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Aims Wear of the polyethylene (PE) tibial insert of total knee arthroplasty (TKA) increases the risk of revision surgery with a significant cost burden on the healthcare system. This study quantifies wear performance of tibial inserts in a large and diverse series of retrieved TKAs to evaluate the effect of factors related to the patient, knee design, and bearing material on tibial insert wear performance. Methods An institutional review board-approved retrieval archive was surveyed for modular PE tibial inserts over a range of in vivo duration (mean 58 months (0 to 290)). Five knee designs, totalling 1,585 devices, were studied. Insert wear was estimated from measured thickness change using a previously published method. Linear regression statistical analyses were used to test association of 12 patient and implant design variables with calculated wear rate. Results Five patient-specific variables and seven implant-specific variables were evaluated for significant association with lower insert wear rate. Six were significant when controlling for other factors: greater patient age, female sex, shorter duration in vivo, polished tray, highly cross-linked PE (HXLPE), and constrained knee design. Conclusion This study confirmed that knee wear rate increased with duration in vivo. Older patients and females had significantly lower wear rates. Polished modular tibial tray surfaces, HXLPE, and constrained TKA designs were device design factors associated with significantly reduced wear rate. Cite this article: Bone Joint J 2021;103-B(11):1695–1701.

While deep learning has revolutionized ecological data analysis, existing strategies often rely on supervised learning, which is subject to limitations on real-world applicability. In this paper, we apply self-supervised deep learning methods to bioacoustic data to enable unsupervised detection of bioacoustic event boundaries. We propose a convolutional deep neural network that operates on the raw waveform directly and is trained in accordance with the Noise Contrastive Estimation principle, which enables the system to detect spectral changes in the input acoustic stream. The model learns a representation of the input audio sampled at low frequency that encodes information regarding dissimilarity between sequential acoustic windows. During inference, we use a peak finding algorithm to search for regions of high dissimilarity in order to identify temporal boundaries of bioacoustic events. We report results using these techniques to detect sperm whale (Physeter macrocephalus) coda clicks in real-world recordings, and we demonstrate the viability of analyzing the vocalizations of other species (e.g. Bengalese finch syllable segmentation) in addition to other data modalities (e.g. animal behavioral dynamics, embryo development and tracking). We find that the self-supervised deep representation learning-based technique outperforms established threshold-based baseline methods without requiring manual annotation of acoustic datasets. Quantitatively, our approach yields a maximal R-value and F1-score of 0.887 and 0.876, respectively, and an area under the Precision-Recall curve (PR-AUC) of 0.917, while a baseline threshold detector acting on signal energy amplitude returns a maximal R-value and F1-score of 0.620 and 0.576, respectively, and a PR-AUC of 0.571. We also compare with a threshold detector using preprocessed (e.g. denoised) acoustic input. The findings of this paper establish the validity of unsupervised bioacoustic event detection using deep neural networks and self-supervised contrastive learning as an effective alternative to conventional techniques that leverage supervised methods for signal presence indication. Providing a means for highly accurate unsupervised detection, this paper serves as an important step towards developing a fully automated system for real-time acoustic monitoring of bioacoustic signals in real-world acoustic data. All code and data used in this study are available online.

While changes in DNA methylation are known to occur early in breast carcinogenesis and the landscape of breast tumour DNA methylation is profoundly altered compared with normal tissue, there have been limited efforts to identify DNA methylation field cancerization effects in histologically normal breast tissue adjacent to tumour. Matched tumour, histologically normal tissue of the ipsilateral breast (ipsilateral-normal), and histologically normal tissue of the contralateral breast (contralateral-normal) were obtained from nine women undergoing bilateral mastectomy. Laser capture microdissection was used to select epithelial cells from normal tissue, and neoplastic cells from tumour for genome-scale measures of DNA methylation with the Illumina HumanMethylationEPIC array. We identified substantially more CpG loci that were differentially methylated between contralateral-normal and tumour (63,271 CpG loci q

