Citations

Abstract Background: Ovarian high-grade serous carcinomas (HGSC) comprise four distinct molecular subtypes based on mRNA expression patterns, with differential survival. Understanding risk factor associations is important to elucidate the etiology of HGSC. We investigated associations between different epidemiologic risk factors and HGSC molecular subtypes. Methods: We pooled data from 11 case–control studies with epidemiologic and tumor gene expression data from custom NanoString CodeSets developed through a collaboration within the Ovarian Tumor Tissue Analysis consortium. The PrOTYPE-validated NanoString-based 55-gene classifier was used to assign HGSC gene expression subtypes. We examined associations between epidemiologic factors and HGSC subtypes in 2,070 cases and 16,633 controls using multivariable-adjusted polytomous regression models. Results: Among the 2,070 HGSC cases, 556 (27%) were classified as C1.MES, 340 (16%) as C5.PRO, 538 (26%) as C2.IMM, and 636 (31%) as C4.DIF. The key factors, including oral contraceptive use, parity, breastfeeding, and family history of ovarian cancer, were similarly associated with all subtypes. Heterogeneity was observed for several factors. Former smoking [OR = 1.25; 95% confidence interval (CI) = 1.03, 1.51] and genital powder use (OR = 1.42; 95% CI = 1.08, 1.86) were uniquely associated with C2.IMM. History of endometriosis was associated with C5.PRO (OR = 1.46; 95% CI = 0.98, 2.16) and C4.DIF (OR = 1.27; 95% CI = 0.94, 1.71) only. Family history of breast cancer (OR = 1.44; 95% CI = 1.16, 1.78) and current smoking (OR = 1.40; 95% CI = 1.11, 1.76) were associated with C4.DIF only. Conclusions: This study observed heterogeneous associations of epidemiologic and modifiable factors with HGSC molecular subtypes. Impact: The different patterns of associations may provide key information about the etiology of the four subtypes.

Background: Many surgeons use body mass index (BMI) cutoffs when offering total hip arthroplasty (THA). However, little is known about who loses weight before THA, and if weight loss improves outcomes. This study determined how many patients lost weight before primary THA, identified predictors of preoperative weight loss, and evaluated whether preoperative weight loss was associated with improved outcomes. Methods: Among 53,038 primary THAs that were performed between 2002 and 2019, we identified 2,463 patients who had a BMI of ≥30 kg/m 2 (measured 1 to 24 months before surgery) and had their weight measured at the time of surgery. The mean age was 66 years; 47% were women. The mean BMI was 35 kg/m 2 . Nonparametric models evaluated potential associations with weight loss. Univariable and multivariable logistic regression and Cox proportional hazards models evaluated the impact of preoperative weight change on hospital length of stay, discharge disposition, operative time, periprosthetic joint infection (PJI), complications, revision, and reoperation. The mean follow-up was 5 years. Results: Overall, 17% of the patients gained >5 pounds (2.27 kg), 38% maintained their weight, 16% lost 5 to <10 pounds (4.54 kg), 17% lost 10 to <20 pounds (9.07 kg), and 12% lost ≥20 pounds before THA. Only 28% of patients with a preoperative BMI of ≥40 kg/m 2 achieved a BMI of <40 kg/m 2 by the time of surgery; those who did required a mean of 1.3 years to lose the weight. In multivariable analyses, there were no significant improvements in operative time, length of stay, and discharge disposition, or survivorship free of PJI, complication, revision, or reoperation for any weight-loss category when compared with those who maintained their weight. Conclusions: Only 12% of patients lost ≥20 pounds, and only 28% of patients with a BMI of ≥40 kg/m 2 achieved a BMI of <40 kg/m 2 before primary THA. There was no decrease in complications, revisions, or reoperations for any preoperative weight-loss category when compared with those who maintained their weight. While weight loss benefits overall health, the results of this study call into question whether preoperative weight loss alone is enough to reduce postoperative complications for most patients. Level of Evidence: Prognostic Level III . See Instructions for Authors for a complete description of levels of evidence.

Cognitive impairment involves alterations to one's cognitive status that affects everyday life. Individuals with CKD, and particularly kidney failure, experience higher rates of cognitive impairment (20%–70%) compared with the general population. The highest prevalence is described in kidney failure such that dialysis-dependent patients have twice the prevalence of age-matched controls. In the past 5 years, the number of investigations examining the “kidney-brain axis,” mechanisms of CKD-related cognitive impairment, and potential therapeutics have exponentially increased. This review article summarizes recent literature on direct and indirect effects of CKD-associated cognitive impairment with emphasis on uremic toxins; brain injury mechanisms; overlap between CKD-associated cognitive impairment, Alzheimer's disease, and other neurodegenerative diseases. Reviewed therapeutic interventions include AST-120 (indoxyl sulfate absorbent), CH-223191 (aryl hydrocarbon receptor antagonist), triarylmethane-34 (Kca3.1-specific inhibitor), anakinra (IL-1R inhibitor), marimastat, exercise, supplements, and kidney transplantation. Special focus is placed on translational studies examining uremic toxin–associated pathogenic processes, including brain oxidative stress, neuroinflammation, and blood-brain barrier dysfunction through in vitro and in vivo models of CKD-associated brain injury. Finally, future research directions are suggested, including targeting of cellular senescence abundance with senotherapeutics and capitalizing on anti-inflammatory effects of regenerative, cell-based therapeutics ( e.g ., mesenchymal stem cells and extracellular vesicles), and use of aged murine models. Collectively, CKD-associated cognitive impairment represents a prevalent condition for which remaining knowledge gaps exist, and scientific advancements are needed to preserve cognitive function and improve the lives of individuals with CKD.

Background We tested whether biologic age, as estimated by deficits, functional impairments, or Age‐Gap or their combination, provide improved estimation of cause‐specific death as compared with chronological age. Methods Cardiovascular and noncardiovascular deficits, functional impairments, and Age‐Gap were prospectively collected in 535 patients aged ≥55 years undergoing percutaneous coronary interventions between August 1, 2014, and March 31, 2018. Age‐Gap was calculated as the difference between chronological age and age estimated by artificial intelligence ECG using a convolutional neural network. The full biological age model included deficits, functional impairments, and Age‐Gap >2 SD. A multivariable reduced model with the least number of variables was also created to provide a comparable C index to the full model. Results The average chronological age was 72.1±9.5 years, and there were 68% of men. During a median follow‐up of 2.61 years, 124 (23%) patients died. There was a modest correlation between Age‐Gap and biological age ( r =0.28 [95% CI, 0.20–0.35]; P <0.001). When modeled with chronologic age as a covariate, Age‐Gap predicted all‐cause (hazard ratio [HR], 1.07 [95% CI, 1.04–1.10]; P <0.001) and cardiovascular (HR, 1.07 [95% CI, 1.04–1.11]; P <0.001) mortality. As compared with chronological age, the full biological age model noted significant improvement in the prediction of long‐term overall (95% CI, 0.65–0.78), cardiovascular (95% CI, 0.69–0.77), and noncardiovascular (95% CI, 0.55–0.86) mortality. In the reduced models, most prognostic information for noncardiovascular mortality (C index: 0.79) was obtained by subjective difficulty in performing tasks, whereas the deficit‐based estimation predicted cardiovascular mortality (C index: 0.72). Conclusions Estimated biological age from deficits and functional impairments was superior to chronological age in predicting long‐term cause‐specific mortality following percutaneous coronary interventions.