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Record W2748213717 · doi:10.2106/jbjs.16.00843

Factors Associated with Adverse Events in Inpatient Elective Spine, Knee, and Hip Orthopaedic Surgery

2017· article· en· W2748213717 on OpenAlexaff
Dov B. Millstone, Anthony V. Perruccio, Elizabeth M. Badley, Y. Raja Rampersaud

Bibliographic record

VenueJournal of Bone and Joint Surgery · 2017
Typearticle
Languageen
FieldHealth Professions
TopicPatient Safety and Medication Errors
Canadian institutionsToronto Western HospitalPublic Health OntarioUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineAdverse effectOdds ratioConfidence intervalOrthopedic surgeryLogistic regressionOsteoarthritisSpinal stenosisSurgeryPhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Orthopaedic procedures for degenerative musculoskeletal conditions (predominantly osteoarthritis and spinal stenosis) represent an increasing burden on the health-care system. These procedures are also associated with adverse event rates and related cost. The objective of this study was to identify risk factors for adverse events associated with orthopaedic surgeries as captured within a common clinical point-of-care system for documenting adverse events (Orthopaedic Surgical AdVerse Events Severity [OrthoSAVES] system). METHODS: In-hospital adverse events were recorded at the point of care over a 2-year period for inpatient elective knee, hip, and spine orthopaedic procedures for degenerative musculoskeletal conditions. Multivariable logistic regression was employed to investigate the association between various factors (age, sex, surgical site, body mass index, surgical risk classification, operative duration, length of stay, and medical comorbidities) and the occurrence of adverse events. RESULTS: The sample included 2,146 patients. The overall adverse event rate was 27% (571 of 2,146), and by surgical site, the rates were 29% (130 of 442) for spine; 27% (266 of 998) for knee; and 25% (175 of 706) for hip. The most common adverse events had a low severity grade, but spinal procedures demonstrated more adverse events with a severity grade of ≥3. Increasing age (odds ratio [OR] = 1.21, 95% confidence interval [CI] =1.05 to 1.41, per 15-year interval), male sex (OR = 1.43, 95% CI =1.16 to 1.77), increasing operative duration (OR = 1.13, 95% CI = 1.03 to 1.23, per 30-minute increase), length of stay (OR = 1.13, 95% CI = 1.10 to 1.17, per day), and undergoing revision surgery (OR = 2.23, 95% CI = 1.35 to 3.70) were independently associated with a greater likelihood of the occurrence of an adverse event. Spine surgery demonstrated decreased odds of an adverse event compared with knee surgery (OR = 0.38, 95% CI = 0.23 to 0.61) when operative duration and length of stay were taken into account. CONCLUSIONS: On the basis of our adjusted analysis, we found increasing age, male sex, revision surgery, length of stay, and increasing operative duration to be common independent risk factors for an adverse event across the population studied. The first 3 risk factors are not modifiable. The association between increasing operative duration and the risk of an adverse event across all anatomical regions and surgical procedures is a unique finding. However, modification of procedural efficiency is multifactorial and warrants further investigation. LEVEL OF EVIDENCE: Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.125
GPT teacher head0.352
Teacher spread0.227 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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".

Quick stats

Citations31
Published2017
Admission routes1
Has abstractyes

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