Laparoscopic bariatric surgery can be performed safely in secondary health care centres with a dedicated service corridor to an affiliated tertiary health care centre
Bibliographic record
Abstract
BACKGROUND: Canada needs to increase capacity for bariatric surgery to reduce the wait for this cost-effective, life-saving surgery. The aim of this study was to test whether laparoscopic bariatric surgery, including gastric bypass, can be delivered safely in secondary health care centres (SHCCs). METHODS: In this prospective cohort study, patients received bariatric surgery at an SHCC that had no intensive care unit but had a dedicated operating room and ward teams and a patient-monitoring environment. Patients with life-threatening complications were transferred to an affiliated tertiary health care centre (THCC) via a dedicated "service corridor." RESULTS: In all, 830 patients were treated: 676 at the SHCC and 154 at the THCC. Gastric bypass was performed in 85.4%, gastric band in 11.1% and gastric sleeve in 3.5%. The body mass index (BMI) was significantly higher in the THCC than the SHCC group (mean 54.4 [standard deviation (SD) 9.7] v. 47.5 [SD 7.4]). Obesity-associated diseases were similar between the groups. Major complications occurred in 2.6% of SHCC patients and 1.7% of THCC patients. Seven patients (1%) required direct transfer to the THCC, and all were treated successfully. There were 2 deaths (1.3%) in the THCC and none in the SHCC groups (combined mortality 0.2%). Weight loss was equivalent up to the fourth year of the study. CONCLUSION: With proper patient selection, a dedicated health care team and a service corridor to an affiliated THCC, laparoscopic bariatric surgery, including gastric bypass can be performed safely in SHCCs. Further study is needed to determine whether the model can be applied across Canada.
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 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".