Literature DB >> 31154849

Validation of a prospective cohort study of older adults with hip fractures.

D Metcalfe1, M L Costa1, N R Parsons2, J Achten1, J Masters1, M E Png1, S E Lamb1, X L Griffin1.   

Abstract

AIMS: This study sought to determine the proportion of older adults with hip fractures captured by a multicentre prospective cohort, the World Hip Trauma Evaluation (WHiTE), whether there was evidence of selection bias during WHiTE recruitment, and the extent to which the WHiTE cohort is representative of the broader population of older adults with hip fractures. PATIENTS AND METHODS: The characteristics of patients recruited into the WHiTE cohort study were compared with those treated at WHiTE hospitals during the same timeframe and submitted to the National Hip Fracture Database (NHFD).
RESULTS: Patients recruited to WHiTE were more likely to be admitted from their own home (83.5% vs 80.2%; p < 0.001) and to have a higher median Abbreviated Mental Test Score (AMTS) (9 (interquartile range (IQR) 6 to 10) vs 9 (IQR 5 to 10); p < 0.001) than those who were not recruited. In terms of WHiTE cohort generalizability, participating hospitals included a greater proportion of Major Trauma Centres (47.8% vs 7.8%) and large hospitals (997 (IQR 873 to 1290) vs 707 (459 to 903) beds) with high-volume Emergency Departments (median annual attendances of 43 981 (IQR 37 147 to 54 385) vs 35 964 (IQR 26 229 to 50 551)). However, there were few differences in baseline characteristics between patients in the WHiTE cohort and those recorded in the NHFD.
CONCLUSION: There is evidence of a weak selection bias towards recruiting fitter patients within the WHiTE cohort, which will help to put into context the findings of future studies. We conclude that the patients within the WHiTE cohort are representative of the national population of older adults with hip fractures throughout England, Wales, and Northern Ireland. Cite this article: Bone Joint J 2019;101-B:708-714.

Entities:  

Keywords:  Hip fracture; National Hip Fracture Database; Prospective cohort

Mesh:

Year:  2019        PMID: 31154849     DOI: 10.1302/0301-620X.101B6.BJJ-2018-1623.R1

Source DB:  PubMed          Journal:  Bone Joint J        ISSN: 2049-4394            Impact factor:   5.082


  7 in total

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Authors:  Gulraj S Matharu; Anjali Shah; Samuel Hawley; Antony Johansen; Dominic Inman; Iain Moppett; Michael R Whitehouse; Andrew Judge
Journal:  BMC Med       Date:  2022-09-26       Impact factor: 11.150

2.  Utilization and costs of formal and informal care, home adaptations, and physiotherapy among older patients with hip fracture.

Authors:  M E Png; X L Griffin; M L Costa; J Achten; R Pinedo-Villanueva
Journal:  Bone Joint Res       Date:  2020-06-08       Impact factor: 5.853

3.  Artificial Neural Network and Cox Regression Models for Predicting Mortality after Hip Fracture Surgery: A Population-Based Comparison.

Authors:  Cheng-Yen Chen; Yu-Fu Chen; Hong-Yaw Chen; Chen-Tsung Hung; Hon-Yi Shi
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4.  Timing of Surgery for Hip Fracture in Patients on Direct Oral Anti-coagulants: A Population-Based Cohort Study.

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5.  Complications following hip fracture: Results from the World Hip Trauma Evaluation cohort study.

Authors:  En Lin Goh; Robin G Lerner; Juul Achten; Nick Parsons; Xavier L Griffin; Professor Matthew L Costa
Journal:  Injury       Date:  2020-03-30       Impact factor: 2.586

6.  Baseline quality of life in people with hip fracture: results from the multicentre WHiTE cohort study.

Authors:  Nick R Parsons; Matthew L Costa; Juul Achten; Xavier L Griffin
Journal:  Bone Joint Res       Date:  2020-08-19       Impact factor: 5.853

7.  Does performance-based remuneration improve outcomes in the treatment of hip fracture?

Authors:  Xavier L Griffin; Juul Achten; Nick Parsons; Matt L Costa
Journal:  Bone Joint J       Date:  2021-05       Impact factor: 5.082

  7 in total

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