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Record W4293529843 · doi:10.1016/j.ijsu.2022.106859

Time to revamp forensic medicine specialty in conflict Arab region

2022· letter· en· W4293529843 on OpenAlexaboutno aff
Sarya Swed, Mohammed Amir Rais, Abdelmonem Siddiq, Sheikh Shoib

Bibliographic record

VenueInternational Journal of Surgery · 2022
Typeletter
Languageen
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsnot available
Fundersnot available
KeywordsCosmesisMedicineCapsular contractureMastectomyImplantBreast reconstructionBreast cancerSurgeryRandomized controlled trialCohort studyProspective cohort studyCohortSpecialtyImplant failureInternal medicineCancerPathology

Abstract

fetched live from OpenAlex

There is no consensus on the timing of postmastectomy radiotherapy (PMRT) in relation to the exchange procedure in breast cancer patients undergoing the immediate two-stage prosthetic breast reconstruction. This meta-analysis investigated the reconstruction failure, complications, and cosmesis between PMRT to the tissue expander (TE) and PMRT to the permanent implant (PI).A literature search was conducted in PubMed and Embase databases until February 2022. Studies presenting at least one aspect relating to reconstruction failure, complications, and cosmesis between two cohorts were included. Newcastle-Ottawa Scale (NOS) was used to assess the risk of bias in included studies.Eleven studies presenting 1447 patients were enrolled. Three studies were prospective controlled research. The risk for implant loss was higher in PMRT to TE cohort (RR 1.75; 95% CI, 1.03 to 2.98; p = 0.04); meanwhile, the PMRT to TE cohort had a significantly lower risk of capsular contracture (RR 0.47; 95% CI, 0.29 to 0.78; p = 0.003). However, the synthesized result should be interpreted sensibly due to heterogeneity in statistical methods and definitions.Delivering PMRT to PI may reduce the risk of implant loss, while delivering PMRT to TE can reduce the risk of severe capsular contracture. More high-quality studies are warranted for the refinement of clinical practice.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.058
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.031
GPT teacher head0.257
Teacher spread0.225 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations1
Published2022
Admission routes1
Has abstractyes

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