Senatvinio silpnumo sindromo įtaka vyresnio amžiaus pacientų pooperaciniams rezultatams po planinės širdies operacijos
Bibliographic record
Abstract
Introduction. Despite surgical, anesthetic and medical advances, older surgical patients continue to suffer from adverse postoperative outcomes. Literary review suggests that frailty predisposes elderly patients to worsening outcome after cardiac surgery. Aim of the study - To analyse the influence of frailty in elderly patients on postoperative outcomes after elective cardiac surgery. Method. Study was conducted between 2nd of December 2020 and 28th of January 2021 at Hospital of Lithuanian University of Health Sciences Kaunas Clinics. The study was approved by the Ethics Committee (ongoing research „Predisponuojančių veiksnių išaiškinimas kognityvinių funkcijų sutrikimo atsiradimui pacientams, kuriems atliekamos operacijos naudojant dirbtinę kraujo apytaką“BE-2-3 2017.04.12 Lietuvos sveikatos mokslų universitetinė ligoninė Kauno klinikos; Širdies, krūtinės ir kraujagyslių chirurgijos klinika). Data on 72 patients after elective cardiac surgery on cardiopulmonary bypass (CPB) were analysed retrospectively. The patients were assessed and monitored preoperatively, during surgery and in the early postoperative period. Frailty syndrome was evaluated using Edmonton Frail Scale (EFS). The most common postoperative complications may include: cardiac complications (one of either ischemia, congestive heart failure, new arrhythmia or sudden death), shock, and haemorrhage, lung (pulmonary) complications wound infection, deep vein thrombosis (DVT) and pulmonary embolism (PE), renal or neurological dysfunction. The data are presented as the mean and the standard deviation (M (SD). Differences were considered as statistically significant at p<0, 05. Conclusions. The prevalence of frailty in elderly patients before cardiac surgery has been evaluated and it was found that preoperatively, the frailty syndrome was identified in the majority of patients (52.8%). After evaluation of correlations of frailty in elderly patients with their clinical factors, it was found that frailty is more common in patients with co-morbidities. The study revealed that frailty was found more frequently in older than 85 yr. patients. Having evaluated correlations between the prevalence of frailty and postoperative outcomes after cardiac surgery it was found that patients with frailty syndrome had postoperative complications more frequently and its prolonged length of stay in the hospital, however it depended on the level of frailty.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".