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Record W4415439224 · doi:10.1302/1358-992x.2025.10.094

PREDICTORS OF SUCCESSFUL SAME-DAY DISCHARGE FOLLOWING PRIMARY HIP AND KNEE ARTHROPLASTY

2025· article· en· W4415439224 on OpenAlexaboutno aff
Bheeshma Ravi, David W. Pincus, Sebastian Tomescu, Johnathan R. Lex, Seper Ekhtiari

Bibliographic record

VenueOrthopaedic Proceedings · 2025
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)ArthroplastyCohortHip arthroplastyRetrospective cohort studyTotal knee arthroplastyCohort studyOrthopedic surgery

Abstract

fetched live from OpenAlex

Advances in anaesthetic technology and orthopaedic practice are enabling same day discharge (SDD) following total hip and knee arthroplasty (THA and TKA). SDD is also an appealing strategy for resource constrained health systems to facilitate THA and TKA for increasing numbers of patients disabled by endstage hip and knee arthritis. Previous research of SDD has aimed to identify suitable patients for this endeavour, but no consensus is available regarding demographics, comorbidities or preoperative scoring systems. One limitation of prior research is that data derives from single ‘centres of excellence’ which may not be generalisable, particularly to smaller hospitals across a large health care system. In this context our goals were two-fold: 1) Assess the safety of SDD across all centres performing THA and TKA in Ontario and 2) Identify patient, surgeon and institutional variables that were significantly associated with failure of SDD. We conducted a population-based, retrospective cohort study of all patients undergoing primary THA and TKA in Ontario between 2016 to 2021. Data was extracted from the ICES database and previously validated algorithms were utilised to identify patients, covariates and outcomes. Inclusion criteria included patients undergoing primary total hip or knee arthroplasty treated by all surgeons and hospitals in Ontario. We excluded revision arthroplasties and other arthroplasty operations (ex. partial knee replacements). “Failure” of SDD was defined as the inability to discharge the patient on the same day / admission to hospital following originally planned SDD. Of 58,120 THAs completed between 2016 and 2021, 3,380 patients were planned for SDD. There were no differences in medical complications (DVT/PE, MI, pneumonia) between those planned SDD versus inpatients. The proportion of patients planned for SDD increased from 0.5% in 2016 to 33% in 2021. Of those planned for SDD, 2981 (88.4%) were successful and 393 (11.6%) failed/could not be discharged the same day. Predictors for failure were Charlson index (p=0.042), obesity (p=0.002), female gender (p<0.001), PUD (p=0.011), frailty (p<0.002), hypertension (p=0.022), use of general anaesthetic (p<0.001) and surgical complications (p=0.006). Of 82,646 TKAs completed between 2016 and 2021, 2,776 patients were planned for SDD. Similar to THA, there were no differences in medical complications (DVT/PE, MI, pneumonia) or mortality within 30 days between those planned SDD versus inpatients following TKA. The proportion of patients planned for SDD increased from 0% in 2016 to 27% in 2021. Of those planned for SDD, 2462 (88.7%) were successful and 314 (11.3%) failed. Once again predictors of failure included Charlson index (p=0.037), frailty (p<0.01), female gender (p=0.019) and use of general anaesthetic (p<0.001). Interestingly for both THAs and TKAs, those with successful SDD were more likely to have an unplanned ED visit within 30 days of surgery (p<0.001). SDD following THA and TKA in Ontario increased from <1% in 2016 to nearly a third of patients in 2021. The early experience of SDD following these procedures in Ontario appears to be safe without and increased risk of medical complications and mortality compared to inpatients. Failure of SDD only occurred in about 10% of patients. Our findings that female gender, obesity, medical comorbidity and general anaesthetic delaying discharge can be helpful in planning for SDD success. Interestingly, the increased ED admission in those with successful SDD suggests a failure to detect early complications, negate patient anxieties or deal with conditions suitable for primary care and is an area for improvement going forward. Future research should assess low fidelity testing including clinical examination findings to help predict SDD success.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.233
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes1
Has abstractyes

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