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Impact of Atopic Dermatitis (Eczema) and Its Treatment on the Risk of Adverse Events Following Total Knee Arthroplasty

2024· article· en· W4403637641 on OpenAlexaff
Julian Smith-Voudouris, Meera M. Dhodapkar, Scott J. Halperin, Jeffrey M. Cohen, Jonathan N. Grauer

Bibliographic record

VenueJAAOS Global Research and Reviews · 2024
Typearticle
Languageen
FieldMedicine
TopicDermatology and Skin Diseases
Canadian institutionsSmiths Detection (Canada)
FundersNational Center for Advancing Translational SciencesYale University
KeywordsMedicineAtopic dermatitisOdds ratioAdverse effectPneumoniaInternal medicineComorbidityPerioperativeEmergency departmentCellulitisSurgeryDermatology

Abstract

fetched live from OpenAlex

BACKGROUND: Atopic dermatitis (AD), also known as eczema, is a highly prevalent, chronic inflammatory skin condition. The perioperative outcomes of patients with AD after total knee arthroplasty (TKA) have not been characterized. METHODS: Adult patients who underwent TKA were identified in the PearlDiver administrative database. After matching based on patient characteristics, 90-day adverse events and 5-year revisions were compared by multivariable analyses and log-rank tests, respectively. Patients with atopic dermatitis were then stratified by medication status for repeated analysis between resultant subcohorts. RESULTS: Relative to age, sex, and comorbidity matched patients without AD, those with AD had increased odds of aggregated adverse events (OR = 1.36), pneumonia (OR = 2.07), urinary tract infection (UTI, OR = 1.77), and emergency department (ED) visits (OR = 1.70) (P < 0.0001 for each). Those on medication for moderate-to-severe disease had similar associations as the primary analysis. Those not on medications were similar, but not found to have elevated odds of pneumonia. 5-year revisions were not markedly different. CONCLUSION: TKA patients with AD were at increased odds of pneumonia, UTI, and ED visits, but these risks were not exacerbated by immunosuppressive medications. Surgeons who are managing patients with AD for TKA should be vigilant but reassured by overall similar 5-year survival to revision.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.075
Threshold uncertainty score0.219

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.056
GPT teacher head0.408
Teacher spread0.353 · 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.

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

Citations2
Published2024
Admission routes1
Has abstractyes

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