High C-Reactive Protein and Low Albumin Levels Predict High 30-Day Mortality in Patients Undergoing Percutaneous Endoscopic Gastrotomy
Bibliographic record
Abstract
BACKGROUND: Percutaneous endoscopic gastrotomy (PEG) enables long-term enteral feeding. The aim of this study was to identify biomarkers that may guide the decision of whether to perform the elective procedure of PEG. METHODS: The medical records of all patients who underwent PEG in our hospital from 2010 to 2016 were screened retrospectively. Patients with mortality within a 30-day follow-up period and those without were compared using the Chi-square test, and continuous variables were compared with the Kruskal-Wallis and Mann-Whitney U tests. Receiver operating characteristic (ROC) curve analysis was used to demonstrate the ability of biomarkers to predict mortality; a cut-off point was determined and its sensitivity, specificity, and positive and negative predictive values were calculated. The Youden index was used to determine the cut-off point. Kaplan-Meier analysis was used to identify PEG-related mortality risk factors and a Cox regression model was applied for risk characterization. RESULTS: A total of 120 patients who underwent PEG were evaluated in the study. The mean age was 67.00 ± 18.00 years. The most common indication for PEG was cerebrovascular disease, in 69 (57.5%) of the patients. Infection of the PEG site was most common within 14 days after PEG tube placement, occurring in 13 patients (10.3%). The mortality rate among patients with post-PEG infection was 68.2%, significantly higher than in patients without infection (P = 0.012). Thirty-four patients (28.3%) died within 30 days of undergoing PEG. CRP values ≥ 78.31 mg/L increased mortality by 8.756-fold, and albumin levels < 2.71 g/dL increased mortality by 2.255-fold. CONCLUSION: Our results indicate that the presence of both high CRP level and low albumin level were associated with significantly higher rate of mortality (73.1%) in patients who underwent PEG.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".