From: Machine learning-based prediction models for accidental hypothermia patients
Variables | Development cohort | Validation cohort |
---|---|---|
(N = 288) | (N = 244) | |
Men | 144 (50.0%) | 126 (51.6%) |
Age, years | 79 (69–87) | 79 (64–87) |
 < 60 | 37 (12.8%) | 47 (19.3%) |
 60–69 | 35 (12.2%) | 37 (15.2%) |
 70–79 | 75 (26.0%) | 48 (19.7%) |
 ≥ 80 | 140 (48.6%) | 117 (48.0%) |
Activities of daily living | ||
 Disturbance | 96 (33.3%) | 66 (27.0%) |
Comorbidity | ||
 Cardiovascular diseases | 126 (43.8%) | 111 (45.5%) |
 Neurological diseases | 53 (18.4%) | 40 (16.4%) |
 Endocrine diseases | 83 (28.8%) | 47 (19.3%) |
 Psychiatric diseases | 55 (19.1%) | 63 (25.8%) |
 Malignant diseases | 12 (4.2%) | 4 (1.6%) |
 Dementia | 57 (19.8%) | 51 (20.9%) |
 Other | 56 (19.4%) | 38 (15.6%) |
External and minimally invasive rewarming | ||
 Warm intravenous fluid | 223 (77.4%) | 168 (68.9%) |
 Forced warm air | 80 (27.8%) | 4 (1.6%) |
 Warm environment, warm blanket | 242 (84.0%) | 222 (91.0%) |
 Other | 23 (8.0%) | 15 (6.1%) |
Active internal rewarming | ||
 Lavage | 29 (10.1%) | 15 (6.1%) |
 CHDF | 4 (1.4%) | 17 (7.0%) |
 VV-ECMO | 0 (0%) | 2 (0.8%) |
 VA-ECMO | 3 (1.0%) | 17 (7%) |
In-hospital mortality | 64 (22.2%) | 66 (27.0%) |