Neuroendoscopic Surgery versus Stereotactic Aspiration in the treatment of supratentorial intracerebral hemorrhage: a meta-analysis
Bibliographic record
Abstract
Abstract Background No consensus has been reached on the superiority between Neuroendoscopic Surgery (NS) versus Stereotactic Aspiration (SA) in the treatment of supratentorial intracerebral hemorrhage (ICH). Therefore, this study conducted in-depth analysis and aimed to evaluate the efficacy and safety of NS versus SA for supratentorial ICH. Methods We searched for the all-relevant studies systematically from English databases including PubMed, Embase, Web of Science and the Cochrane Library. Two independent researchers identified and selected these literatures that met the inclusion criteria. Then we evaluated the quality of these studies according to the Cochrane Collaboration’s risk of bias tool and the Newcastle-Ottawa Scale. RevMan 5.4 statistical software was used to conduct this meta-analysis. Results Fifteen studies, including 2600 supratentorial ICH patients, were included in our meta-analysis. The pooled results showed that NS could effectively reduce the postoperative mortality (P < 0.00001) and increase the hematoma evacuation rate (P < 0.00001). However, no significant difference was found between NS and SA in improving the functional prognosis (P = 0.15). In the aspect of hospital stays (P < 0.00001), no enough evidence could support that SA could shorten the hospital stays better than NS. However, SA had more advantages in shortening operation time (P < 0.00001) and reducing intraoperative blood loss (P < 0.00001). In the aspect of complications, NS could have a positive effect on preventing intracranial infection (P = 0.004). In the subgroup analysis, we found that Initial GCS might be a risk factor affecting prognosis and hematoma volume might be an important factor affecting mortality. Conclusion NS might have more advantages than SA in the treatment of supratentorial ICH. However, SA was also an effective alternative for middle-aged and elderly patients. More high-quality studies were needed to verify our conclusions in the future.
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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 | 0.015 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.056 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 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".