132 Physical Function Comparison of Acutely Unwell COVID-Negative Older Adults Pre-Pandemic and Through-Pandemic; “Covid-Protected”
Bibliographic record
Abstract
Abstract Introduction The risk of severe morbidity after COVID-19 infection is high in older adults (Lithander et al, 2020). Subsequent responsive UK Government guidance for older adults included self-isolation during the pandemic. It is therefore hypothesised that during the pandemic older adults are inadvertently deconditioned due to iatrogenic factors such as inactivity, social isolation, hospital-avoidance and malnutrition, and present with reduced resilience to illness and lower levels of function. The OPU continued to admit COVID-negative, or recently termed “COVID-protected”, patients throughout the pandemic. Data captured prior to, and during the COVID-19 pandemic has been compared to explore the implications on older adults, and elicit whether they are protected from the consequences of the pandemic? Method Demographic and physical function data (average 6 m gait-speed, Elderly Mobility Scale) were captured pre- and through-pandemic for all patients admitted to a COVID-negative OPU ward over a one month period. Ethical review was provided through local Trust governance process. Results Pre-pandemic 2019 (n = 67, mean(±SD) age 82.7(±8.2) years, 61%, hospital length-of-stay (LOS) 7.9(±7.3) days, hospital mortality-rate 7.2%) and through-pandemic 2020 (n = 73, 83.1(±8.3) years, 59%♀, LOS 9.0(±9.1) days, hospital mortality-rate 7.5%) data were captured during July 2019 and May 2020 respectively. There were no between-group differences in age [t(−.313) = 138, p = 0.755], gender [X2, 1 df, p = 0.782], LOS [t(0.78) = 134, p = 0.44], or hospital mortality-rate [X2 1 df, p = 0.96]. Through-pandemic patients had a significantly slower 6 m gait-speed (0.11(±0.05) m.s-1) than pre-pandemic (0.16(±0.24) m.s-1); [t(2.74) = 93, p = 0.007] and lower median (IQR) Elderly Mobility Scale (4(6 IQR) vs 9 (12 IQR) [u = 866, p = 0.015]). Conclusion Our data indicates this relatively short period of self-isolation might have significant implications on the physical function of older adults. The likely mechanism is iatrogenic deconditioning. Critical Public Health and policy responses are required to mitigate these unforeseen risks by deploying prehabilitative counter-measures and accurately targeted hospital and community rehabilitation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".