapies, the LA treatment established itself as a safe and lifesaving intervention. Patients on chronic LA require a multidisciplinary approach to address their comorbidity and the apheresis unit's medical staff (doctors and nurses) play a pivotal role creating a bridge toward the general practitioner and other specialists for overcoming clinical issues. [ABSTRACT FROM AUTHOR]

Background and Objectives: Kidney transplant recipients are at risk of developing more severe forms of COVID-19 infection. The aim of this study was to compare the clinical course of COVID-19 infection among kidney transplant patients and a control group. Materials and Methods: We examined 150 patients hospitalized with COVID-19 infection. Patients were divided into study (kidney transplant recipients, n = 53) and control (without a history of kidney transplantation, n = 97) groups. Demographics, clinical characteristics, treatment data, and clinical outcomes were assessed. Results: The median patient age was 56.0 (46.0–64.0) years, and seventy-seven patients (51.3%) were men. The median Charlson comorbidity index was higher in the study group (3.0 vs. 2.0, p < 0.001). There was a higher incidence of hypoxemia in the control group upon arrival (52.6% vs. 22.6%, p = 0.001) and a higher NEWS index median (2.0 vs. 1.0 points, p = 0.009) and incidence of pneumonia during hospitalization (88.7% vs. 73.6%, p = 0.023). In the study group, there were more cases of mild (26.4% vs. 11.3%, p = 0.023) and critically severe forms of COVID-19 infection (26.4% vs. 3.1%, p < 0.001), kidney failure was more prevalent (34.0% vs. 1.0%, p < 0.001), and a greater number of patients were transferred to the intensive care unit (22.6% vs. 3.1%, p < 0.001) and died (18.9% vs. 1.0%, p < 0.001). Multivariable analysis revealed that treatment in the intensive care unit correlated with a higher mortality rate than transplantation itself (HR = 20.71, 95% CI 2.01–213.33, p = 0.011). Conclusions: The course of the COVID-19 disease in kidney transplant recipients is heterogeneous and can be more severe than in the general population. Even though patients may be hospitalized with fewer symptoms, complications and death are more likely to occur. [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to clarify factors associated with polypharmacy among patients with systemic lupus erythematosus. Methods: This single-centre cross-sectional study was conducted by reviewing the medical records and questionnaire data of 261 systemic lupus erythematosus patients at a teaching hospital in Japan from 1 September to 30 November 2020. Polypharmacy was defined as the regular administration of five or more oral medications; excessive polypharmacy consisted of the regular use of 10 or more oral medications. This study investigated (1) the prevalence of polypharmacy and excessive polypharmacy, (2) the distribution of medication types, and (3) the factors associated with polypharmacy and excessive polypharmacy. Results: The proportions of patients who exhibited polypharmacy and excessive polypharmacy were 70% and 19%, respectively. Polypharmacy was associated with older age, long duration of systemic lupus erythematosus, high disease activity, and administration of glucocorticoids or immunosuppressive agents. Excessive polypharmacy was associated with a higher updated Charlson comorbidity index, history of visits to multiple internal medicine clinics, and presence of public assistance. Conclusions: Polypharmacy and excessive polypharmacy in patients with systemic lupus erythematosus are related to medical aspects such as disease severity and comorbidities in addition to social aspects such as hospital visitation patterns and economic status. [ABSTRACT FROM AUTHOR]

To examine the prevalence of comorbidities in Chinese urticaria patients and assess medication use patterns across different ages (6–11 years, 12–17 years, above 18 years), a retrospective cohort study was performed in 192,647 urticaria patients within the Health Database. After 1:1 propensity score matching, 166,921 people were divided into the urticaria group and the control group, and the follow-up data were collected within 2 years. During the 12-month and 24-month follow-up period, significant comorbidities identified included allergic rhinitis and asthma, with distinct patterns observed across age groups. Chronic urticaria patients often have complications, such as allergic rhinitis, upper respiratory infection, oropharyngeal infection, and dental caries. The study underscores the need for age-specific treatment strategies in urticaria management.

