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Record W2046889498 · doi:10.1093/cid/ciu036

Reply to Strandberg and Tienari

2014· letter· en· W2046889498 on OpenAlexaff
Tony Antoniou, David N. Juurlink, Muhammad Mamdani, Tara Gomes

Bibliographic record

VenueClinical Infectious Diseases · 2014
Typeletter
Languageen
FieldMathematics
TopicAdvanced Causal Inference Techniques
Canadian institutionsInstitute for Clinical Evaluative SciencesSunnybrook HospitalUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineDermatology

Abstract

fetched live from OpenAlex

To the Editor—We examined whether statins were associated with a heightened risk of herpes zoster in patients aged ≥66 years and found a small but significantly increased risk among statin users relative to a propensity-matched group of nonusers of these drugs. As noted in our study [1], we did not have access to serum cholesterol levels, and could therefore not account for this variable when matching users and nonusers of statins. We did, however, consider an array of clinically important predictors of statin use when deriving the propensity score. Strandberg and Tienari suggest that despite propensity score matching, users and nonusers of statins differed with respect to cardiovascular disease burden [2]. However, standardized differences for all baseline variables were <0.1, indicating that intergroup differences between these covariates were negligible [3, 4]. Strandberg and Tienari are correct that unmeasured confounders and confounding by indication are potential threats to the validity of all observational studies, including ours. They cite 2 studies supporting their hypothesis that serum cholesterol and the apolipoprotein E epsilon 4 (APOE4) allele are associated with herpes zoster [5, 6]. For these variables to act as confounders, they must be extraneous risk factors for herpes zoster, and the studies cited by Strandberg and Tienari are problematic in supporting this assertion [7]. In the first study, investigators found that cholesterol levels were higher among 12 heart transplant patients who developed herpes zoster in the month prior to the episode than those of the same patients within the first posttransplant year (P = .007) or those of control patients within the first posttransplant year (P = .025) [5]. Although these data suggest that a correlation may exist between serum cholesterol and herpes zoster, the report is limited by a very small sample size, the high-risk nature of the patients, and a lack of control for potential confounders, importantly statin use. The second study compared the distribution of APOE alleles among 104 herpes zoster patients with those of a control group [6]. The authors found that women with herpes zoster were more likely to be homozygous for APOE4 relative to women with no history of herpes zoster, although the absolute numbers were too small to draw firm conclusions [6]. Similar findings were not observed in men, no data on cholesterol levels were provided, and another report found no difference in the distribution of APOE alleles between patients with and without herpes zoster [8]. Although conclusive evidence associating cholesterol levels and/or APOE4 with herpes zoster is lacking, this may simply reflect a deficit in the state of knowledge regarding the pathophysiology of varicella zoster reactivation. As with most diseases, the etiology of herpes zoster is multifactorial, and it is possible that cholesterol and statin use are both components of a specific causal pathway that results in varicella zoster virus reactivation. We agree with the editorialist's call for replication of our findings in other databases [9]. Financial support. T. G., T. A., and M. M. M. have received institutional grant funding from the Ontario Ministry of Health and Long Term Care. T. A. is also funded by an Ontario HIV Treatment Network post-doctoral fellowship. Potential conflicts of interest. All authors: No reported conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.095
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.117
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.095
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0060.007
Scholarly communication0.0070.006
Open science0.0030.004
Research integrity0.1170.081
Insufficient payload (model declined to judge)0.0090.007

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.

Opus teacher head0.176
GPT teacher head0.464
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

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Citations1
Published2014
Admission routes1
Has abstractno

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