Required reconsideration or review of do-not-resuscitate (DNR) orders perioperatively is recommended by the American Association of Nurse Anesthesiology and other organizations instead of automatic suspension of the DNR. A survey on perioperative DNR orders developed for a 2000 study by Coopmans and Gries was amended, reviewed by an expert panel, reformatted for web-based layout, and emailed to a random sample of 3,000 practicing Certified Registered Nurse Anesthetists (CRNAs) in the United States. From 207 returned responses, most CRNAs (63.5%) initially reported unfamiliarity with required reconsideration. After receiving a definition of the term, more CRNAs reported familiarity and past education on the concept. Chi-square analyses showed that familiarity with required reconsideration was associated with potential refusal to care for patients with active DNR orders (P=.004). CRNAs reported education or training on required reconsideration as uncommon and often informal. The survey found significant changes in reported perioperative DNR orders at practice institutions between the original survey by Coopmans and Gries and the present study. CRNAs' responses from the present survey indicate significant increases in policies of required review with patient involvement and policies of informed routine suspension (P.001). Findings also revealed a significant decrease in reported policies of uninformed routine suspension (P.001).

Purpose Due to the nature of military service, the patient-physician relationship in Veterans is unlike that seen in civilian life. The structure of the military is hypothesized to result in barriers to open patient-physician communication and patient participation in elective care decision-making. Decision quality is a measure of concordance between a chosen treatment and the aspects of medical care that matter most to an informed patient; high decision quality is synonymous with patient-centered care. While past research has examined how age and other demographic factors affect decision quality in Veterans, duration of military service, rank at discharge, and years since discharge have not been studied. Patients and methods We enrolled 25 Veterans with knee osteoarthritis at a VA hospital. Enrollees completed a survey with demographic, military service, and decision-making preference questions and the Hip-Knee Decision Quality Instrument (HK-DQI), which measures patients' knowledge about their disease process, concordance of their treatment decision, and the considered elements in their decision-making process. Results The HK-DQI knowledge score had a significant, positive correlation with duration of military service (R2=0.36, p=0.004). Rank at discharge and years since discharge did not show a significant correlation with decision quality (p=0.500 and p=0.317, respectively). The concordance score did not show a statistically significant correlation with rank, duration of service, and years since discharge (p=0.640, p=0.486 and p=0.795, respectively). Additionally, decision process score was not significantly associated with rank, duration of military service, and years since discharge (p=0.380, p=0.885, and p=0.474, respectively). Conclusion Decision quality in Veterans considering treatment for knee osteoarthritis appears to be correlated positively with duration of military service. These findings may present an opportunity for identification of Veterans at most risk of low decision quality and customization of shared decision-making methods for Veterans by characteristics of military service.

OBJECTIVES To (1) describe the prevalence of psychiatric illness in fracture patients ≥70 years of age and (2) investigate the association between psychiatric illness and complications requiring unplanned readmission in elderly patients. DESIGN Retrospective cohort study. PATIENTS/PARTICIPANTS One thousand one hundred eighty-six patients ≥70 years of age with surgically treated fractures and ≥1-month follow-up treated from 2012 to 2017. INTERVENTION None. MAIN OUTCOME MEASURE Complication requiring unplanned readmission. RESULTS Forty-four percent of patients ≥70 years of age have psychiatric comorbidities, and of those, 34% had >1 diagnosis. There was a higher rate of readmission among patients with psychiatric diagnosis compared with those without psychiatric diagnosis (35% vs. 21%, P < 0.001). There was a higher prevalence of psychiatric illness among patients 70 years of age or older compared with patients less than 70 years of age (44% vs. 39%, P = 0.007). Multivariate regression analysis controlling for age, sex, Charlson Comorbidity Index, dementia, delirium during admission, tobacco use, substance abuse, Injury Severity Score, fracture location, number of procedures, and number of fractures demonstrated an independent association between psychiatric illness and unplanned readmission (adjusted OR 1.54, 95% confidence interval, 1.15-2.07, P = 0.003). CONCLUSIONS Almost half of the elderly patients in the present cohort have psychiatric comorbidities. Furthermore, psychiatric illness is an independent predictor of unplanned readmission, which may have substantial consequences for recovery and cost of care. This emphasizes the need for more attention to these issues in geriatric patient populations and the need to identify means to influence the downstream consequences of these comorbidities. LEVEL OF EVIDENCE Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

DNA methylation (DNAm) alterations have been heavily implicated in carcinogenesis and the pathophysiology of diseases through upstream regulation of gene expression. DNAm deep-learning approaches are able to capture features associated with aging, cell type, and disease progression, but lack incorporation of prior biological knowledge. Here, we present modular, user-friendly deep learning methodology and software, MethylCapsNet and MethylSPWNet, that group CpGs into biologically relevant capsules – such as gene promoter context, CpG island relationship, or user-defined groupings – and relate them to diagnostic and prognostic outcomes. We demonstrate these models’ utility on 3,897 individuals in the classification of central nervous system (CNS) tumors. MethylCapsNet and MethylSPWNet provide an opportunity to increase DNAm deep learning analyses’ interpretability by enabling a flexible organization of DNAm data into biologically relevant capsules.