Background and objective: Limited data exist regarding the adverse events of advanced diagnostic bronchoscopy, with most of the available information derived from retrospective datasets that primarily focus on early complications. Methods: We conducted a 15-month prospective cohort study among consecutive patients undergoing endosonography and/or guided bronchoscopy under general anesthesia. We evaluated the 30-day incidence of severe complications, any complication, unplanned hospital encounters, and deaths. Additionally, we analyzed the time of onset (immediate, within 1 h of the procedure; early, 1 h–24 h; late, 24 h–30 days) and identified risk factors associated with these events. Results: Thirty-day data were available for 697 out of 701 (99.4%) enrolled patients, with 85.6% having suspected malignancy and multiple comorbidities (median Charlson Comorbidity Index (IQR): 4 (2–5)). Severe complications occurred in only 17 (2.4%) patients, but among them, 10 (58.8%) had unplanned hospital encounters and 2 (11.7%) died within 30 days. A significant proportion of procedure-related severe complications (8/17, 47.1%); unplanned hospital encounters (8/11, 72.7%); and the two deaths occurred days or weeks after the procedure. Low-dose attenuation in the biopsy site on computed tomography was independently associated with any complication (OR: 1.87; 95% CI 1.13–3.09); unplanned hospital encounters (OR: 2.17; 95% CI 1.10–4.30); and mortality (OR: 4.19; 95% CI 1.74–10.11). [ABSTRACT FROM AUTHOR]

Objective. To analyze the characteristics of patients with severe COVID-19 and lethal outcome. Materials and Methods. This retrospective pharmacoepidemiological study (March – April 2021) enrolled 172 patients with confirmed COVID-19 and death in the intensive care unit of City Clinical Hospital No. 24. Results. The mean age was 74.4 ± 7.4 years, patients over 65 years old – 81% (n = 139), over 75 years old – 44% (n = 75). Males – 66% (n = 113). All patients had a secondary bacterial infection. The predominant COVID-19 complications were respiratory failure (100%), pulmonary edema (96%), multiorgan failure (96%), and acute respiratory distress syndrome (92.4%). All patients had concomitant diseases (cardiovascular – 94.2%, gastrointestinal tract – 81.2%, endocrine – 72.0%). The mean Charlson Comorbidity Index was 7.4 points. The mean length of hospital stay was 12.4 ± 11.0 days (range: 1–36 days), the maximum number of deaths was observed on the 9th day. Analysis of laboratory parameters revealed a significant increase in ferritin, lactate dehydrogenase, and C-reactive protein levels, WBC, absolute lymphocyte count, as well as a decrease in RBC and platelet count at the last measurement before death. All patients received antibiotic therapy (carbapenems – 24%, fluoroquinolones and cephalosporins – 20% each). Antiviral therapy was performed in 62% (n = 106), predominantly with favipiravir (88%). Conclusions. The population of patients with fatal outcome due to COVID-19 was characterized by older age, high Charlson comorbidity index, predominance of cardiovascular, GI tract and endocrine diseases, and high levels of laboratory acute-phase inflammation markers.

Abstract Objectives This study aimed to explore the value of the Charlson comorbidity index (CCI) in predicting ICU admission in patients with aortic aneurysm (AA). Methods The clinical data of patients were obtained from the Medical Information Mart for Intensive Care-IV database. The association between CCI and ICU admission was explored by restricted cubic spline (RCS), threshold effect analysis, generalized linear model, logistic regression, interaction, and mediation analyses. Its clinical value was evaluated by decision curve analysis (DCA), receiver operating characteristic curve (ROC), DeLong's test, and net reclassification index (NRI) analyses. Results The ICU admission was significantly associated with the thoracic AA (TAA), unruptured status, and surgery status. Therefore, 288 candidate patients with unruptured TAA who received surgery were enrolled in the further analysis. We found that CCI was independently associated with the ICU admission of candidates (P = 0.005). Further, their nonlinear relationship was observed (adjusted P = 0.008), and a significant turning point of 6 was identified. The CCI had a favorable performance in predicting ICU admission (area under curve = 0.728) and achieved a better clinical net benefit. New models based on CCI significantly improved the accuracy of prediction. Besides the importance of CCI in ICU admission, CCI also exerted important interaction effect (rather than mediating effects) on the association of other variables (such as age and blood variables) with ICU admission requirements (all P

Abstract Background Older patients are more likely to have comorbidities than younger patients, and multiple comorbidities are associated with mortality in patients with cancer. Therefore, we hypothesized that a functional comorbidity index could predict the therapeutic effects of rehabilitation. Objectives In this study, we investigate whether the comorbidities influenced the execution and therapeutic effects of rehabilitation. Methods A consecutive cohort of 48 patients with gastrointestinal cancer who underwent surgery between January 1 and November 30, 2020, was analyzed. Charlson Comorbidity Index (CCI) scores were calculated based on data derived from medical records. The primary outcomes were ambulation status, duration (days) from the start of postoperative rehabilitation, and length of hospital stay. We investigated the relationship between CCI scores and primary outcomes. Results The CCI did not correlate with the duration of rehabilitation or the length of hospital stay. Subsequently, patients with functional recovery problems were evaluated, and we identified the conditions that were not included in the list using CCI scores. Most conditions are associated with surgical complications. Furthermore, using the Clavien-Dindo classification (CDC), we assessed the clinical features of the severity of complications. We found that the length of stay and the duration to start rehabilitation were significantly longer in the patients with higher severity of surgical complications (CDC≧III) than in those with lower severity (CDC≦II). Conclusions Treatment-related conditions may significantly impact the perioperative period more than the original comorbidities. In addition to original comorbidities, events related to surgical complications should be assessed to determine the therapeutic effects of rehabilitation in patients with gastrointestinal cancer.

