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Record W3101918103 · doi:10.1097/gox.0000000000003179

Comparing the Clinical and Cost-Effectiveness of Abdominal-based Autogenous Tissue and Tissue-Expander Implant: A Feasibility Study

2020· article· en· W3101918103 on OpenAlexaff
Ronen Avram, Arianna Dal Cin, Jessica Murphy, Eric Duku, Feng Xie

Bibliographic record

VenuePlastic & Reconstructive Surgery Global Open · 2020
Typearticle
Languageen
FieldMedicine
TopicAortic aneurysm repair treatments
Canadian institutionsMcMaster UniversityImpact
Fundersnot available
KeywordsMedicineQuality of life (healthcare)CohortImplantCohort studySurgeryPhysical therapyNursingInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: To determine the superiority of autologous abdominal tissue (AAT) or tissue-expander implant (TE/I) reconstruction, a robust comparative cohort study is required. This study sought to determine the feasibility of a future large pragmatic cohort study comparing clinical and cost-effectiveness of AAT and TE/I at 12 months postoperative. METHODS: Potential participants were screened during consultation with their surgeon. Three health-related quality-of-life scales, the Health Utility Index Mark 3, the 12-Item Short Form Health Survey, and the BREAST-Q were used preoperatively, 1, 6, and 12 months postoperatively. Direct medical costs and postoperative patient/caregiver productivity loss were collected using patient diaries. Feasibility was assessed through patient recruitment rates and compliance of patients and study staff to complete required study documentation. RESULTS: Sixty-three patients consented to participate, 44 completed baseline questionnaires; the feasibility objective of recruiting 80% of eligible patients was not met. A 90% completion rate for patient questionnaires was seen at 1-month follow-up and decreased up to 12 months. Quality-adjusted life years were calculated at 0.77 and 0.89 for the AAT and TE/I group, respectively. Case report form completion by study staff and patient diary completion was moderate and low, respectively. Collaborating with hospital case-costing specialists to identify direct medical costs was reliable and efficient. CONCLUSIONS: A future large-scale study is feasible. However, due to a diminishing rate of questionnaire completion, almost twice as many patients need to be recruited than expected to have adequate power. Cost data collection from hospital sources was reliable. Case report forms need to be tailored more toward a busy hospital setting.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.015
Threshold uncertainty score0.852

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.128
GPT teacher head0.394
Teacher spread0.266 · 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

Citations3
Published2020
Admission routes1
Has abstractyes

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