Objective: A 5% change in weight is a significant predictor for frailty and obesity. We ascertained how self-reported weight change over the lifespan impacts rates of frailty in older adults. Methods: We identified 4,984 subjects ≥60 years with body composition measures from the National Health and Nutrition Examination Survey. An adapted version of Fried’s frailty criteria was used as the primary outcome. Self-reported weight was assessed at time current,1 and 10 years earlier and at age 25. Weight changes between each time point were categorized as ≥ 5%, ≤5% or neutral. Logistic regression assessed the impact of weight change on the outcome of frailty. Results: Among 4,984 participants, 56.5% were female, mean age was 71.1 years, and mean BMI was 28.2kg/m2. A weight loss of ≥ 5% had a higher association with frailty compared to current weight, age 25 (OR 2.94 [1.72,5.02]), 10 years ago (OR 1.68 [1.05,2.69]), and 1 year ago (OR 1.55 [1.02,2.36]). Weight gain in the last year was associated with increased rate of frailty (1.59 [1.09,2.32]). Conclusion: There is an association between frailty and reported weight loss over time while only weight gain in the last year has an association with frailty.

OBJECTIVE: Body composition changes with aging can increase rates of obesity, frailty and impact function. Measuring adiposity using body fat (%BF) or central adiposity using waist circumference (WC) have greater diagnostic accuracy than traditional measures such as body mass index (BMI). DESIGN: This is an observational study SETTING: This study focused on older community-dwelling participants PARTICIPANTS: We identified individuals age ≥ 60 years old using the 1999–2004 cross-sectional National Health and Nutrition Survey (NHANES). INTERVENTION: The primary analysis evaluated the association between frailty and %BF or WC. Frailty was the primary predictor (robust=referent) and %BF and WC were considered continuous outcomes. Multiple imputation analyses accounted for missing characteristics. MEASUREMENT: Dual energy x-ray absorptiometry was used to assess %BF and WC was objectively measured. Frailty was defined using an adapted version of Fried’s criteria that was self-reported: (low BMI

Background Decision quality measures the degree to which care decisions are knowledge-based and value-aligned. Because military service emphasizes hierarchy, command, and mandates some healthcare decisions, military service may attenuate patient autonomy in healthcare decisions and lower decision quality. VA is the nation's largest provider of orthopedic care. We compared decision quality in a sample of VA and non-VA patients seeking care for knee osteoarthritis. Methods Our study sample consisted of patients newly referred to our orthopedic clinic for the management of knee osteoarthritis. None of the study patients were exposed to a knee osteoarthritis decision aid. Consenting patients were administered the Hip/Knee Decision Quality Instrument (HK-DQI). In addition, they were surveyed about decision-making preferences and demographics. We compared results to a non-VA cohort from our academic institution's arthroplasty database. Results The HK-DQI Knowledge Score was lower in the VA cohort (45%, SD = 22, n = 25) compared with the non-VA cohort (53%, SD = 21, n = 177) (p = 0.04). The Concordance Score was lower in the VA cohort (36%, SD = 49%) compared with the control cohort (70%, SD 46%) (p = 0.003). Non-VA patients were more likely to make a high-quality decision (p = 0.05). Non-VA patients were more likely to favor a shared decision-making process (p = 0.002). Conclusions Decision quality is lower in Veterans with knee osteoarthritis compared with civilians, placing them at risk for lower treatment satisfaction and possibly unwarranted surgical utilization. Our future work will examine if this difference is from conditioned military service behaviors or confounding demographic factors, and if conventional shared decision-making techniques will correct this deficiency.