Chronic obstructive pulmonary disease (COPD) patients are particularly susceptible to respiratory infections like influenza, which exacerbate symptoms and increase healthcare utilization. While smoking cessation and influenza vaccination are recommended preventive measures, their combined impact on healthcare resource utilization is underexplored. The Charlson Comorbidity Index (CCI) assesses comorbidity burden in COPD patients and may influence healthcare outcomes. We conducted a retrospective analysis of 357 COPD patients, evaluating smoking cessation success over one year and influenza vaccination receipt, stratifying patients by CCI scores. Healthcare utilization outcomes included emergency room visits, hospitalizations, and medical expenses. Results showed that 51.82% of patients quit smoking and 59.66% received influenza vaccination, with higher comorbidity prevalence in advanced COPD stages (p = 0.002). Both smoking cessation and influenza vaccination independently correlated with decreased emergency room visits, hospital admissions, days, and costs. Patients who both quit smoking and received influenza vaccination exhibited the lowest healthcare utilization rates. In conclusion, smoking cessation and influenza vaccination significantly reduce healthcare resource utilization in COPD patients, with the combination yielding synergistic benefits, particularly in those with lower CCI scores. Integrating these interventions and comorbidity management in COPD strategies is essential for optimizing patient outcomes and healthcare efficiency.

Radical cystectomy (RC) remains a mainstay surgical treatment for non-metastatic muscle-invasive and BCG-unresponsive bladder cancer. Various perioperative scoring tools assess comorbidity burden, complication risks, and cancer-specific mortality (CSM) risk. We investigated the prognostic value of these scores in patients who underwent RC between 2015 and 2021. Cox proportional hazards were used in survival analyses. Risk models’ accuracy was assessed with the concordance index (C-index) and area under the curve. Among 215 included RC patients, 63 (29.3%) died, including 53 (24.7%) cancer-specific deaths, with a median follow-up of 39 months. The AJCC system, COBRA score, and Charlson comorbidity index (CCI) predicted CSM with low accuracy (C-index: 0.66, 0.65; 0.59, respectively). Multivariable Cox regression identified the AJCC system and CCI > 5 as significant CSM predictors. Additional factors included the extent of lymph node dissection, histology, smoking, presence of concomitant CIS, and neutrophil-to-lymphocyte ratio, and model accuracy was high (C-index: 0.80). The internal validation of the model with bootstrap samples revealed its slight optimism of 0.06. In conclusion, the accuracy of the AJCC staging system in the prediction of CSM is low and can be improved with the inclusion of other pathological data, CCI, smoking history and inflammatory indices.

The aim was to evaluate two biomarker scores trained to identify comorbidity burden in the prediction of specified chronic morbidities, and mortality in the general population. Cardiovascular biomarkers were measured in the cardiovascular cohort of the Malmö Diet and Cancer Study. A score of 19 biomarkers associated with Charlson Comorbidity Index (CCI) was created (BSMDC). Individuals with CCI diagnoses and other major comorbidities were excluded. Another score of 11 biomarkers associated with comorbidity burden from a previous study of acute dyspnea was also created (BSADYS). The scores were prospectively evaluated for prediction of mortality, and some chronic diseases, using Cox Proportional Hazards Model. Fully adjusted models showed that BSMDC was significantly associated per 1 SD increment of the score with incident COPD, 55%, and congestive heart failure, 32%; and with mortality, 33% cardiovascular, 91% respiratory, 30% cancer, and 45% with all-cause mortality. The BSADYS showed no association with these outcomes, after simultaneous inclusion of both biomarker scores to all the clinical covariates. BSMDC shows strong prediction of morbidity and mortality in individuals free from comorbidities at baseline, and the results suggest that healthy individuals with high level of BSMDC would benefit from intense preventive actions. A score of 19 biomarkers associated with Charlson Comorbidity Index was created, the Biomarker Score of Malmö Diet and Cancer study (BSMDC). The created BSMDC index was associated with both incident COPD, and incident CHF. BSMDC was also associated with cardiovascular mortality, respiratory mortality, cancer mortality and with all-cause mortality. [ABSTRACT FROM AUTHOR]

