Kognition bei älteren multimorbiden stationären Patienten: Einfluss auf Endpunkte bei Entlassung und dreimonatiger Nachbeobachtung
Bibliographic record
Abstract
Cognitive deficits in older multimorbid patients hospitalised for non-neuropsychiatric reasons often remain undiagnosed but are associated with poor therapy adherence and unfavourable disease trajectories. This study aimed to investigate the relationship of cognition on hospital admission with patients’ functional status and frailty at discharge, as well as mortality, hospital readmission, admission to a long-term care facility (LTCF) and falls one and three months after discharge in older hospitalised multimorbid patients. It was hypothesised that better cognition upon admission would predict better outcomes at and after discharge. One hundred and thirty-one (N = 131) older (≥ 65 years), multimorbid (≥ two chronic diseases) inpatients at Ageing Medicine Ward of the Department II of Internal Medicine at the University Hospital of Cologne underwent upon admission comprehensive geriatric assessment (CGA) with Multidimensional Prognostic Index (MPI) calculation and a neuropsychological battery (Montreal Cognitive Assessment – MoCA, Trail Making Test Parts A and B – TMT-A & -B). Outcomes were functional ability (Barthel-Index – BI) and frailty/ poor prognosis (CGA-based MPI) at discharge as well as by phone collected one- and three-months post-discharge mortality, readmission to hospital, admission to LTCF, and falls. Of 131 patients, n = 121 (92.4%) showed global cognitive deficit upon admission. Of those, n = 6 cases were already known (n = 1 mild cognitive impairment – MCI, n =5 dementia), while 95% were patients with a newly identified mild or severe cognitive deficit (mCD or sCD). Patients with better performance in MoCA, TMT-A, and -B upon admission showed significantly higher functional ability at discharge (p < .001, p = .008, p = .003, respectively). MoCA (R2 = .227, p <.001) and TMT-B [OR (95% CI) = 1.006 (1.002, 1.009), p = .003] predicted BI independent of demographic factors (age, gender, education, MPI upon admission). Patients with better MoCA scores showed lower frailty at discharge (p = .005), but MoCA did not predict MPI. Neither MoCA nor TMT anticipated any of the post-discharge outcomes. In conclusion, better cognitive function upon hospital admission appears protective against functional loss at discharge in older multimorbid German inpatients. Therefore, early cognitive assessment in this population is crucial to identify patients who will develop functional deficits at discharge to ensure timely implementation of preventive strategies or individually adapted therapy schemata. Given the demographic transition and the hospitalisation rate, cognitive testing should be an integral part of the geriatric evaluation upon admission to an acute hospital.
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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) | 0.001 | 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 | 0.001 |
| 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".