Additional file 1 of Clustering of critically ill patients using an individualized learning approach enables dose optimization of mobilization in the ICU
Bibliographic record
Abstract
Additional file 1. Figure S1: Elbow method for determination of clusters. Figure S2: Euclidian distance plot. Heatmap showing Euclidean distances between samples clustered using complete linkage. Factors used for Cluster Analysis are visualized as column annotations. Table S1: Patient Characteristics. Numbers are presented as n (%) or median [IQR]. “Frail” is defined as Clinical Frailty Scale 5–9. A p-value of < 0.05 was considered significant. ICU Intensive Care Unit, IQR Interquartile Range, APACHE II Acute Physiology and Chronic Health Evaluation Score, SOFA Sepsis-related Organ Failure Assessment Score, MTB Mobility-Transfer-Barthel. Table S2: Post-hoc Analyses of patient characteristics in the four clusters. Numbers are presented as n (%) or median [IQR]. “Frail” is defined as Clinical Frailty Scale 5–9. A p-value of < 0.05 was considered significant. APACHE Acute Physiology and Chronic Health Evaluation Score, SOFA Sepsis-related Organ Failure Assessment Score, MTB Mobility-Transfer-Barthel. Table S3: Post-hoc Analyses of mobilization characteristics in the four clusters. Early mobilization is defined as mobilization within 72h of ICU admission. A p-value of < 0.05 was considered significant. Numbers are presented as n (%) or median [IQR]. IQR Interquartile Range, SOMS Surgical Intensive Care Unit Optimal Mobilization Score. Table S4: Stepwise Regression Models. “Frailty” is defined as Clinical Frailty Scale 5–9. A p-value of < 0.05 was considered significant. Early mobilization is defined as mobilization within 72h of ICU admission. OR Odds Ratio, CI Confidence interval, ICU Intensive Care Unit, IQR Interquartile Range, APACHE II Acute Physiology and Chronic Health Evaluation Score, SOFA Sepsisrelated Organ Failure Assessment Score, SOMS Surgical Intensive Care Unit Optimal Mobilization Score. Table S5: Logistic regression models of survivors of hospital stay. Early mobilization is defined as mobilization within 72h of ICU admission. A p-value of < 0.05 was considered significant. OR Odds Ratio, CI Confidence interval, SOMS Surgical Intensive Care Unit Optimal Mobilization Score. a Model was corrected for postoperative care, frailty, department. b Model was corrected for Sepsis-related Organ Failure Assessment Score, body mass index (categories), postoperative, frailty, other admission reasons, admission, and non-traumatic brain injury. c Model was corrected for department and Glasgow Coma Scale. d Model was corrected for APACHE II, department, admission, Mobility-Transfer-Barthel Score at hospital admission and age (categories). Table S6: Sensitivity Analysis with the ICU Mobility Scale. Early mobilization is defined as mobilization within 72h of ICU admission. A p-value of < 0.05 was considered significant. OR Odds Ratio, CI Confidence interval. IQR Interquartile Range, IMS ICU Mobility Scale. Table S7: Secondary Endpoints. Secondary endpoints in dependence of the four clusters. Here, the results of the primary analysis as well as the post-hoc analyses are listed. Numbers are presented as n (%) or median [IQR]. A p-value of < 0.05 was considered significant. IQR Interquartile Range, ICU Intensive Care Unit.
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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 | 0.002 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.823 | 0.114 |
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".