Simple Summary: For certain malignancies, comorbidities are associated with an increased risk of cancer recurrence. However, it is unknown if this is also true for localized, non-muscle-invasive bladder cancer. The Charlson–Deyo comorbidity score is a commonly used tool for comorbidity-associated survival. We relied on this tool to stratify patients into low vs. high comorbidity burden groups and tested whether the comorbidity burden affected the risk of recurrence. Our data suggest that patients who harbor a high comorbidity burden have an increased risk of tumor recurrence. Purpose: To test the association between the Charlson–Deyo Comorbidity Index (CCI) and the recurrence of non-muscle-invasive bladder cancer (NMIBC). Methods: NMIBC (Ta, T1, TIS) patients who underwent transurethral resection of bladder tumor (TURB) between 2010 and 2018 were identified within a retrospective data repository of a large university hospital. Kaplan–Meier estimates and uni- and multivariable Cox regression models tested for differences in risk of recurrence according to low vs. high comorbidity burden (CCI ≤ 4 vs. >4) and continuously coded CCI. Results: A total of 1072 NMIBC patients were identified. The median follow-up time of the study population was 55 months (IQR 29.6–79.0). Of all 1072 NMIBC patients, 423 (39%) harbored a low comorbidity burden vs. 649 (61%) with a high comorbidity burden. Overall, the rate of recurrence was 10% at the 12-month follow-up vs. 22% at the 72-month follow-up. In low vs. high comorbidity burden groups, rates of recurrence were 6 vs. 12% at 12 months and 18 vs. 25% at 72 months of follow-up (p = 0.02). After multivariable adjustment, a high comorbidity burden (CCI > 4) independently predicted a higher risk of recurrence (HR 1.42, 95% confidence interval (CI) 1.06–1.92, p = 0.018). After multivariable adjustment, the hazard of recurrence increased by 5% per each one-unit increase on the CCI scale (HR 1.05, 95% CI 1.00–1.10, p = 0.04). Conclusions: Comorbidities in NMIBC patients are common. Our data suggest that patients with higher CCI have an increased risk of BC recurrence. As a consequence, patients with a high comorbidity burden should be particularly encouraged to adhere to NMIBC guidelines and conform to follow-up protocols. [ABSTRACT FROM AUTHOR]

Background: Multimorbidity is defined as the coexistence of two or more chronic health conditions in the same individual. It is associated with an increased number of hospital visits, polypharmacy, adverse drug events, increased treatment costs, increased burden on the families, poor functional status, poor quality of life, and an increased risk of death. Objective: The objective of the study is to determine the prevalence of multimorbidity and associated sociodemographic factors among elderly population in a rural area in south Kerala. Materials and Methods: This cross-sectional study was conducted among elderly population residing in the field practice area of a rural health training center of a medical college in South Kerala for a duration of 3 months from October 2019 to December 2019. Data were collected by interview of the subjects by the investigator. Charlson comorbidity index was used to assess the morbidity status of the subjects. Results: The self-reported prevalence of multimorbidity among the study participants was 86.4% (95% confidence interval: 82.5-90.3). In this, 42.8% had mild, 22.4% had severe, and 21.4% had moderate multimorbidity. Hypertension was the most common (53.1%) morbidity among the participants, followed by rheumatic diseases (42.7%) and diabetes mellitus (41%). Multimorbidity among the study participants was found to be significantly associated with their age, occupation status, and smoking habit among them. Conclusion: Multimorbidity among elderly population deserves much more attention than it has at present, and hence, there is an urgent need to focus on it with emphasis on the need to strengthen the health-care facilities for them, with respect to early identification and holistic management of their morbidities under one roof. [ABSTRACT FROM AUTHOR]

