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Record W2954620149 · doi:10.1016/j.amsu.2019.07.004

Cost-effectiveness of current approaches in rectal surgery

2019· review· en· W2954620149 on OpenAlexaff
Khalid N. Alsowaina, Christopher M. Schlachta, Nawar A. Alkhamesi

Bibliographic record

VenueAnnals of Medicine and Surgery · 2019
Typereview
Languageen
FieldMedicine
TopicColorectal Cancer Surgical Treatments
Canadian institutionsWestern UniversityLondon Health Sciences Centre
Fundersnot available
KeywordsMedicineIntensive care medicineMEDLINEQuality of life (healthcare)Colorectal cancerCost effectivenessRandomized controlled trialSurgeryCancerRisk analysis (engineering)

Abstract

fetched live from OpenAlex

Colorectal cancer is ranked as the fourth malignant cause of mortality. With the tremendous revolution in the modern medical techniques, minimally invasive approaches have been incorporated into rectal surgery. The effectiveness of surgical procedures is usually measured by a combination of qualitative (quality of life) and quantitative (years of life) measures, while the costs should reflect the use of different resources that were involved in delivering the medical care and they are affected by several factors, including length of hospital stay. In this review, we provide an insight into the cost-effectiveness of the different types of rectal surgeries in order to present a systematic approach for future preferences. A comprehensive literature review using Medline (via PUBMED), Embase and Cochrane Central Register of clinical trials (via clinical trial.org) was performed. Minimally invasive rectal surgeries have considerable cost-effective properties that outweigh those of the open techniques in terms of earlier return to bowel function, lower morbidity rates, reduced pain, shorter length of hospital stay and the overall patients' quality of life although there was no difference in long-term oncological and survival outcomes. The paucity of currently available long-term oncologic, quality of life, and economic outcomes may limit an adequate comparison of robotic surgeries to other surgical techniques. It is therefore recommended to conduct focused studies to help balance the cost/benefit factors along with other technical considerations aimed at reducing the cost of robotic systems with subsequent improvement of their cost-effectiveness.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.878
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
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 head0.696
GPT teacher head0.492
Teacher spread0.204 · 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 designOther design
Domainnot available
GenreReview

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

Citations17
Published2019
Admission routes1
Has abstractyes

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