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Record W1978446579 · doi:10.1002/nau.20081

Tension‐free vaginal tape: Do patients who fail to follow‐up have the same results as those who do?

2004· article· en· W1978446579 on OpenAlexaff
Vatché A. Minassian, Ahmed Al‐Badr, Dante Pascali, Danny Lovatsis, Harold P. Drutz

Bibliographic record

VenueNeurourology and Urodynamics · 2004
Typearticle
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsMedicineTension (geology)SurgeryComposite materialCompression (physics)

Abstract

fetched live from OpenAlex

AIMS: To compare success and complication rates of the Tension-free vaginal tape (TVT) between patients with good versus poor follow-up. MATERIALS AND METHODS: A prospective cohort study of 108 women undergoing a TVT procedure was conducted. Patients were seen postoperatively at 6 weeks, 3, 6, 12 months, and yearly thereafter. Patients were categorized as poor follow-up if this schedule was not adhered to. Those who were lost to follow-up at or after their 6-week visit were considered as having failed the procedure. RESULTS: Seventy-nine (73%) patients had good follow-up. Of the remaining 29 patients with poor follow-up, 12 (11%) could not be reached and 17 (16%) were contacted by phone. Reasons given for poor follow-up were: busy or live far from hospital (11), health problems (4), and dissatisfied from surgery (2). Perioperative complication rates were similar between the two groups (P = 0.16). When patients with complete loss to follow-up were analyzed as failures, subjective and objective cure rates were significantly higher in patients with good as opposed to poor follow-up: 92 and 95% versus 72 and 69%, respectively, (P = 0.006). CONCLUSIONS: Patients with poor follow-up probably have lower cure rates after TVT. It is important to follow postoperative patients closely. When reporting success rates, one has to account for all cases to produce realistic results.

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 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 score0.088
Threshold uncertainty score1.000

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 integrity0.0000.001
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 head0.009
GPT teacher head0.252
Teacher spread0.243 · 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

Citations5
Published2004
Admission routes1
Has abstractyes

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