Background Nearly 6 million deaths and over a half trillion dollars in healthcare costs worldwide are attributed to tobacco smoking each year. Extensive research efforts have been pursued to elucidate the molecular underpinnings of smoking addiction and facilitate cessation. In this study, we genotyped and obtained both resting state and task-based functional magnetic resonance imaging from 64 non-smokers and 42 smokers. Smokers were imaged after having smoked normally (“sated”) and after having not smoked for at least 12 h (“abstinent”). Results While abstinent smokers did not differ from non-smokers with respect to pairwise resting state functional connectivities (RSFCs) between 12 brain regions of interest, RSFCs involving the caudate and putamen of sated smokers significantly differed from those of non-smokers (P

Background DNA methylation (DNAm) is an epigenetic regulator of gene expression programs that can be altered by environmental exposures, aging, and in pathogenesis. Traditional analyses that associate DNAm alterations with phenotypes suffer from multiple hypothesis testing and multi-collinearity due to the high-dimensional, continuous, interacting and non-linear nature of the data. Deep learning analyses have shown much promise to study disease heterogeneity. DNAm deep learning approaches have not yet been formalized into user-friendly frameworks for execution, training, and interpreting models. Here, we describe MethylNet, a DNAm deep learning method that can construct embeddings, make predictions, generate new data, and uncover unknown heterogeneity with minimal user supervision. Results The results of our experiments indicate that MethylNet can study cellular differences, grasp higher order information of cancer sub-types, estimate age and capture factors associated with smoking in concordance with known differences. Conclusion The ability of MethylNet to capture nonlinear interactions presents an opportunity for further study of unknown disease, cellular heterogeneity and aging processes.

BackgroundEmerging work has demonstrated that histologically normal (non-tumor) tissue adjacent to breast tumor tissue shows evidence of molecular alterations related to tumorigenesis, referred to as field cancerization effects. Although changes in DNA methylation are known to occur early in breast carcinogenesis and the landscape of breast tumor DNA methylation is profoundly altered compared with normal tissue, there have been limited efforts to identify DNA methylation field cancerization effects in histologically normal breast tissue adjacent to tumor.MethodsMatched tumor, histologically normal tissue of the ipsilateral breast (ipsilateral-normal), and histologically normal tissue of the contralateral breast (contralateral-normal) were obtained from nine women undergoing bilateral mastectomy. Laser capture microdissection was used to select breast epithelial cells from normal tissues, and neoplastic cells from tumor specimens for genome-scale measures of DNA methylation with the Illumina HumanMethylationEPIC array.ResultsWe identified substantially more CpG loci that were differentially methylated between contralateral-normal breast and tumor tissue (63,271 CpG loci q < 0.01), than between ipsilateral-normal tissue and tumor (38,346 CpG loci q < 0.01). In addition, we identified differential methylation in ipsilateral-normal relative to contralateral-normal tissue (9,562 CpG loci p < 0.01). Hypomethylated loci in ipsilateral normal relative to contralateral were significantly enriched for breast cancer-relevant transcription factor binding sites including those for ESR1, FoxA1, and GATA3. Hypermethylated loci in ipsilateral-normal relative to contralateral-normal tissue were significantly enriched for CpG island shore regions.ConclusionsOur results indicate that early hypermethylation events in breast carcinogenesis are more likely to occur in the regions immediately surrounding CpG islands than CpG islands per se, reflecting a field effect of the tumor on surrounding histologically normal tissue. This work offers an opportunity to focus investigations of early DNA methylation alterations in breast carcinogenesis and potentially develop epigenetic biomarkers of disease risk.

BACKGROUND: Food insecurity refers to the physical, social, and economic inability to access and secure sufficient, safe and nutritious food. Food insecurity has been found to be associated with poor health status, obesity, and chronic disease. To date, a relationship between food insecurity and functional limitations has not been described in of older adults. METHODS: We examined 9,309 adults ≥60 years old from the 2005–2014 National Health and Nutrition Examination Surveys (NHANES). Food security was categorized as full, marginal, low, and very low. Functional limitations were assessed as having difficulty in physical, basic or instrumental activities of daily living. RESULTS: Of adults ≥60 years old (mean age: 70.5±0.08, 51% female), the prevalence of full, marginal, low, or very low food insecurity was 7,572 (81%), 717 (7%), 667 (8%), and 353 (4%), respectively. The prevalence of any functional limitations was 5,895 (66.3%). The adjusted odds (OR [95%CI]) of having any functional limitation in marginal, low, and very low food security levels compared to full food security are: 1.08 [1.02–1.13], 1.16 [1.10–1.22], 1.14 [1.07–1.21], respectively. The association between levels of food insecurity and functional limitation is modified by race/ethnicity. CONCLUSIONS: Functional limitation is significantly associated with increasing food insecurity in older adults.

