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Record W2043399608 · doi:10.2310/7070.2005.34609

Is Suction Drainage an Effective Means ofPreventing Hematoma in Thyroid Surgery? A Meta-Analysis

2005· review· en· W2043399608 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueThe Journal of Otolaryngology · 2005
Typereview
Languageen
FieldMedicine
TopicThyroid and Parathyroid Surgery
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineHematomaSuctionPostoperative hematomaSurgeryMeta-analysisOdds ratioThyroidectomyThyroidRandomized controlled trialConfidence intervalInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the efficacy of suction drainage in preventing postoperative hematoma formation in thyroid surgery. METHODS: We conducted a meta-analysis using only randomized controlled trials in which the incidence of post-thyroidectomy hematoma was compared directly in patients with and without suction drains (eight studies since 1980; N = 944). The odds ratio (OR) with respective confidence intervals (CIs) using the fixed effects model was reported. We used an OR < 1.0 as being in favour of treatment (ie, the use of suction drains). RESULTS: In our meta-analysis, there was no statistically significant difference between the rates of post-thyroidectomy hematoma whether or not suction drains were used when the results were combined using a fixed effects model (OR 1.04, 95% CI-1.93), with p = .90. In this comparison, a fixed effects model was used rather than a random effects model because there was no statistically significant heterogeneity (chi2 = 6.26, p = .28). CONCLUSIONS: We conclude that the use of suction drains in thyroid surgery to prevent postoperative hematoma is not evidence based.

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.

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)0.009
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.307
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0100.009
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.103
GPT teacher head0.380
Teacher spread0.277 · 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