Outcomes of transanal tube placement in anterior resection: A meta-analysis and systematic review
Bibliographic record
Abstract
BACKGROUND: In recent years, transanal tube placement was reported to be an effective procedure preventing anastomotic leakage after anterior resection of rectal cancer. However, this procedure is still controversial owing to inconsistent results found in previous studies. METHODS: A comprehensive literature search was performed using Pubmed, Embase, Cochrane library from the databases inception up until June 21, 2018. The methodological quality of randomized controlled trials and cohort studies were evaluated by Cochrane Collaboration's tool for assessing risk of bias and Newcastle-Ottawa Scale, respectively. Statistical analysis was performed using the RevMan 5.3 software. RESULTS: 1 randomized controlled trial and 9 cohort studies were included in our meta-analysis. The randomized controlled trial was proven to be low risk according to the Cochrane Collaboration's tool for assessing risk of bias. All of the cohort studies proved a high quality according to the Newcastle-Ottawa Scale. Patients in transanal tube group had more disadvantageous preoperative demographic characteristics than patients in non-transanal tube group. The anastomotic leak rate was lower in the transanal tube group. Patients in the transanal tube group tended to have lower reoperation rates and shorter hospital stays compared with patients in the non-transanal tube group. CONCLUSION: Despite various unfavorable preoperative characteristics, anastomotic leakage after anterior resection was lower in patients who received transanal tube placement compared with the control group. Transanal tube placement may be an alternative procedure of defunctioning stoma. A large sample size, multicenter RCT was needed to prove our results.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.038 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".