Dataset Information

Development and Validation of Multivariable Prediction Models for In-Hospital Death, 30-Day Death, and Change in Residence After Hip Fracture Surgery and the "Stratify-Hip" Algorithm.

ABSTRACT:

Background

To develop and validate the stratify-hip algorithm (multivariable prediction models to predict those at low, medium, and high risk across in-hospital death, 30-day death, and residence change after hip fracture).

Methods

Multivariable Fine-Gray and logistic regression of audit data linked to hospital records for older adults surgically treated for hip fracture in England/Wales 2011-14 (development n = 170 411) and 2015-16 (external validation, n = 90 102). Outcomes included time to in-hospital death, death at 30 days, and time to residence change. Predictors included age, sex, pre-fracture mobility, dementia, and pre-fracture residence (not for residence change). Model assumptions, performance, and sensitivity to missingness were assessed. Models were incorporated into the stratify-hip algorithm assigning patients to overall low (low risk across outcomes), medium (low death risk, medium/high risk of residence change), or high (high risk of in-hospital death, high/medium risk of 30-day death) risk.

Results

For complete-case analysis, 6 780 of 141 158 patients (4.8%) died in-hospital, 8 693 of 149 258 patients (5.8%) died by 30 days, and 4 461 of 119 420 patients (3.7%) had residence change. Models demonstrated acceptable calibration (observed:expected ratio 0.90, 0.99, and 0.94), and discrimination (area under curve 73.1, 71.1, and 71.5; Brier score 5.7, 5.3, and 5.6) for in-hospital death, 30-day death, and residence change, respectively. Overall, 31%, 28%, and 41% of patients were assigned to overall low, medium, and high risk. External validation and missing data analyses elicited similar findings. The algorithm is available at https://stratifyhip.co.uk.

Conclusions

The current study developed and validated the stratify-hip algorithm as a new tool to risk stratify patients after hip fracture.

SUBMITTER: Goubar A

PROVIDER: S-EPMC10460557 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature

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Publications

Development and Validation of Multivariable Prediction Models for In-Hospital Death, 30-Day Death, and Change in Residence After Hip Fracture Surgery and the "Stratify-Hip" Algorithm.

Goubar Aicha A Martin Finbarr C FC Sackley Catherine C Foster Nadine E NE Ayis Salma S Gregson Celia L CL Cameron Ian D ID Walsh Nicola E NE Sheehan Katie J KJ

The journals of gerontology. Series A, Biological sciences and medical sciences 20230801 9

<h4>Background</h4>To develop and validate the stratify-hip algorithm (multivariable prediction models to predict those at low, medium, and high risk across in-hospital death, 30-day death, and residence change after hip fracture).<h4>Methods</h4>Multivariable Fine-Gray and logistic regression of audit data linked to hospital records for older adults surgically treated for hip fracture in England/Wales 2011-14 (development n = 170 411) and 2015-16 (external validation, n = 90 102). Outcomes incl ...[more]

