ArticleJournal of bone and mineral metabolism2025
Independent risk factors and survival prediction in hip refractures patients: insights from a 10-year cohort.
Article in Journal of bone and mineral metabolism, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Comment on "Independent risk factors and survival prediction in hip refractures patients: insights from a 10-year cohort".Journal of bone and mineral metabolism · 2025Article
Corrections and comments
- Commented on by
Authors and funding
4 authors.
Funding
Abstract
introductionHip fracture (HF) is one of the leading causes of mortality and disability in older populations. Hip refracture (HRF) is more serious than HF. We examined the survival rates of patients with HRFs at the Affiliated Dongyang Hospital of Wenzhou Medical University and developed a prediction model for their survival outcomes. MATERIALS AND
methodsThis study involved identifying and analyzing patients with HRFs from January 2013 to August 2023. Utilizing our hospital's database, we systematically extracted these patients' information. We monitored the survival time and constructed Kaplan-Meier (K-M) survival curve. Through Cox proportional hazards regression analyses, independent risk factors were identified. Based on these factors, a survival prediction model was developed and its reliability was evaluated by the receiver operating characteristic (ROC) curve. In addition, patients who refused surgery were excluded, the eligible patients were divided into a long waiting group (> 48 h) and a short waiting group (≤ 48 h). According to a similar process, independent risk factors were identified. Another nomogram chart and ROC curve were conducted.
resultsData from 174 patients were used, presenting a median survival time of 40 months. Both univariate and multivariate analyses identified age (HR = 1.71, 95% CI: 1.26-2.32), surgical intervention (HR = 0.34, 95% CI: 0.21-0.55), number of comorbidities (HR = 1.44, 95% CI: 1.09-1.92) and lymphocyte levels (HR = 0.75, 95% CI: 0.61-0.92) as independent influence factors. Based on these factors, a nomogram chart was constructed. The areas under the ROC curve for predicting 1-year, 2-year, and 3-year survival rates were 0.748, 0.794 and 0.806 respectively. Additionally, through regression analysis of surgical patients, some factors (age, number of comorbidities and lymphocyte levels) were supported as independent influence factors.
conclusionAdvanced age, non-surgical management, multiple comorbidities and lower lymphocyte levels showed a higher risk of all-cause mortality among the patients with HRFs, and these factors were associated with a poor prognosis in this patient population. This study may be useful for improving these patients' prognosis.
Indexed as
Identifiers
40679628What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.