Food insecurity refers to restricted or uncertain access to and ineffective utilization of nutritious and safe foods. Although food insecurity is linked to poorer physical health consequences among older adults, national estimates are not well known on food insecurity and depression. Using the 2005–2014 National Health and Nutrition Examination Survey, this study examines the associations between varying food insecurity levels and clinically relevant depressive symptoms (defined by PHQ-9≥10) among adults ≥60 years old (n=7,969). Rates of clinically relevant depressive symptoms in marginal, low, and very low food security were 12.3%, 16.3%, and 25.2%, respectively. Marginal, low, and very low food security were significantly associated with clinically relevant depressive symptoms: odds ratio (OR)=1.12 (95% confidence intervals [CI] 1.07–1.18), OR=1.07 (95% CI 1.03–1.12), and OR=1.24 (95% CI 1.16–1.32), respectively. Given the intersection of food insecurity and depression, geriatric health professionals should work to improve health and nutrition programs for older adults at risk for or experiencing both public health concerns.

Introduction Geriatric fracture patients are at risk for poorly controlled pain and side effects of opioid medications. The arthroplasty literature has demonstrated that infiltration of long-acting local anesthetic or anesthetic cocktails improves pain control and reduces post-operative opioid use resulting in better postoperative mobility without the deleterious effects of narcotics. Despite having a higher risk for adverse events, there is limited data among geriatric trauma patients. The aim this study was to evaluate whether local anesthetic infiltration (LAI) into the soft tissues surrounding the surgical field reduces narcotic use or pain scores in patients undergoing surgical management of proximal and diaphyseal femur fractures. Materials and methods A retrospective review was performed of patients age >65 undergoing operative intervention for proximal and diaphyseal femur fracture. The electronic record was utilized to determine if local anesthetic was injected into the surgical wound, the amount of narcotics administered over 48 h in four-hour intervals, and to obtain visual analog scale (VAS) pain scores associated with patients post-operative course in four-hour intervals. The amount of narcotics was converted to morphine milligram equivalents (MME). Results Among 477 patients with femur fracture, 358 did not receive LAI and 119 patients received LAI. Baseline demographics, fracture types, and surgical procedure were equivalent between the groups. In the first 28 h following surgery, compared with those who did not receive LAI, those who did required significantly less opioid (57.8 MME versus 94.3 MME, p = 0.034) and despite decreased narcotics, had equal pain scores (mean difference 0.37, p = 0.22). There was no difference in rates of post-operative complications. Conclusion LAI is associated with a reduction in opioid consumption in geriatric fracture patients with equivalent pain scores. Optimizing pain control is a critical issue in caring for geriatric fracture patients since both under-treated pain and opioid medications are implicated in postoperative delirium, complications, and ability to mobilize early. More research is needed to identify effective ways to optimize pain management in this at-risk patient population.

OBJECTIVES To evaluate physical function and return to independence of geriatric trauma patients, to compare physical function outcomes of geriatric patients who sustained high-energy trauma with that of those who sustained low-energy trauma, and to identify predictors of physical function outcomes. DESIGN Retrospective. SETTING Urban Level I trauma center. PATIENTS Study group of 216 patients with high-energy trauma and comparison group of 117 patients with low-energy trauma. INTERVENTION Injury mechanism (high- vs. low-energy mechanism). MAIN OUTCOME MEASUREMENT Patient-Reported Outcomes Measurement Information System Physical Function (PROMIS PF) patient-reported outcome measure, and change in living situation and mobility. RESULTS Physical function outcomes and return to independence differed between patients with high-energy and low-energy injuries. High-energy geriatric trauma patients had significantly higher PROMIS PF scores compared with low-energy geriatric trauma patients (PROMIS PF score 42.2 ± 10.4 vs. 24.6 ± 10.4, P < 0.001). High-energy geriatric trauma patients were able to ambulate outdoors without an assistive device in 67% of cases and were living independently 74% of the time in comparison with 28% and 45% of low-energy geriatric trauma patients, respectively (P < 0.001, P < 0.001). Multivariate linear regression analysis demonstrated that low-energy mechanism injury was independently associated with a 13.2 point reduction in PROMIS PF score (P < 0.001). CONCLUSIONS Geriatric patients greater than 1 year out from sustaining a high-energy traumatic injury seem to be functioning within the expected range for their age, whereas low-energy trauma patients seem to be functioning substantially worse than both age-adjusted norms and their high-energy cohorts. LEVEL OF EVIDENCE Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Lack of available resources has been identified as a significant barrier for community implementation of climate adaptation actions. Although a broad array of federal resources exists, it i...