PMID: 36754375

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Project description:PurposeThe 30-day mortality rate after hip fracture surgery has been considered as an indirect indicator of the quality of care. The aim of this work is to analyse preoperative and postoperative factors potentially related to early 30-day mortality in patients over 65 undergoing hip fracture surgery.MethodsProspective cohort study including all consecutive primary hip fracture patients over 65 admitted to Trauma and Orthopaedics department from January 1, 2018 to December 31, 2019. Bed-ridden, non- surgically treated patients, and high energy trauma or tumoral aetiology fractures were excluded. A total of 943 patients were eligible (attrition rate: 2.1%). Follow-up included 30-days after discharge. We noted the 30-day mortality after hip fracture surgery, analysing 130 potentially related variables including biodemographic, fracture-related, preoperative, and postoperative clinical factors. Qualitative variables were assessed by χ2, and quantitative variables by non-parametric tests. Odds ratio determined by binary logistic regression. We selected preventable candidate variables for multivariate risk assessment by logistic regression.ResultsA total of 923 patients were enrolled (mean age 86.22±6.8, 72.9% women). The 30-day mortality rate was 6.0%. We noted significant increased mortality on men (OR = 2.381[1.371-4.136], p = 0.002), ageing patients (ORyear = 1.073[1.025-1.122], p = 0.002), and longer time to surgery (ORday = 1.183[1.039-1146], p<0.001), on other 20 preoperative clinical variables, like lymphopenia (lymphocyte count <103/μl, OR = 1.842[1.063-3.191], p = 0.029), hypoalbuminemia (≤3.5g/dl, OR = 2.474[1.316-4.643], p = 0.005), and oral anticoagulant intake (OR = 2.499[1.415-4.415], p = 0.002), and on 25 postoperative clinical variables, like arrhythmia (OR = 13.937[6.263-31.017], p<0.001), respiratory insufficiency (OR = 7.002[3.947-12.419], p<0.001), hyperkalaemia (OR = 10.378[3.909-27.555], p<0.001), nutritional supply requirement (OR = 3.576[1.894-6.752], p = 0.021), or early arthroplasty dislocation (OR = 6.557[1.206-35.640], p = 0.029). We developed a predictive model for early mortality after hip fracture surgery based on postoperative factors with 96.0% sensitivity and 60.7% specificity (AUC = 0.863).ConclusionWe revealed that not only preoperative, but also postoperative factors have a great impact after hip fracture surgery. The influence of post-operative factors on 30-day mortality has a logical basis, albeit so far they have not been identified or quantified before. Our results provide an advantageous picture of the 30-day mortality after hip fracture surgery.

Project description:Importance:Although wait times for hip fracture surgery have been linked to mortality and are being used as quality-of-care indicators worldwide, controversy exists about the duration of the wait that leads to complications. Objective:To use population-based wait-time data to identify the optimal time window in which to conduct hip fracture surgery before the risk of complications increases. Design, Setting, and Participants:Population-based, retrospective cohort study of adults undergoing hip fracture surgery between April 1, 2009, and March 31, 2014, at 72 hospitals in Ontario, Canada. Risk-adjusted restricted cubic splines modeled the probability of each complication according to wait time. The inflection point (in hours) when complications began to increase was used to define early and delayed surgery. To evaluate the robustness of this definition, outcomes among propensity-score matched early and delayed surgical patients were compared using percent absolute risk differences (RDs, with 95% CIs). Exposure:Time elapsed from hospital arrival to surgery (in hours). Main Outcomes and Measures:Mortality within 30 days. Secondary outcomes included a composite of mortality or other medical complications (myocardial infarction, deep vein thrombosis, pulmonary embolism, and pneumonia). Results:Among 42 230 patients with hip fracture (mean [SD] age, 80.1 years [10.7], 70.5% women) who met study entry criteria, overall mortality at 30 days was 7.0%. The risk of complications increased when wait times were greater than 24 hours, irrespective of the complication considered. Compared with 13 731 propensity-score matched patients who received surgery earlier, 13 731 patients who received surgery after 24 hours had a significantly higher risk of 30-day mortality (898 [6.5%] vs 790 [5.8%]; % absolute RD, 0.79; 95% CI, 0.23-1.35) and the composite outcome (1680 [12.2%]) vs 1383 [10.1%]; % absolute RD, 2.16; 95% CI, 1.43-2.89). Conclusions and Relevance:Among adults undergoing hip fracture surgery, increased wait time was associated with a greater risk of 30-day mortality and other complications. A wait time of 24 hours may represent a threshold defining higher risk.

