Effect of Preoperative Accurate Evaluation and Intervention on Prognosis and Outcome in Elderly Patients with Painless Gastroenteroscopy: Protocol for A Single-Centre Randomized Controlled Trial
Bibliographic record
Abstract
Background: Factors such as abstinence from drinking, fasting, intestinal preparation, and stress responses can contribute to issues like inadequate blood volume, hypoglycemia, and electrolyte imbalances. The ASA classification presently serves as a primary assessment standard globally. In response to prevailing clinical challenges, we propose enhancing the preoperative assessment for elderly patients undergoing painless gastroenteroscopy. This enhancement involves incorporating the Frailty score, bedside ultrasound, and bedside laboratory results alongside the ASA classification, to establish a comprehensive assessment system. This holistic approach aims to monitor patients’ fluid balance, electrolyte levels, and blood glucose changes, facilitating precise interventions and optimized anesthesia strategies. The ultimate goal is to diminish perioperative adverse events, especially those related to the cardiovascular system, thereby enhancing prognosis, outcomes, and patient satisfaction among the elderly. Methods: This study is a randomized controlled trial conducted at a single center. It includes 204 patients scheduled for painless gastroenteroscopy. Eligible subjects will be randomly assigned to either Group A or Group B. Pre-anesthesia assessments will be conducted twice – during the preoperative visit and upon entry to the endoscopy center on the examination day. Evaluation parameters will encompass the Edmonton Frail Scale (EFS), bedside ultrasound measurements including inspiratory IVCDmax, expiratory IVCDmin, and calculation of the inferior vena cava collapse index (IVC-CI). Additionally, serum electrolyte (potassium) and blood glucose levels will be measured. Patients in Group A will receive specific interventions based on predetermined criteria. The primary endpoint is anesthesia-related adverse events. The measurements will be performed perioperatively, post-treatment, and at 1 day, 3 days, and 7 days after the end of treatment.
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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 | 0.033 | 0.032 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.017 | 0.008 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.042 | 0.007 |
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".