Sarcopenia is a gradual loss of muscle mass and strength that occurs with aging. This muscle deterioration is linked to increased morbidity, disability, and other adverse outcomes. Although reduced handgrip strength can be considered a marker of sarcopenia and other aging-related decline in the elderly, there is limited research on this physical health problem in at-risk groups with common biopsychosocial conditions such as depression. Our primary objective was to ascertain level of combined handgrip strength and its relationship with depression among adults aged 60 years and older. Unadjusted and adjusted linear regression models were conducted with a cross-sectional survey dataset. Secondary dataset from the 2011–2014 National Health and Nutrition Examination Survey (NHANES). Community-dwelling, noninstitutionalized adults ≥60 years old (n=3,421). The predictor variables included a positive screen for clinically relevant depression (referent=PHQ-9 score

Recent advances in deep learning, particularly unsupervised approaches, have shown promise for furthering our biological knowledge through their application to gene expression datasets, though applications to epigenomic data are lacking. Here, we employ an unsupervised deep learning framework with variational autoencoders (VAEs) to learn latent representations of the DNA methylation landscape from three independent breast tumor datasets. Through interrogation of methylation-based learned latent dimension activation values, we demonstrate the feasibility of VAEs to track representative differential methylation patterns among clinical subtypes of tumors. CpGs whose methylation was most correlated VAE latent dimension activation values were significantly enriched for CpG sparse regulatory regions of the genome including enhancer regions. In addition, through comparison with LASSO, we show the utility of the VAE approach for revealing novel information about CpG DNA methylation patterns in breast cancer.

AimsThe aims of this study were to quantify health state utility values (HSUVs) after a tibial fracture, investigate the effect of complications, to determine the trajectory in HSUVs that result in these differences and to quantify the quality-adjusted life years (QALYs) experienced by patients.Patients and MethodsThis is an analysis of 2138 tibial fractures enrolled in the Fluid Lavage of Open Wounds (FLOW) and Study to Prospectively Evaluate Reamed Intramedullary Nails in Patients with Tibial Fractures (SPRINT) trials. Patients returned for follow-up at two and six weeks and three, six, nine and 12 months. Short-Form Six-Dimension (SF-6D) values were calculated and used to calculate QALYs.ResultsCompared with those who did not have a complication, those with a complication treated either nonoperatively or operatively had lower HSUVs at all times after two weeks. The HSUVs improved in all patients with the passage of time. However, they did not return to the remembered baseline preinjury values nor to US age-adjusted normal values by 12 months after the injury.ConclusionWhile the acute fracture and complications may have resolved clinically, the detrimental effect on a patient’s quality of life persists up to 12 months after the injury. Cite this article: Bone Joint J 2018;100-B:1227–33.

