Correction: Assessing the Impact of Frailty on Infection Risk in Older Adults: Prospective Observational Cohort Study
Bibliographic record
Abstract
Background: Infectious diseases are among the leading causes of death and disability and are recognized as a major cause of health loss globally. At the same time, frailty as a geriatric syndrome is a rapidly growing major public health problem. However, few studies have investigated the incidence and risk of infectious diseases in frail older people. Thus, research on frailty and infectious diseases is urgently needed. Objective: The purpose of this study was to evaluate the association between frailty and infectious diseases among older adults aged 65 years and older. Methods: In this prospective observational cohort study, we have analyzed the infectious disease prevalence outcomes of older adults aged 65 years and older who participated in frailty epidemiological surveys from March 1, 2018, to March 2023 in Dalang Town, Dongguan City, and from March 1, 2020, to March 2023 in Guancheng Street, Dongguan City. This study has an annual on-site follow-up. Incidence data for infectious diseases were collected through the Chinese Disease Controland Prevention Information System—Infectious Disease Monitoring and Public Health Emergency Monitoring System. A project-developed frailty assessment scale was used to assess the frailty status of study participants. We compared the incidence rate ratios (IRR) of each disease across frailty status, age, and gender to determine the associations among frailty, gender, age, and infectious diseases. Cox proportional hazards regression was conducted to identify the effect of frailty on the risk of demographic factors and frailty on the risk of infectious diseases, with estimations of the hazard ratio and 95% CI. Results: A total of 235 cases of 12 infectious diseases were reported during the study period, with an incidence of 906.21/100,000 person-years in the frailty group. In the same age group, the risk of infection was higher in men than women. Frail older adults had a hazard ratio for infectious diseases of 1.50 (95% CI 1.14‐1.97) compared with healthy older adults. We obtained the same result after sensitivity analyses. For respiratory tract–transmitted diseases (IRR 1.97, 95% CI 1.44‐2.71) and gastrointestinal tract–transmitted diseases (IRR 3.67, 95% CI 1.39‐10.74), frail older adults are at risk. Whereas no significantassociation was found for blood-borne, sexually transmitted, and contact-transmitted diseases (IRR 0.76, 95% CI 0.37‐1.45). Conclusions: Our study provides additional evidence that frailty components are significantly associated with infectious diseases. Health care professionals must pay more attention to frailty in infectious disease prevention and control.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
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 | 0.020 | 0.268 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.006 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.095 | 0.016 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".