Impact of the type of anesthesia on the frequency of postoperative complications after hernioplasty and on the dynamics of the frailty index in elderly patients with inguinal hernia
Bibliographic record
Abstract
Purpose of the study. The purpose of the study was to compare the effect of spinal and general anesthesia on the incidence of postoperative complications aſter hernioplasty and on the dynamics of the frailty index (FI) in elderly patients with inguinal hernia. Patients and methods. 78 patients diagnosed with inguinal hernia were involved in the study (average age was 70.1 ± 0.8 years). Patients underwent open hernia repair and Lichtenstein plasty of the posterior wall of the inguinal canal. The patients were divided into two groups depending on the type of anesthesia: spinal anesthesia (SA; N = 65) and general anesthesia (GA; N = 13). At the time of admission, 30 days aſter the surgery, the FI was calculated using the Edmonton questionnaire. Results. In the SA group, 39 patients (60 %) had a FI ≥ 7; 9 patients (13.8 %) had a FI ≥ 9; 8 patients (12.3 %) had a FI ≥ 11; and 9 patients (13.8 %) had the highest FI ≥ 12. At 30 days aſter surgery, 20 patients (30.8 %) showed a decrease in FI values (FI from 7 to 9 decreased almost 2-fold). In the GA group, on the day of admission, 6 patients (46.2 %) had FI ≥ 7, 5 (38.5 %) had FI ≥ 9, and 2 (15.4 %) had FI ≥ 11. At 30 days aſter surgery, no changes were observed in patients with FI ≥ 7. Conclusion. In the spinal anesthesia group, urinary retention was predominant among complications, while in patients aſter general anesthesia, pulmonary atelectasis prevailed among complications. The use of spinal anesthesia for hernioplasty was accompanied by a decrease in the frailty index within 30 days aſter surgery in individuals with a FI ≥ 7. In the GA group, decrease in the index within 30 days aſter surgery was observed in patients with FI ≥ 9.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".