Hip fracture is a significant public health problem, with associated high morbidity and mortality. Orthopedic surgeons are concerned to improve prognosis and stratify mortality risk after hip fracture surgery. This study established a nomogram that combines the Charlson Comorbidity Index (CCI) with specific laboratory parameters to predict mortality risk after hip fracture surgery in geriatrics. Methods: The records of consecutive patients who underwent hip fracture surgery from January 2015 through May 2020 at one medical center were reviewed for perioperative factors and mortality. Patients with age ≥ 70 years who were diagnosed with intertrochanteric or femoral neck fractures were included. Patients who were diagnosed with pathological fracture, received only conservative treatment or lost to follow-up were excluded. A multivariate Cox proportional hazards regression model was used to identify risk factors. A nomogram was established with R software and evaluated using concordance (C)-index, area under receiver operating characteristic (AUC), calibration curves, and decision curve analysis (DCA). Results: In total, 454 patients were included with a mean age of 81.6 years. The mean follow-up and oneyear mortality rate were 37.2 months and 10.4%, respectively. Five identified risk variables for mortality after hip fracture surgery in geriatrics comprised age (HR 1.05, 95% CI 1.01-1.08; P = 0.003), CCI (HR 1.38, 95% CI 1.24-1.54; P = 0.0 0 0), albumin (HR 1.78, 95% CI 1.31-2.43; P = 0.0 0 0), sodium (HR 1.59, 95% CI 1.18-2.15; P = 0.002) and hemoglobin (HR 1.46, 95% CI 1.07-2.00; P = 0.02). A nomogram was proposed and evaluated, showing a C-index of 0.76 ± 0.02. The AUCs for 6-month, 1-year, and 3-year mortality predictions were 0.83, 0.79, and 0.77, respectively. The calibration curve and DCA showed good discrimination and clinical usefulness. Conclusion: This novel nomogram for stratifying the mortality risk after hip fracture surgery in geriatrics incorporated age, CCI, serum albumin, sodium, and hemoglobin. Internal validation indicated that the model has good accuracy and usefulness. This nomogram had improved convenience and precision compared with other models. External validation is warranted to confirm its performance.

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Rheumatoid arthritis (RA) is a chronic inflammatory and autoimmune disorder. RA is progressive and needs long-term treatment. Vitexin is a naturally-occurring flavonoid that is identified in various plant sources. Vitexin is demonstrated to produce antioxidant effects with numerous pharmacological activities. This experimental in vivo study assessed the antiarthritic and apoptotic role of a natural plant extract, vitexin, on RA. Collagen-induced arthritis (CIA) rat model Sprague Dawley males were grouped into five sets with six rats each: control, CIA, CIA + vitexin (10 mg/kg bw), CIA + Methotrexate (1 mg/kg bw), and vitexin (10 mg/kg bw) alone.The body weight, organ weight, biochemical assay, inflammatory enzymes, apoptosis, and cytokines levels were evaluated and compared among groups. Janus kinase (JAK)/signal transducer and activator of transcription (STAT)/suppressors of cytokine signaling (SOCS) levels and histopathology of ankle joints were also studied and compared. Significance was considered at a p < 0.05. Vitexin (10 mg/kg bw) significantly reduced the inflammatory enzyme markers, interleukin (IL)-1β, IL-6, IL-17, IL-4, IL-10, tumor necrosis factor-α, interferon-γ, and iNOS levels in arthritis rats (p < 0.05). Vitexin significantly improved collagen-induced arthritic histological changes (p < 0.05). Vitexin also reduced JAK/STAT expressions associated with inflammation and significantly increased elevated SOCS levels (p < 0.05). Aberration in apoptosis, inflammatory mediators, C-reactive protein, and rheumatoid factor levels in the arthritic rats reverted to normal with vitexin. These results emphasize that vitexin possesses anti-inflammatory and apoptotic activity via the regulation of JAK/STAT/SOCS signaling in CIA in a rat model. Hence, vitexin is a promising auxiliary drug for RA treatment.

Background: Acute kidney injury (AKI), characterized by sudden impairment of kidney function, is an uncommon complication following hip fracture surgery that is associated with increased morbidity and mortality. We constructed a nomogram to stratify patients according to risk of AKI after hip fracture surgery to guide clinicians in the implementation of timely interventions. Methods: Patients who received hip fracture surgery from January 2015 to December 2021 were retrospectively identified and divided into a training set (n=448, surgery from January 2015 to December 2019) and a validation set (n=200, surgery from January 2020 to December 2021). Univariate and multivariate logistic regression were used to identify risk factors for AKI after surgery in the training set. A nomogram was constructed based the risk factors for AKI, and was evaluated by receiver operating characteristic (ROC) analysis, calibration curves, and decision curve analysis (DCA). Results: The mean age was 82.0±6.22 years-old and the prevalence of post-surgical AKI was 13.3%. Age, American Society of Anesthesiologists (ASA) score, the preexistence of chronic kidney disease (CKD), cemented surgery and the decrease of hemoglobin on the first day after surgery were identified as independent risk factors of AKI after hip fracture surgery, and a predictive nomogram was established based on the multivariable model. The predictive nomogram had good discrimination ability (training set: AUC: 0.784, 95% CI: 0.720-0.848; validation set: AUC: 0.804, 95% CI: 0.704-0.903), and showed good validation ability and clinical usefulness based on a calibration plot and decision curve analysis. Conclusion: A nomogram that incorporated five risk factors including age, ASA score, preexisting CKD, cemented surgery and the decrease of hemoglobin on the first day after surgery had good predictive performance and discrimination. Use of our results for early stratification and intervention has the potential to improve the outcomes of patients receiving hip fracture surgery. Future large, multicenter cohorts are needed to verify the model's performance.

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