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Record W4212846229 · doi:10.1097/gox.0000000000004127

The Effect of Hypothyroidism on Surgical Outcomes Postabdominoplasty: A Case-control Study

2022· article· en· W4212846229 on OpenAlexaff

Bibliographic record

VenuePlastic & Reconstructive Surgery Global Open · 2022
Typearticle
Languageen
FieldMedicine
TopicBody Contouring and Surgery
Canadian institutionsCegep de Saint JeromeMcGill University Health Centre
Fundersnot available
KeywordsMEDLINEDiseaseIncidence (geometry)ComplicationThyroidRetrospective cohort study

Abstract

fetched live from OpenAlex

Background: Hypothyroidism is common in surgical patients. The objective of this study is to determine the rate of short- and long-term complications after abdominoplasty for patients treated for hypothyroidism. Methods: This is a retrospective chart review that enrolled consecutive patients undergoing abdominoplasty across a 5-year period. Cases had a preoperative diagnosis of overt hypothyroidism requiring thyroid replacement therapy, whereas controls are without thyroid disease. Groups were matched by age, gender, comorbidity status (hypertension and diabetes), smoking, and center of surgery in a 3:1 ratio. Results: There was a total of 61 cases and 183 matched controls followed up for 18 months; most were women (n = 240, 98%) and between the ages of 31 and 45 years (n = 142, 58%). There were no significant differences between cases and controls in any of the sociodemographic and comorbidity status except for current BMI, which was higher for cases than the control ( P < 0.05). The proportions of all other infections (4.5% versus 1.6%), wound dehiscence (4.7% versus 0.8%), dermatitis (4.7% versus 1.6%), and necrosis (2.3% versus 0%), hematoma (4.7% versus 2.5%) and seroma (2.3% versus 1.6%) formation were higher in cases but not significant ( P > 0.05). LTCs were not statistically different across groups ( P > 0.05). Conclusion: This study did not find a significantly different higher risk of complications after abdominoplasty for patients treated for hypothyroidism.

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)0.003
metaresearch head score (Gemma)0.003
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 score0.037
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.277
Teacher spread0.262 · 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".

Quick stats

Citations2
Published2022
Admission routes1
Has abstractyes

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