0113 The Influence of Insomnia Severity on Cognitive Functions in Older Surgical Patients
Bibliographic record
Abstract
Abstract Introduction Sleep disorders, including insomnia, affect up to one-third of older adults over the age of 65 undergoing surgery, yet they often remain untreated. Insomnia-related sleep disturbances have been linked to weakened immune function, delayed recovery, and impaired cognitive abilities (e.g., attention, memory, language), particularly in older adults. However, the influence of sleep-related disorders on cognitive functions in older surgical patients remains unclear. Given the increasing hospitalization rates in older adults, we hypothesized that greater insomnia severity would be associated with poorer cognitive performance. Methods A cohort of 17 older adults (≥70 years) scheduled for total knee, total hip, or spine surgery was recruited. One week before their scheduled surgery, participants were asked to complete the Insomnia Severity Index (ISI) questionnaire and the Montreal Cognitive Assessment (MOCA), which assessed primary cognitive functions, including abstraction, attention, language, orientation, and delayed recall. Results We computed a simple linear regression model analysis to investigate whether ISI scores predicted cognitive performances using the total MOCA scores as our key dependent variables. Additional model predictors were tested included surgery type, sex, and age. In alignment with our hypothesis, results suggested that for every 1 SD increase in ISI scores a 0.09 SD decrease in MOCA scores was predicted (SE =.07, p = 0.26). Although not statistically significant, these preliminary findings are promising, as we are still collecting data and anticipate stronger trends as we reach sufficient statistical power. Conclusion Out preliminary results seemed to indicate that older adults with higher insomnia severity may exhibit larger cognitive impairments, potentially increasing their vulnerability during surgical recovery. Further investigation is warranted. Support (if any) Alzheimer’s Association Clinician Scientist Fellowship (AACSF-23-1148490, L.G)
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".