Chronic Cytomegalovirus Infection and Inflammation Are Associated with Prevalent Frailty in Community‐Dwelling Older Women
Bibliographic record
Abstract
OBJECTIVES: To evaluate the association between asymptomatic chronic cytomegalovirus (CMV) infection and the frailty syndrome and to assess whether inflammation modifies this association. DESIGN: Cross-sectional analysis. SETTING: Women's Health and Aging Study I & II, Baltimore, Maryland. PARTICIPANTS: Seven hundred twenty-four community-dwelling women aged 70 to 79 with baseline measures of CMV, interleukin-6 (IL-6), and frailty status. MEASUREMENTS: CMV serology and IL-6 concentrations were measured using enzyme-linked immunosorbent assay. Frailty status was based on previously validated criteria: unintentional weight loss, weak grip strength, exhaustion, slow walking speed, and low level of activity. Frail women had three or more of the five components, prefrail women had one or two components, and women who were not frail had none of the components. Multinomial logistic regression adjusted for potential confounders. RESULTS: Eighty-seven percent of women were CMV seropositive, an indication of chronic infection. CMV was associated with prevalent frailty, adjusting for age, smoking history, elevated body mass index, diabetes mellitus, and congestive heart failure (CMV frail adjusted odds ratio (AOR)=3.2, P=.03; CMV prefrail AOR=1.5, P=.18). IL-6 interacted with CMV, significantly increasing the magnitude of this association (CMV positive and low IL-6 frail AOR=1.5, P=.53; CMV positive and high IL-6 frail AOR=20.3, P=.007; CMV positive and low IL-6 prefrail AOR=0.9, P=.73; CMV positive and high IL-6 prefrail AOR=5.5, P=.001). CONCLUSION: Chronic CMV infection is associated with prevalent frailty, a state with increased morbidity and mortality in older adults; inflammation enhances this effect. Further prospective studies are needed to establish a causal relationship between CMV, inflammation, and frailty.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".