17-β-Estradiol and Progesterone as Efficient Predictors of Survival in Older Women Undergoing Hip Fracture Surgery

Zhang, Yinwang; Xu, Zhen; Zhang, Jingyuan; Tang, Jie; Liu, Fuhai; Song, Yanting; Chen, Jie

doi:10.3389/fmed.2020.00345

Cited by 3 publications

(2 citation statements)

References 27 publications

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“…The previously described inclusion criteria were as follows 15 : (a) patients with hip fractures proven via imagological examination, (b) the minimum age of the patients was 60 years, (c) blood samples were preoperatively collected, (d) complete clinical, laboratory, imaging and follow‐up data were collected; (e) the patients were selected from inpatients; (f) the patients were free from systemic diseases; and (g) the patients were undergoing hip fracture surgery (internal fixation or joint replacement).…”

Section: Methodsmentioning

confidence: 99%

Pretreatment red blood cell distribution width as an efficient predictor of survival in older patients undergoing hip fracture surgery

Wei-Hsiang

Zhu

Zhang

et al. 2021

Int J Clinical Practice

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Purpose We aimed to determine whether pretreatment red blood cell distribution width (RDW) is an efficient predictor of 30‐day mortality in older patients undergoing hip fracture surgery. Methods In this prospective cohort study, 203 patients with hip fractures were eligible and followed up for at least 30 days. All the patients underwent medical examinations. RDW was measured using an automated hematology analyzer. To evaluate the prognostic significance of RDW, Cox proportional hazard model and Kaplan‐Meier analyses were performed. Results Of the 203 patients (114 men, 89 women), 28 (13.79%) died within 30 days. The mean RDW was significantly higher in the deceased group than in the survival group (14.54% ± 1.09% vs 13.26% ± 0.57%; P < .001). Multivariate Cox regression analysis showed that elevated RDW (hazard ratio = 2.73, 95% confidence interval = 2.06‐3.62, P < .001) was the key predictor of 30‐day mortality in older patients undergoing hip fracture surgery. Survival analysis showed that patients with a high RDW had a significantly higher 30‐day mortality rate (log‐rank test, P < .05). Similar results were observed in the male and female subgroups. Conclusion RDW might be an effective predictor of 30‐day mortality in older patients undergoing hip fracture surgery.

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Section: Methodsmentioning

confidence: 99%

Pretreatment red blood cell distribution width as an efficient predictor of survival in older patients undergoing hip fracture surgery

Wei-Hsiang

Zhu

Zhang

et al. 2021

Int J Clinical Practice

Self Cite

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“…Estrogen, a common sex steroid hormone active in the reproductive organs, is also found in other organs and tissues, such as the skeletal muscle (83). In postmenopausal women or following bilateral oophorectomy, limited estrogen levels can cause osteoporosis, frailty, and sarcopenia (84)(85)(86). Estrogen deficiency is also related to decreased muscle strength (87), but the effects and function of estrogen on muscles remain unclear (88,89).…”

Section: Estrogenmentioning

confidence: 99%

The Therapeutic Intervention of Sex Steroid Hormones for Sarcopenia

Huang

Wang

2021

Front. Med.

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Sarcopenia, characterized by the excessive loss of skeletal muscle mass, strength, and function, is associated with the overall poor muscle performance status of the elderly, and occurs more frequently in those with chronic diseases. The causes of sarcopenia are multifactorial due to the inherent relationship between muscles and molecular mechanisms, such as mitochondrial function, inflammatory pathways, and circulating hormones. Age-related changes in sex steroid hormone concentrations, including testosterone, estrogen, progesterone, and their precursors and derivatives, are an important aspect of the pathogenesis of sarcopenia. In this review, we provide an understanding of the treatment of sarcopenia through the regulation of sex steroid hormones. The potential benefits and future research emphasis of each sex steroid hormone therapeutic intervention (testosterone, SARMs, estrogen, SERMs, DHEA, and progesterone) for sarcopenia are discussed. Enhanced understanding of the role of sex steroid hormones in the treatment for sarcopenia could lead to the development of hormone therapeutic approaches in combination with specific exercise and nutrition regimens.

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A New Random Forest Algorithm-Based Prediction Model of Post-operative Mortality in Geriatric Patients With Hip Fractures

et al. 2022

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BackgroundPost-operative mortality risk assessment for geriatric patients with hip fractures (HF) is a challenge for clinicians. Early identification of geriatric HF patients with a high risk of post-operative death is helpful for early intervention and improving clinical prognosis. However, a single significant risk factor of post-operative death cannot accurately predict the prognosis of geriatric HF patients. Therefore, our study aims to utilize a machine learning approach, random forest algorithm, to fabricate a prediction model for post-operative death of geriatric HF patients.MethodsThis retrospective study enrolled consecutive geriatric HF patients who underwent treatment for surgery. The study cohort was divided into training and testing datasets at a 70:30 ratio. The random forest algorithm selected or excluded variables according to the feature importance. Least absolute shrinkage and selection operator (Lasso) was utilized to compare feature selection results of random forest. The confirmed variables were used to create a simplified model instead of a full model with all variables. The prediction model was then verified in the training dataset and testing dataset. Additionally, a prediction model constructed by logistic regression was used as a control to evaluate the efficiency of the new prediction model.ResultsFeature selection by random forest algorithm and Lasso regression demonstrated that seven variables, including age, time from injury to surgery, chronic obstructive pulmonary disease (COPD), albumin, hemoglobin, history of malignancy, and perioperative blood transfusion, could be used to predict the 1-year post-operative mortality. The area under the curve (AUC) of the random forest algorithm-based prediction model in training and testing datasets were 1.000, and 0.813, respectively. While the prediction tool constructed by logistic regression in training and testing datasets were 0.895, and 0.797, respectively.ConclusionsCompared with logistic regression, the random forest algorithm-based prediction model exhibits better predictive ability for geriatric HF patients with a high risk of death within post-operative 1 year.

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17-β-Estradiol and Progesterone as Efficient Predictors of Survival in Older Women Undergoing Hip Fracture Surgery

Cited by 3 publications

References 27 publications

Pretreatment red blood cell distribution width as an efficient predictor of survival in older patients undergoing hip fracture surgery

Pretreatment red blood cell distribution width as an efficient predictor of survival in older patients undergoing hip fracture surgery

The Therapeutic Intervention of Sex Steroid Hormones for Sarcopenia

A New Random Forest Algorithm-Based Prediction Model of Post-operative Mortality in Geriatric Patients With Hip Fractures

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