Objectives To determine the relationship between frailty and overall and cardiovascular mortality. Design Longitudinal mortality analysis. Setting National Health and Nutrition Examination Survey (NHANES) 1999–2004. Participants Community‐dwelling older adults aged 60 and older (N = 4,984; mean age 71.1 ± 0.19, 56% female). Measurements We used data from 1999–2004 cross‐sectional NHANES and mortality data from the National Death Index, updated through December 2011. An adapted version of Fried's frailty criteria was used (low body mass index, slow walking speed, weakness, exhaustion, low physical activity). Frailty was defined as persons meeting 3 or more criteria, prefrailty as meeting 1 or 2 criteria, and robust (reference) as not meeting any criteria. The primary outcome was to evaluate the association between frailty and overall and cardiovascular mortality. Cox proportional hazard models were used to evaluate the association between risk of death and frailty category adjusted for age, sex, race, smoking, education, coronary artery disease, heart failure, nonskin cancer, diabetes, and arthritis. Results Half (50.4%) of participants were classified as robust, 40.3% as prefrail, and 9.2% as frail. Fully adjusted models demonstrated that prefrail (hazard ratio (HR) = 1.64, 95% confidence interval (CI) = 1.45–1.85) and frail (HR = 2.79, 95% CI = 2.35–3.30) participants had a greater risk of death and of cardiovascular death (prefrail: HR = 1.84, 95% CI = 1.45–2.34; frail: HR = 3.39, 95% CI = 2.45–4.70). Conclusion Frailty and prefrailty are associated with increased risk of death. Demonstrating the association between prefrail status and mortality is the first step to identifying potential targets of intervention in future studies.

Background: Head and neck squamous cell carcinoma (HNSCC) is commonly diagnosed at an advanced stage, and prognosis for such patients is poor. There remains a gap in our understanding of genetic variants related with HNSCC prognosis. miRNA-related single nucleotide polymorphisms (miR-SNPs) are a class of genetic variants with gene-regulatory potential. Methods: We used a genome-scale approach and independent patient populations in a two-stage approach to test 40,286 common miR-SNPs for association with HNSCC survival in the discovery population (n = 847), and selected the strongest associations for replication in validation phase cases (n = 1,236). Furthermore, we leveraged miRNA interaction databases and miRNA expression data from The Cancer Genome Atlas, to provide functional insight for the identified and replicated associations. Results: Joint population analyses identified novel miR-SNPs associated with overall survival in oral and laryngeal cancers. rs1816158, located within long noncoding RNA MIR100HG, was associated with overall survival in oral cavity cancer (HR, 1.56; 95% confidence interval (CI), 1.21–2.00). In addition, expression of MIR100HG-embedded miRNA, miR-100, was significantly associated with overall survival in an independent cohort of HNSCC cases (HR, 1.25; 95% CI, 1.06–1.49). A SNP in the 3′UTR of SH3BP4 (rs56161233) that overlaps predicted miRNA-binding sites and is predicted to disrupt several miRNA–mRNA interactions was associated with overall survival of laryngeal cancer (HR, 2.57; 95% CI, 1.71–3.86). Conclusions: This work reveals novel miR-SNPs associated with HNSCC survival, and utilizes miRNA-mRNA interaction and expression data to provide functional support for these associations. Impact: These findings extend our understanding of how genetic variation contributes to HNSCC survival, and may contribute to future prognostic models for improved risk stratification.

Objective Arthritis and depressive symptoms often interact and negatively influence one another to worsen mental and physical health outcomes. Better characterization of arthritis rates among older adults with different levels of depressive symptoms is an important step toward informing mental health professionals of the need to detect and respond to arthritis and related mental health complications. The primary objective is to determine arthritis rates among US older adults with varying degrees of depression. Methods Using National Health and Nutrition Examination Survey 2011 to 2014 data (N = 4792), we first identified participants aged ≥50 years. Measures screened for depressive symptoms and self-reported doctor-diagnosed arthritis. Weighted logistic regression models were conducted. Results Prevalence of arthritis was 55.0%, 62.9%, and 67.8% in participants with minor, moderate, and severe depression, respectively. In both unadjusted and adjusted regression models, a significant association between moderate depression and arthritis persisted. There were also significant associations between minor and severe depression with arthritis. Conclusions Arthritis is commonly reported in participants with varying degrees of depression. This study highlights the importance of screening for and treating arthritis-related pain in older adults with depressive symptoms and the need for future geriatric psychiatry research on developing integrated biopsychosocial interventions for these common conditions.