Objective Chronic myeloid leukemia is a myeloproliferative neoplasm with an incidence of 1–2 cases per 100 000 adults. Central to the pathogenesis of CML, is the fusion of the Abelson murine leukemia (ABL1) gene on chromosome 9 with the breakpoint cluster region (BCR) gene on chromosome 22. The therapeutic landscape changed dramatically with the development of the tyrosine kinase inhibitors (TKIs). This “targeted” approach altered the natural history of CML, improving the 10-year survival rate to 80-90%. This study aims to investigate the effective management of TKI treatment and overall survival in “real-life” CML patients and to discuss the results with current literature. Material and Method Fifty-eight patients who were diagnosed as CML between 2000 and 2018 in Suleyman Demirel University Hematology Department were evaluated. Patients’ clinical and laboratory characteristics, clinical and demographical features, treatment options, side effects and responses were evaluated in this study. Risk assessment and staging applied with World Health Organization criteria and Sokal Hasford and Eutos risk scoring system. We determined hematological, cytogenetic and molecular response according to European Leukemia Network criteria. Results The average age, male / female ratio and survival rates were found similar to those in literature. The age distribution (p = 0,001) and Charlson comorbidity index (p = 0.005) and Charlson comorbidity-age index (p = 0,000) had a statistically significant effect on overall survival. Age distribution (p = 0,029), Charlson comorbidity age index (p = 0,001) and major molecular response at 12 months (p = 0,028) were found to have a significant effect on disease-free survival. Major molecular response at 12 months (p = 0,006) also had a statistically significant effect on progression-free survival. Reticular fiber grade did not significantly affect overall survival, disease-free survival and progression free survival of patients. Conclusion These results suggest that CML is generally well managed with existing treatment options and that death occur more frequently due to other medical problems. In CML, Charlson indices have been shown to be significantly associated with overall survival and disease-free survival. Keywords: Charlson comorbidity index, Charlson comorbidity-age index, Chronic Myeloid Leukemia, Real life data, Prognosis [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to explore the value of the Charlson comorbidity index (CCI) in predicting ICU admission in patients with aortic aneurysm (AA). Methods: The clinical data of patients were obtained from the Medical Information Mart for Intensive Care-IV database. The association between CCI and ICU admission was explored by restricted cubic spline (RCS), threshold effect analysis, generalized linear model, logistic regression, interaction, and mediation analyses. Its clinical value was evaluated by decision curve analysis (DCA), receiver operating characteristic curve (ROC), DeLong's test, and net reclassification index (NRI) analyses. Results: The ICU admission was significantly associated with the thoracic AA (TAA), unruptured status, and surgery status. Therefore, 288 candidate patients with unruptured TAA who received surgery were enrolled in the further analysis. We found that CCI was independently associated with the ICU admission of candidates (P = 0.005). Further, their nonlinear relationship was observed (adjusted P = 0.008), and a significant turning point of 6 was identified. The CCI had a favorable performance in predicting ICU admission (area under curve = 0.728) and achieved a better clinical net benefit. New models based on CCI significantly improved the accuracy of prediction. Besides the importance of CCI in ICU admission, CCI also exerted important interaction effect (rather than mediating effects) on the association of other variables (such as age and blood variables) with ICU admission requirements (all P < 0.05). Conclusions: The CCI is an important predictor of ICU admission after surgery in patients with unruptured TAA. [ABSTRACT FROM AUTHOR]

Introduction: Though hip fractures are associated with significant mortality and morbidity, increasing life expectancy in developed countries necessitates an analysis of mortality trends and factors predicting long term survival. The aim of this study is to identify the predictors of 10-year mortality as well as assess the correlation of Age-adjusted Charlson comorbidity index (ACCI) with 10-year mortality in a surgically treated Asian geriatric hip fracture population. Materials and Methods: From January 1, 2007 to December 31, 2009, 766 patients who underwent surgery for hip fracture with a minimum follow up of 10-years were recruited to the study (92% follow-up rate). A review of the patient's electronic hospital records was performed to glean the following data: patient demographics, pre-existing comorbidities, operation duration, length of stay, fracture configuration, as well as mortality data up to 10 years. CCI scores and individual co-morbidities were correlated with inpatient, 30-day, 1-year, 5-year and beyond 10-year mortality. Results: Of the 766 patients, the mortality rate for 30-day, 1-year, 5-year and 10-years was 2.9%, 12.0%, 38.9% and 61.6% respectively. The average ACCI was 5.31. The 10-year mortality for patients with ACCI ≤ 3, ACCI 4-5 and ACCI ≥ 6 are 29.4%, 57.4% and 77.5% respectively. End-Stage-Renal Failure (ESRF), liver failure and COPD were dominant predictors of mortality at 10 years, whereas cancer was the predominant predictor at 1 year. Discussion: ACCI significantly correlates with the 10-year mortality after surgically treated hip fractures with a shift of the dominant predictors from cancer to ESRF and COPD. This could inform future health policy and resource planning. This data also represents recently available pre-pandemic survival trends after hip fracture surgery and serves as a baseline for post-pandemic outcome surveillance of interventions for fragility fractures. Conclusion: This study demonstrates that ACCI correlated with 10-year mortality after surgical treatment of hip fractures. [ABSTRACT FROM AUTHOR]