Evidence map›Paper›PMID 41251817›Full record

ArticleArchives of orthopaedic and trauma surgery2025

Development of a simple clinical score to estimate in-hospital adverse event risk after elective hip arthroplasty: a retrospective cohort study in a high-risk population.

Matthias Wolf, Dominik Papathanakis, Raphael Trefzer, Christian Merle, Tilman Walker, Julian Deisenhofer

Abstract read
In one paragraph

Article in Archives of orthopaedic and trauma surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Matthias WolfOrthopaedic University Hospital, University Hospital Heidelberg, Heidelberg, Germany. Matthias.Wolf@med.uni-heidelberg.de.
Dominik PapathanakisOrthopaedic University Hospital, University Hospital Heidelberg, Heidelberg, Germany.
Raphael TrefzerOrthopaedic University Hospital, University Hospital Heidelberg, Heidelberg, Germany.
Christian MerleOrthopädische Klinik Paulinenhilfe, Diakonie-Klinikum Stuttgart, Stuttgart, Germany.
Tilman WalkerOrthopaedic University Hospital, University Hospital Heidelberg, Heidelberg, Germany.
Julian DeisenhoferOrthopaedic University Hospital, University Hospital Heidelberg, Heidelberg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionPatients undergoing total hip arthroplasty (THA) in tertiary centres often present with complex comorbidities that increase the risk of perioperative adverse events (AE). While fast-track and outpatient protocols are expanding, reliable risk stratification tools tailored to high-risk European populations remain limited. This study aimed to (1) compare comorbidity burden in a high-risk population to national data, (2) determine incidence and risk factors for in-hospital AE and (3) develop a simple, pragmatic score to identify patients at elevated AE risk. MATERIALS AND

methodsWe retrospectively analyzed 4,101 elective primary THA cases from a German tertiary care centre (2010-2019). Comorbidity burden was quantified using the Elixhauser Comorbidities (EC) and benchmarked against national registry data (EPRD). Independent predictors of in-hospital AE were identified using multivariate logistic regression. These variables were then used to develop a pragmatic preoperative clinical risk score via LASSO regression, internally validated with 10-fold cross-validation and bootstrapping.

resultsCompared to the national registry, our cohort showed significantly higher rates of major comorbidities, including cardiac valvular disease, diabetes, and fluid/electrolyte disorders. The overall in-hospital AE rate was 2.6%. Six comorbidities-including pulmonary circulation disorders (OR 10.7, 95% CI: 3.6-31.8)-were independently associated with AE. The derived LASSO model demonstrated strong discrimination (AUC 0.80; 95% CI: 0.75-0.84) and calibration (Brier score 0.07). A cutoff score ≥ 2 identified patients with an AE rate of > 7%, while scores < 2 corresponded to an NPV of 0.99, supporting its utility in identifying low-risk patients for fast-track pathways.

conclusionsPatients treated in tertiary centres exhibit elevated comorbidity burden but maintain acceptable perioperative AE rate. A simple, validated clinical score can flag patients at substantially increased risk of in-hospital AE who may benefit from closer in-hospital surveillance and effectively identify low-risk candidates for fast-track THA pathways. Further external validation is warranted.

Indexed as

Arthroplasty, Replacement, HipElective Surgical ProceduresPostoperative ComplicationsAgedAged, 80 and overComorbidityFemaleGermanyHumansMaleMiddle AgedRetrospective StudiesRisk AssessmentRisk FactorsArthroplastyComorbidityHipPostoperative complicationsReplacementRisk assessment

Identifiers

PMID41251817
PMCPMC12627149

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.