Safety of Simultaneous Hepatectomy and Splenectomy in the Treatment of Hepatocellular Carcinoma Complicated with Hypersplenism: A Meta-analysis
Bibliographic record
Abstract
BACKGROUND: We conducted this meta-analysis to compare the efficacy and safety of simultaneous hepatectomy and splenectomy (HS) with hepatectomy alone (HA) in patients with hepatocellular carcinoma (HCC) and hypersplenism. MATERIALS AND METHODS: A systematic search was conducted in PubMed, Embase, Cochrane Library, and Wanfang Data through March 1, 2018, with no limits. Two investigators independently screened all retrieved studies. The investigators of the original publications were contacted if required information was absent. All the included studies were managed by EndNote X7. Quality assessment of the included studies was performed using a modified Newcastle-Ottawa Scale judgment. Extracted data for each endpoint were analyzed by using STATA 12.0 software. RESULTS: Thirteen studies, including a total of 1468 patients, comparing the effects of HS with HA were pooled in this meta-analysis. Outcomes including postoperative complications, perioperative mortality, intraoperative blood transfusion, and albumin (ALB) content at postoperation day (POD) 7 did not differ significantly between the two groups. Simultaneous approaches significantly promoted 1-, 3-, and 5-year disease-free survival (DFS) rates and overall survival (OS) rates, prolonged operation time, aggravated intraoperative blood loss, increased white blood cell (WBC) and platelet (PLT) counts at POD 7, and lowered total bilirubin (T-Bil) contents at POD 1 and 7. CONCLUSION: Compared to HA, HS is safer and more effective in ameliorating liver function and improving survival of HCC patients complicated with hypersplenism. This trial is registered with CRD42018093779.
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 | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.059 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| 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".