Comparative analysis of different methods of anesthesia in patients with acute pancreatitis using pain scales
Bibliographic record
Abstract
Aim. To conduct a comparative analysis of used anesthesia methods in patients with acute pancreatitis in intensive care units settings using pain scales.Methods. Depending on the anesthesia type, 44 patients with acute pancreatitis were divided into three groups: the first group received intramuscular injections of nonsteroidal anti-inflammatory drugs and spasmolytics, the second group - intramuscular injections of non-steroidal anti-inflammatory drugs and opioid analgesics, the third group - epidural anesthesia with local anesthetics. Comparative analysis of pain character, intensity was conducted, its dynamics in patients of all groups amid anesthesia was evaluated using a visual analogue scale, verbal rating scale, verbal descriptor scale, McGill pain questionnaire.Results. Baseline pain intensity in patients of all groups was high. Patients estimated this pain as «very strong». The time and the level of pain intensity reduction for various anesthesia types had differences. Pain syndrome was eliminated slower in patients of the second group. By the end of the 1st day, patients of this group continued to complain of «strong» pain. Pain intensity decreased only on the 2nd day - patients reported «moderate» pain. Pain syndrome was not completely eliminated in these patients for 2 days of anesthesia. 97.7% of patients reported that the visual analogue scale is the most acceptable pain assessment scale for them.Conclusion. In patients with acute pancreatitis, the most optimal anesthesia types are intramuscular nonsteroidal anti-inflammatory drugs with spasmolytics and prolonged epidural anesthesia with local anesthetics; intramuscular administration of opioid analgesics with non-steroidal anti-inflammatory drugs is less effective in relieving pain.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".