MétaCan
Menu
Back to cohort
Record W6964124242 · doi:10.25384/sage.c.6313202.v1

A systematic review of clinical outcomes for outpatient vs. inpatient shoulder arthroplasty

2022· other· en· W6964124242 on OpenAlexaff

Bibliographic record

VenueSage Journals Data · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsMcMaster University
Fundersnot available
KeywordsArthroplastyCochrane LibraryMEDLINESystematic reviewShoulder surgeryOutpatient surgeryPatient satisfactionNarrative review

Abstract

fetched live from OpenAlex

BackgroundOutpatient shoulder arthroplasty is growing in popularity as a cost-effective and potentially equally safe alternative to inpatient arthroplasty. The aim of this study was to investigate literature relating to outpatient shoulder arthroplasty, looking at clinical outcomes, complications, readmission, and cost compared to inpatient arthroplasty.MethodsWe conducted a systematic review of Medline, Embase and Cochrane Library databases from inception to 6 April 2020. Methodological quality was assessed using MINORS and GRADE criteria.ResultsWe included 17 studies, with 11 included in meta-analyses and 6 in narrative review. A meta-analysis of hospital readmissions demonstrated no statistically significant difference between outpatient and inpatient cohorts (OR = 0.89, <i>p</i> = 0.49). Pooled post-operative complications identified decreased complications in those undergoing outpatient surgery (OR = 0.70, <i>p</i> = 0.02). Considerable cost saving of between $3614 and $53,202 (19.7–69.9%) per patient were present in the outpatient setting. Overall study quality was low and presented a serious risk of bias.DiscussionShoulder arthroplasty in the outpatient setting appears to be as safe as shoulder arthroplasty in the inpatient setting, with a significant reduction in cost. However, this is based on low quality evidence and high risk of bias suggests further research is needed to substantiate these findings.

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)0.012
metaresearch head score (Gemma)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.273
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0030.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0690.001

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 head0.149
GPT teacher head0.436
Teacher spread0.288 · 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 designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueSage Journals DataFrench-language works237,207