Effect of complication grade on survival following curative gastrectomy for carcinoma
Bibliographic record
Abstract
AIM: To elucidate the potential impact of the grade of complications on long-term survival of gastric cancer patients after curative surgery. METHODS: A total of 751 gastric cancer patients who underwent curative gastrectomy between January 2002 and December 2006 in our center were enrolled in this study. Patients were divided into four groups: no complications, Grade I, Grade II and Grade III complications, according to the following classification systems: T92 (Toronto 1992 or Clavien), Accordion Classification, and Revised Accordion Classification. Clinicopathological features were compared among the four groups and potential prognostic factors were analyzed. The Log-rank test was used to assess statistical differences between the groups. Independent prognostic factors were identified using the Cox proportional hazards regression model. Stratified analysis was used to investigate the impact of complications of each grade on survival. RESULTS: Significant differences were found among the four groups in age, sex, other diseases (including hypertension, diabetes and chronic obstructive pulmonary disease), body mass index (BMI), intraoperative blood loss, tumor location, extranodal metastasis, lymph node metastasis, tumor-node-metastasis (TNM) stage, and chemotherapy. Overall survival (OS) was significantly influenced by the complication grade. The 5-year OS rates were 43.0%, 42.5%, 25.5% and 9.6% for no complications, and Grade I, Grade II and Grade III complications, respectively (P < 0.001). Age, tumor size, intraoperative blood loss, lymph node metastasis, TNM stage and complication grade were independent prognostic factors in multivariate analysis. With stratified analysis, lymph node metastasis, tumor size, and intraoperative blood loss were independent prognostic factors for Grade I complications (P < 0.001, P = 0.031, P = 0.030). Age and lymph node metastasis were found to be independent prognostic factors for OS of gastric cancer patients with Grade II complications (P = 0.034, P = 0.001). Intraoperative blood loss, TNM stage, and chemotherapy were independent prognostic factors for OS of gastric cancer patients with Grade III complications (P = 0.003, P = 0.005, P < 0.001). There were significant differences among patients with Grade I, Grade II and Grade III complications in TNM stage II and III cancer (P < 0.001, P = 0.001). CONCLUSION: Complication grade may be an independent prognostic factor for gastric cancer following curative resection. Treatment of complications can improve the long-term outcome of gastric cancer patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".