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Record W145287968

Type I thyroplasty: risk stratification approach to inpatient versus outpatient postoperative management.

2010· article· en· W145287968 on OpenAlexaff
Xiao Zhao, Kathryn Roth, Kevin Fung

Bibliographic record

VenuePubMed · 2010
Typearticle
Languageen
FieldMedicine
TopicVoice and Speech Disorders
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineGynecology
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: type I thyroplasty is an effective and safe procedure for unilateral vocal fold paralysis and is shifting toward outpatient postoperative care. However, serious airway complications have been reported. OBJECTIVES: the aims of this study were to investigate whether risk stratification into inpatient/outpatient postoperative care reduces outpatient airway complications and to compare the cost-effectiveness and surgical outcomes of risk stratification to a historical inpatient control group (non-risk stratified). SETTING: tertiary, university-based medical centre. DESIGN AND RESULTS: Three retrospective groups were examined: historical inpatient control (n = 15), risk-stratified (RS)- inpatient (n = 16), and RS outpatient (n = 17). Laryngeal edema was encountered in two historical controls (13.3%), two RS inpatients (12.5%), and one RS outpatient (5.9%). One case of implant extrusion occurred in the RS outpatient group. There was no difference in maximum phonation time or voice-related quality of life between RS versus historical controls (p > .5). The cost savings of risk stratification versus entirely inpatient care was $CAD 633.12/patient. The average duration in hospital for RS inpatient versus RS outpatient was 29.8 and 8.3 hours, respectively. CONCLUSIONS: postoperative RS may reduce potentially serious outpatient airway complications and cost while improving patient satisfaction.

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)0.006
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 score0.001
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
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)0.0010.000

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 head0.024
GPT teacher head0.245
Teacher spread0.221 · 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

Citations15
Published2010
Admission routes1
Has abstractyes

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