Who stands to lose the most: impact of delirium on long‐term cognitive impairment in a hip fracture repair cohort
Bibliographic record
Abstract
BACKGROUND: Delirium, an acute disorder of attention and cognition, is a potentially preventable contributor to poor outcomes in older adults including future cognitive decline. The goal of this study was to determine the cognitive impact of postoperative delirium on patients who underwent hip fracture repair (HFR) over a 1-year period. Our hypothesis was that the downstream impact of delirium may be greater among individuals who are cognitively unimpaired compared to those who have cognitive impairment at baseline. METHOD: Cognitive assessments from 200 HFR patients enrolled in the randomized clinical trial "A Strategy to Reduce the Incidence of Postoperative Delirium in Elderly Patients" (STRIDE) were examined for cognitive changes at 1-year after surgery. Inclusion criteria were age ≥65 and Mini-Mental State Exam (MMSE) score ≥15. Delirium status and Clinical Dementia Rating (CDR) were adjudicated by a consensus diagnostic panel. Global CDR score was used to define subgroups. Data were analyzed using a random-intercept linear spline model, with MMSE over time as outcome of interest; MMSE scores at baseline, 1-month, and 1-year were used. RESULT: Delirium incidence in this cohort was 36.5%. Prior to surgery, 41% were cognitively unimpaired (CDR=0), while 58% had mild cognitive impairment or dementia (CDR>0), 2 cases were missing CDR. Baseline MMSE was 2.054 points lower for the group that experienced delirium compared to the no delirium group in the entire cohort (Figure 1). Delirium incidence was associated with rate of decline in MMSE scores in the entire cohort. Incident delirium was associated with more rapid rate of MMSE decline in the entire cohort (β=-0.002, SE=0.001, p = 0.110) (Figure 1) and in the subgroup without cognitive impairment (CDR=0) (β=-0.004, SE=0.002, p = 0.046) (Figure 2); but not in participants with baseline cognitive impairment (CDR>0). Greater delirium severity, measured by Delirium Rating Scale-Revised-98 (DRS-R-98), was associated with more rapid decline in MMSE only for the subgroup without cognitive impairment (β = -0.0004, SE=0.0001, p = 0.004). CONCLUSION: Delirium incidence and severity impact cognitive changes in older adults undergoing HFR, most significantly in those who are cognitively unimpaired. Results from this cohort are aligned with other studies suggesting that cognitively unimpaired individuals stand to lose the most after delirium.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".