The relationship between fragility scores and intraoperative body temperature changes in geriatric patients: Prospective observational research
Bibliographic record
Abstract
Today, to evaluate morbidity and mortality in elderly surgical patients, fragility scores, which reflect the patient's current condition rather than increasing age, are used as a basis. Our research examines the association between fragility groups, body temperature changes, and inadvertent perioperative hypothermia (IPH) in major orthopedic surgery patients. Patients over the age of 65 who underwent major orthopedic surgery were evaluated. Body temperature measurements were taken tympanically preoperatively and every 5 minutes during surgery. Temperature changes (Δn) were calculated. Patients whose body temperature was below 36 °C were recorded as IPH. The Canadian Study of Health and Aging-Clinical Frailty Scale scoring system, consisting of 9 categories, was used for fragility scores. As the category number increases, the level of fragility increases. These categories are classified into 3 subgroups: Group F1 (Level 1-3), Group F2 (Level 4-7), and Group F3 (Level 8-9). Age groups: it is defined as Group A1 (66-74 years), Group A2 (75-84 years), and Group A3 (85<). The median (min-max) of surgery time was determined as 75 (35-131). For Δ35 (ºC), the differences between both fragility groups (P = .054) and the age groups (P = .145) were not significant. IPH frequency is 44.0% (n = 149). No difference was detected between hypothermia frequencies in the fragility groups (P = .546) and the age groups (P = .065). Nearly half of major surgery patients developed IPH. We did not find a relationship between both fragility groups and age groups and the frequency of IPH.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".