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The Bone & Joint Journal
Vol. 106-B, Issue 6 | Pages 573 - 581
1 Jun 2024
van Houtert WFC Strijbos DO Bimmel R Krijnen WP Jager J van Meeteren NLU van der Sluis G

Aims

To investigate the impact of consecutive perioperative care transitions on in-hospital recovery of patients who had primary total knee arthroplasty (TKA) over an 11-year period.

Methods

This observational cohort study used electronic health record data from all patients undergoing preoperative screening for primary TKA at a Northern Netherlands hospital between 2009 and 2020. In this timeframe, three perioperative care transitions were divided into four periods: Baseline care (Joint Care, n = 171; May 2009 to August 2010), Function-tailored (n = 404; September 2010 to October 2013), Fast-track (n = 721; November 2013 to May 2018), and Prehabilitation (n = 601; June 2018 to December 2020). In-hospital recovery was measured using inpatient recovery of activities (IROA), length of stay (LOS), and discharge to preoperative living situation (PLS). Multivariable regression models were used to analyze the impact of each perioperative care transition on in-hospital recovery.


Aims

Delirium is associated with adverse outcomes following hip fracture, but the prevalence and significance of delirium for the prognosis and ongoing rehabilitation needs of patients admitted from home is less well studied. Here, we analyzed relationships between delirium in patients admitted from home with 1) mortality; 2) total length of hospital stay; 3) need for post-acute inpatient rehabilitation; and 4) hospital readmission within 180 days.

Methods

This observational study used routine clinical data in a consecutive sample of hip fracture patients aged ≥ 50 years admitted to a single large trauma centre during the COVID-19 pandemic between 1 March 2020 and 30 November 2021. Delirium was prospectively assessed as part of routine care by the 4 A’s Test (4AT), with most assessments performed in the emergency department. Associations were determined using logistic regression adjusted for age, sex, Scottish Index of Multiple Deprivation quintile, COVID-19 infection within 30 days, and American Society of Anesthesiologists grade.


The Bone & Joint Journal
Vol. 104-B, Issue 4 | Pages 486 - 494
4 Apr 2022
Liu W Sun Z Xiong H Liu J Lu J Cai B Wang W Fan C

Aims. The aim of this study was to develop and internally validate a prognostic nomogram to predict the probability of gaining a functional range of motion (ROM ≥ 120°) after open arthrolysis of the elbow in patients with post-traumatic stiffness of the elbow. Methods. We developed the Shanghai Prediction Model for Elbow Stiffness Surgical Outcome (SPESSO) based on a dataset of 551 patients who underwent open arthrolysis of the elbow in four institutions. Demographic and clinical characteristics were collected from medical records. The least absolute shrinkage and selection operator regression model was used to optimize the selection of relevant features. Multivariable logistic regression analysis was used to build the SPESSO. Its prediction performance was evaluated using the concordance index (C-index) and a calibration graph. Internal validation was conducted using bootstrapping validation. Results. BMI, the duration of stiffness, the preoperative ROM, the preoperative intensity of pain, and grade of post-traumatic osteoarthritis of the elbow were identified as predictors of outcome and incorporated to construct the nomogram. SPESSO displayed good discrimination with a C-index of 0.73 (95% confidence interval 0.64 to 0.81). A high C-index value of 0.70 could still be reached in the interval validation. The calibration graph showed good agreement between the nomogram prediction and the outcome. Conclusion. The newly developed SPESSO is a valid and convenient model which can be used to predict the outcome of open arthrolysis of the elbow. It could assist clinicians in counselling patients regarding the choice and expectations of treatment. Cite this article: Bone Joint J 2022;104-B(4):486–494


Bone & Joint Open
Vol. 1, Issue 6 | Pages 175 - 181
2 Jun 2020
Musowoya RM Kaonga P Bwanga A Chunda-Lyoka C Lavy C Munthali J

Aims

Sickle cell disease (SCD) is an autosomal recessive inherited condition that presents with a number of clinical manifestations that include musculoskeletal manifestations (MM). MM may present differently in different individuals and settings and the predictors are not well known. Herein, we aimed at determining the predictors of MM in patients with SCD at the University Teaching Hospital, Lusaka, Zambia.

Methods

An unmatched case-control study was conducted between January and May 2019 in children below the age of 16 years. In all, 57 cases and 114 controls were obtained by systematic sampling method. A structured questionnaire was used to collect data. The different MM were identified, staged, and classified according to the Standard Orthopaedic Classification Systems using radiological and laboratory investigations. The data was entered in Epidata version 3.1 and exported to STATA 15 for analysis. Multiple logistic regression was used to determine predictors and predictive margins were used to determine the probability of MM.