A Meta-Analysis of Endoscopic vs. Microscopic Transsphenoidal Surgery for Non-functioning and Functioning Pituitary Adenomas: Comparisons of Efficacy and Safety
Bibliographic record
Abstract
Background: Although microscopic (MTSS) and endoscopic transsphenoidal surgery (ETSS) are both effective approaches for treating non-functioning pituitary adenomas (NFPA) and functioning pituitary adenomas (FPA), the consensus remains unidentified on whether there are differences in the risk of postoperative complications between the two surgical approaches. Method: A meta-analysis of the study of MTSS vs. ETSS for NFPA and FPA was conducted by searching the electronic databases of PubMed, Cochrane Library, and EMBASE, from the date of establishment of electronic databases to September 2020 based on the PRISMA guidelines. Results: In this study, a total of 16 studies were selected, hailing from Belgium, the USA, India, Finland, France, Korea, Spain, China, and Canada. We enrolled 1003 patients in the ETSS and 992 patients in the MTSS group. In patients with NFPA, the ETSS group was related to a higher incidence of post-operative gross-total resection (GTR). (OR = 1.655, 95% CI 1.131–2.421, P = 0.010). In participants with FPA, the results illustrated that the ETSS group had higher rates of visual improvement (OR = 2.461, 95% CI 1.109–5.459) and gross-total resection (OR = 2.033, 95% CI 1.335–3.096), as well as lower meningitis rates (OR = 0.195, 95% CI 0.041–1.923). In participants with acromegaly, no significant difference was shown in the postoperative complications. Conclusion: Based on current evidence, participants with NFPA treated by endoscopy were related to higher rates of GTR; patients with FPA treated by ETSS were related to higher rates of visual improvement and GTR, as well as a lower rates of meningitis.
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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 | 0.018 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.055 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 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".