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Bone & Joint Open
Vol. 2, Issue 5 | Pages 314 - 322
1 May 2021
Alcock H Moppett EA Moppett IK

Aims. Hip fracture is a common condition of the older, frailer person. This population is also at risk from SARS-CoV-2 infection. It is important to understand the impact of coexistent hip fracture and SARS-CoV-2 for informed decision-making at patient and service levels. Methods. We undertook a systematic review and meta-analysis of observational studies of older (> 60 years) people with fragility hip fractures and outcomes with and without SARS-CoV-2 infection during the first wave of the COVID-19 pandemic. The primary outcome was early (30-day or in-hospital) mortality. Secondary outcomes included length of hospital stay and key clinical characteristics known to be associated with outcomes after hip fracture. Results. A total of 14 cohort and five case series studies were included (692 SARS-CoV-2 positive, 2,585 SARS-CoV-2 negative). SARS-CoV-2 infection was associated with an overall risk ratio (RR) for early mortality of 4.42 (95% confidence interval (CI) 3.42 to 5.82). Early mortality was 34% (95% CI 30% to 38%) and 9% (95% CI 8% to 10%) in the infected and noninfected groups respectively. Length of stay was increased in SARS-CoV-2 infected patients (mean difference (MD) 5.2 days (3.2 to 7.2)). Age (MD 1.6 years (0.3 to 2.9)); female sex (RR 0.83 (95% CI 0.65 to 1.05)); admission from home (RR 0.51 (95% CI 0.26 to 1.00)); presence of dementia (RR 1.13 (95% CI 0.94 to 1.43)); and intracapsular fracture (RR 0.89 (95% CI 0.71 to 1.11)) were not associated with SARS-CoV-2 infection. There were statistically, but not clinically, significantly greater Nottingham Hip Fracture Scores in infected compared with non-infected patients (MD 0.7 (0.4 to 0.9)). Conclusion. SARS-CoV-2 infection is associated with worse outcomes after hip fracture. This is not explained by differences in patient characteristics. These data can be used to support informed decision-making and may help track the impact of widespread adoption of system-level and therapeutic changes in management of the COVID-19 pandemic. Cite this article: Bone Jt Open 2021;2(5):314–322


Bone & Joint Open
Vol. 2, Issue 12 | Pages 1017 - 1026
1 Dec 2021
Sadiq S Lipski C Hanif U Arshad F Chaudary M Chaudhry F

Aims

This study assessed the impact of COVID-19 on hip and distal femur fracture patient outcomes across three successive UK lockdown periods over one year.

Methods

A single-centre retrospective cohort study was performed at an acute NHS Trust. Hip and distal femur fracture patients admitted within the first month from each of the three starting dates of each national lockdown were included and compared to a control group in March 2019. Data were collected as per the best practice tariff outcomes including additional outcomes as required. Data collection included COVID-19 status, time to theatre, 30-day mortality, presence of acute kidney injury (AKI) and pneumonia, and do not attempt cardiopulmonary resuscitation (DNACPR) status. Data were analyzed using an independent-samples t-test or chi-squared test with Fisher’s exact test where applicable. A p-value of < 0.05 was considered statistically significant.


Bone & Joint Research
Vol. 6, Issue 9 | Pages 550 - 556
1 Sep 2017
Tsang C Boulton C Burgon V Johansen A Wakeman R Cromwell DA

Objectives

The National Hip Fracture Database (NHFD) publishes hospital-level risk-adjusted mortality rates following hip fracture surgery in England, Wales and Northern Ireland. The performance of the risk model used by the NHFD was compared with the widely-used Nottingham Hip Fracture Score.

Methods

Data from 94 hospitals on patients aged 60 to 110 who had hip fracture surgery between May 2013 and July 2013 were analysed. Data were linked to the Office for National Statistics (ONS) death register to calculate the 30-day mortality rate. Risk of death was predicted for each patient using the NHFD and Nottingham models in a development dataset using logistic regression to define the models’ coefficients. This was followed by testing the performance of these refined models in a second validation dataset.