Cytomegalovirus seropositivity is associated with herpes zoster
Bibliographic record
Abstract
Herpes zoster (HZ) is caused by VZV reactivation that is facilitated by a declined immunity against varicella-zoster virus (VZV), but also occurs in immunocompetent individuals. Cytomegalovirus (CMV) infection is associated with immunosenescence meaning that VZV-specific T-cells could be less responsive. This study aimed to determine whether CMV infection could be a risk factor for the development of HZ. CMV IgG serostatus was determined in stored serum samples from previously prospectively recruited ambulatory adult HZ patients in the UK (N = 223) in order to compare the results with those from UK population samples (N = 1545) by means of a logistic regression (controlling for age and gender). Furthermore, we compared the UK population CMV seroprevalence with those from population samples from other countries (from Belgium (N1 = 1741, N2 = 576), USA (N = 5572) and Australia (N = 2080)). Furthermore, CMV IgG titers could be compared between UK HZ patients and Belgium N2 population samples because the same experimental set-up for analysis was used. We found UK ambulatory HZ patients to have a higher CMV seroprevalence than UK population samples (OR 1.56 [1.11 2.19]). CMV IgG seropositivity was a significant risk factor for HZ in the UK (OR 3.06 [1.32 7.04]. Furthermore, high CMV IgG titers (exceeding the upper threshold) were less abundant in CMV-seropositive Belgian N2 population samples than in CMV-seropositive UK HZ patients (OR 0.51 [0.31 0.82]. We found CMV-seroprevalence to increase faster with age in the UK than in other countries (P < 0.05). We conclude that CMV IgG seropositivity is associated with HZ. This finding could add to the growing list of risk factors for HZ.
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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 | 0.000 | 0.003 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".