Low-grade Chronic Inflammation and Vascular Damage in Patients with Rheumatoid Arthritis: Don’t Forget “Metabolic Inflammation”
Bibliographic record
Abstract
Abstract BACKGROUND Laparoscopy-assisted trans-anal TME (ta-TME), or hybrid ta-TME, inherited the advantages of both trans-anal surgery and trans-abdominal surgery, and is gaining increasing acceptance from colorectal surgeons worldwide. This research aims to make a comprehensive comparison between hybrid ta-TME surgery and traditional laparoscopic TME (la-TME) surgery regarding surgical quality and long-term survival. METHODS Cochrane Library, EMbase, Web of Science and PubMed were searched for studies comparing hybrid ta-TME with traditional la-TME. Indicators for surgical quality and long-term prognosis were extracted and pooled. Heterogeneity was assessed with I2 index and was significant when p < 0.1 and I2 > 50%. Publication bias was estimated by Egger’s test, where p<0.1 was considered statistically significant. RESULTS 13 studies with 992 patients were included in meta-analysis, of which 467 were in hybrid ta-TME cohorts, and 525 were in traditional la-TME cohorts. Compared with traditional la-TME, hybrid ta-TME has lower rate of positive circumferential margin (RR=0.454, 95%CI 0.240~0.862, p=0.016) and lower conversion rate (RR=0.336, 95%CI 0.134~0.844, p=0.020). On rate of positive distal resection margin, completeness/near-completeness of meso-rectum, overall complications, anal leakage, ileus, urinary dysfunction, 2-year DFS and 2-year OS, there were no significant difference between the two techniques. CONCLUSIONS Hybrid ta-TME is significantly superior to traditional la-TME in ensuring CRM safety and lowering intra-operative conversion rate, and is meanwhile not inferior on other major outcome indicators concerning surgical quality and long-term survival. To further understand this new surgical technique, we need high-quality RCTs, as well as previous researchers’ updates with results of prolonged follow-up.
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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 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".