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The Bone & Joint Journal
Vol. 104-B, Issue 8 | Pages 963 - 971
1 Aug 2022
Sun Z Liu W Liu H Li J Hu Y Tu B Wang W Fan C

Aims. Heterotopic ossification (HO) is a common complication after elbow trauma and can cause severe upper limb disability. Although multiple prognostic factors have been reported to be associated with the development of post-traumatic HO, no model has yet been able to combine these predictors more succinctly to convey prognostic information and medical measures to patients. Therefore, this study aimed to identify prognostic factors leading to the formation of HO after surgery for elbow trauma, and to establish and validate a nomogram to predict the probability of HO formation in such particular injuries. Methods. This multicentre case-control study comprised 200 patients with post-traumatic elbow HO and 229 patients who had elbow trauma but without HO formation between July 2019 and December 2020. Features possibly associated with HO formation were obtained. The least absolute shrinkage and selection operator regression model was used to optimize feature selection. Multivariable logistic regression analysis was applied to build the new nomogram: the Shanghai post-Traumatic Elbow Heterotopic Ossification Prediction model (STEHOP). STEHOP was validated by concordance index (C-index) and calibration plot. Internal validation was conducted using bootstrapping validation. Results. Male sex, obesity, open wound, dislocations, late definitive surgical treatment, and lack of use of non-steroidal anti-inflammatory drugs were identified as adverse predictors and incorporated to construct the STEHOP model. It displayed good discrimination with a C-index of 0.80 (95% confidence interval 0.75 to 0.84). A high C-index value of 0.77 could still be reached in the internal validation. The calibration plot showed good agreement between nomogram prediction and observed outcomes. Conclusion. The newly developed STEHOP model is a valid and convenient instrument to predict HO formation after surgery for elbow trauma. It could assist clinicians in counselling patients regarding treatment expectations and therapeutic choices. Cite this article: Bone Joint J 2022;104-B(8):963–971


The Bone & Joint Journal
Vol. 106-B, Issue 4 | Pages 412 - 418
1 Apr 2024
Alqarni AG Nightingale J Norrish A Gladman JRF Ollivere B

Aims

Frailty greatly increases the risk of adverse outcome of trauma in older people. Frailty detection tools appear to be unsuitable for use in traumatically injured older patients. We therefore aimed to develop a method for detecting frailty in older people sustaining trauma using routinely collected clinical data.

Methods

We analyzed prospectively collected registry data from 2,108 patients aged ≥ 65 years who were admitted to a single major trauma centre over five years (1 October 2015 to 31 July 2020). We divided the sample equally into two, creating derivation and validation samples. In the derivation sample, we performed univariate analyses followed by multivariate regression, starting with 27 clinical variables in the registry to predict Clinical Frailty Scale (CFS; range 1 to 9) scores. Bland-Altman analyses were performed in the validation cohort to evaluate any biases between the Nottingham Trauma Frailty Index (NTFI) and the CFS.


The Bone & Joint Journal
Vol. 103-B, Issue 1 | Pages 164 - 169
1 Jan 2021
O'Leary L Jayatilaka L Leader R Fountain J

Aims

Patients who sustain neck of femur fractures are at high risk of malnutrition. Our intention was to assess to what extent malnutrition was associated with worse patient outcomes.

Methods

A total of 1,199 patients with femoral neck fractures presented to a large UK teaching hospital over a three-year period. All patients had nutritional assessments performed using the Malnutrition Universal Screening Tool (MUST). Malnutrition risk was compared to mortality, length of hospital stay, and discharge destination using logistic regression. Adjustments were made for covariates to identify whether malnutrition risk independently affected these outcomes.