Objectives:This study aimed to: describe the incidence of thyroid gland involvement in advanced laryngeal cancer, analyse patterns of spread to the thyroid and elucidate predictors of thyroid involvement.Methods:A retrospective review was performed on patients who underwent laryngectomy from 1991 to 2015 as a primary or salvage treatment for squamous cell carcinoma of the larynx, hypopharynx or base of tongue. The incidence of thyroidectomy during total laryngectomy, type of thyroidectomy, incidence of gland involvement, route of spread, and positive predictors of spread were analysed and reported.Results:A total of 188 patients fit the inclusion criteria. Of these, 125 (66 per cent) underwent thyroidectomy. The thyroid was involved in 10 of the 125 patients (8 per cent), 9 by direct extension and 1 by metastasis. Cartilage invasion was a predictor of thyroid gland involvement, with a positive predictive value of 26 per cent.Conclusion:There is a low incidence of thyroid gland involvement in laryngeal carcinoma. Most cases of gland involvement occurred by direct extension. Thyroidectomy during laryngectomy should be considered for advanced stage tumours with cartilage invasion.

Breast cancer is a complex disease consisting of four distinct molecular subtypes. DNA methylation-based (DNAm) studies in tumors are complicated further by disease heterogeneity. In the present study, we compared DNAm in breast tumors with normal-adjacent breast samples from The Cancer Genome Atlas (TCGA). We constructed models stratified by tumor stage and PAM50 molecular subtype and performed cell-type reference-free deconvolution to control for cellular heterogeneity. We identified nineteen differentially methylated gene regions (DMGRs) in early stage tumors across eleven genes (AGRN, C1orf170, FAM41C, FLJ39609, HES4, ISG15, KLHL17, NOC2L, PLEKHN1, SAMD11, WASH5P). These regions were consistently differentially methylated in every subtype and all implicated genes are localized to the chromosomal cytoband 1p36.3. Seventeen of these DMGRs were independently validated in a similar analysis of an external data set. The identification and validation of shared DNAm alterations across tumor subtypes in early stage tumors advances our understanding of common biology underlying breast carcinogenesis and may contribute to biomarker development. We also discuss evidence of the specific importance and potential function of 1p36 in cancer.

Breast cancer is a complex disease and studying DNA methylation (DNAm) in tumors is complicated by disease heterogeneity. We compared DNAm in breast tumors with normal-adjacent breast samples from The Cancer Genome Atlas (TCGA). We constructed models stratified by tumor stage and PAM50 molecular subtype and performed cell-type reference-free deconvolution on each model. We identified nineteen differentially methylated gene regions (DMGRs) in early stage tumors across eleven genes (AGRN, C1orf170, FAM41C, FLJ39609, HES4, ISG15, KLHL17, NOC2L, PLEKHN1, SAMD11, WASH5P). These regions were consistently differentially methylated in every subtype and all implicated genes are localized on chromosome 1p36.3. We also validated seventeen DMGRs in an independent data set. Identification and validation of shared DNAm alterations across tumor subtypes in early stage tumors advances our understanding of common biology underlying breast carcinogenesis and may contribute to biomarker development. We also provide evidence on the importance and potential function of 1p36 in cancer.

With the explosion of data in healthcare, there is a growing need to develop intelligent methods for automatically mining and implementing analyses from these data. In clinical applications, longitudinal patient records are often stored in disparate systems or locations in a non-integreted manner, adding work to providers and researchers to effectively utilize the information. Recent work with treatment recommendation systems has begun to help clinicians overcome these challenges, but there remains a need for concise synthesis, abstraction, and presentation of this temporal information. We present a method for unsupervised classification of common co-occuring medication administration and patient surgical events in electronic medical record data using vector-space analysis and unsupervised cluster classification. This work was done independent of domain expertice and demonstrates a method of identifying co-occuring patient events.

Summary: The public availability of high throughput molecular data provides new opportunities for researchers to advance discovery, replication and validation efforts. One common challenge in leveraging such data is the diversity of measurement approaches and platforms and a lack of utilities enabling cross-platform comparisons among data sources for analysis. We present a method to map DNA methylation data from bisulfite sequencing approaches to CpG sites measured with the widely used Illumina methylation bead-array platforms. Correlations and median absolute deviations support the validity of using bisulfite sequencing data in combination with Illumina bead-array methylation data. Availability and Implementation: https://github.com/Christensen-Lab-Dartmouth/methyLiftover includes source, documentation and data references. Contact: brock.c.christensen@dartmouth.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Body composition changes with aging can impact function in older adults leading to frailty. Measuring adiposity using body fat or central adiposity using waist circumference (WC) have greater diagnostic accuracy than traditional measures such as body mass index (BMI).