Project description:AimsThe aim of this study to compare 30-day survival and recovery of mobility between patients mobilized early (on the day of, or day after surgery for a hip fracture) and patients mobilized late (two days or more after surgery), and to determine whether the presence of dementia influences the association between the timing of mobilization, 30-day survival, and recovery.MethodsAnalysis of the National Hip Fracture Database and hospital records for 126,897 patients aged ≥ 60 years who underwent surgery for a hip fracture in England and Wales between 2014 and 2016. Using logistic regression, we adjusted for covariates with a propensity score to estimate the association between the timing of mobilization, survival, and recovery of walking ability.ResultsA total of 99,667 patients (79%) mobilized early. Among those mobilized early compared to those mobilized late, the weighted odds ratio of survival was 1.92 (95% confidence interval (CI) 1.80 to 2.05), of recovering outdoor ambulation was 1.25 (95% CI 1.03 to 1.51), and of recovering indoor ambulation was 1.53 (95% CI 1.32 to 1.78) by 30 days. The weighted probabilities of survival at 30 days post-admission were 95.9% (95% CI 95.7% to 96.0%) for those who mobilized early and 92.4% (95% CI 92.0% to 92.8%) for those who mobilized late. The weighted probabilities of regaining the ability to walk outdoors were 9.7% (95% CI 9.2% to 10.2%) and indoors 81.2% (95% CI 80.0% to 82.4%), for those who mobilized early, and 7.9% (95% CI 6.6% to 9.2%) and 73.8% (95% CI 71.3% to 76.2%), respectively, for those who mobilized late. Patients with dementia were less likely to mobilize early despite observed associations with survival and ambulation recovery for those with and without dementia.ConclusionEarly mobilization is associated with survival and recovery for patients (with and without dementia) after hip fracture. Early mobilization should be incorporated as a measured indicator of quality. Reasons for failure to mobilize early should also be recorded to inform quality improvement initiatives. Cite this article: Bone Joint J 2021;103-B(7):1317-1324.

Project description:BackgroundRecent publications indicate increased mortality in patients admitted to hospital at the weekend, but these findings may be subject to inadequate adjustment for case-mix and the complexities of resource provision. Hip fractures generally occur in a frail comorbid population with a consistent diagnosis precipitating admission as an emergency. We therefore aimed to examine the association between the day of the week of milestones in the care pathway and 30-day mortality in this population.MethodsUsing data from a prospective national database of hip fractures, we investigated the association between day of the week of admission, surgery, inpatient stay, and discharge (care pathway milestones) and 30-day mortality using generalised linear models. Data was collected between January 1, 2011, and December 31, 2014, on 241,446 patients. An incremental case-mix adjustment strategy was performed using patient characteristics, non-surgical interventions, surgical interventions and discharge characteristics.ResultsThe day of admission was not associated with 30-day mortality. Sunday surgery (OR, 1.094; 95% CI, 1.043-1.148; P < 0.0001) and a delay to surgery of more than 24-hours (OR, 1.094; 95% CI, 1.059, 1.130; P < 0.0001) were both associated with a 9.4% increase in 30-day mortality. Discharge from the hospital on a Sunday (OR, 1.515; 95% CI, 1.224, 1.844; P < 0.0001) or out-of-hours discharge (OR, 1.174; 95% CI, 1.081, 1.276; P < 0.0001) were associated with a 51.5% and 17.4% increase in 30-day mortality, respectively. Mortality during the inpatient stay was 5.6% lower (IRR, 0.944; 95% CI, 0.909, 0.980; P = 0.003) at the weekend compared to weekdays.ConclusionsThere is limited evidence of a generalised weekend effect in patients admitted to hospital for hip fracture. Optimising resource utilisation is an essential element of planning and delivering healthcare services. Interventions that lead to surgery within 24-hours of admission are justified. Factors such as Sunday operations, discharge and out-of-hours discharge require further investigation.

Dataset Information

Development and Validation of Multivariable Prediction Models for In-Hospital Death, 30-Day Death, and Change in Residence After Hip Fracture Surgery and the "Stratify-Hip" Algorithm.

Background

Methods

Results

Conclusions

Publications

Development and Validation of Multivariable Prediction Models for In-Hospital Death, 30-Day Death, and Change in Residence After Hip Fracture Surgery and the "Stratify-Hip" Algorithm.

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