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Record W2902607057 · doi:10.1093/ofid/ofy210.1300

1470. Neurocognitively-Acting Potentially Inappropriate Medications, Alcohol, and Community-Acquired Pneumonia Among Patients with and Without HIV

2018· article· en· W2902607057 on OpenAlexaff
Christopher T. Rentsch, Janet P. Tate, Kirsha S. Gordon, Alice Tseng, Kristina M. Niehoff, Kristina Crothers, E. Jennifer Edelman, Amy C. Justice

Bibliographic record

VenueOpen Forum Infectious Diseases · 2018
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsMedicineOdds ratioInternal medicineAlcohol use disorderCommunity-acquired pneumoniaPneumoniaPediatricsAlcohol

Abstract

fetched live from OpenAlex

Alcohol interactions with neurocognitively-acting potentially inappropriate medications (NC-PIMs) may be more common, more harmful, and associated with lower levels of alcohol use among people living with HIV. We conducted a nested case–control study using data from the Veterans Aging Cohort Study (2007–2015). Cases with community-acquired pneumonia (CAP) requiring hospitalization (n = 6,716) were 1:5 matched to controls without CAP (n = 33,253) at the time of event by age, sex, race, HIV status, baseline year, and duration of observation time. Index date was defined as CAP date for cases and match date for controls. Based on pharmacy data in the year prior to index date, NC-PIMs included receipt of at least one prescription of any duration for anticonvulsants, sedatives (including benzodiazepines), prescription opioids, antidepressants, antipsychotics, and muscle relaxants. Among HIV+, NC-PIMs exposure also included ritonavir (RTV), cobicistat (COBI), and efavirenz (EFV). Conditional logistic regression models were used to obtain adjusted odds ratios (OR) and 95% confidence intervals (CI) for NC-PIMs (any and count overall, and by class), alcohol use disorder (AUD) diagnoses in the year prior to index date, and their interaction adjusted for smoking status, VACS Index, steroids, vaccination status (influenza and pneumonia), hepatitis C, previous CAP, and various comorbidities. Among 39,989 patients, 17,161 (43%) were HIV+, 98% were male, and median age was 58 years. An increase in number of classes of NC-PIMs was associated with a 17% increase in the odds of CAP among HIV+ and uninfected, and this effect was augmented by contemporaneous AUD. Among HIV+, all classes of NC-PIMs apart from EFV were positively associated with CAP, most notably antipsychotics (OR 1.66, 95% CI 1.43–1.93). Among uninfected, the highest risk of CAP was associated with antipsychotics (OR 1.81, 95% CI 1.61–2.03) and anticonvulsants (OR 1.64, 95% CI 1.49–1.80). AUD positively interacted with sedatives, opioids, antidepressants, and muscle relaxants in both groups, and with RTV/COBI in HIV+ patients. NC-PIMs, especially with concurrent AUD, are associated with increased CAP risk among those living with and without HIV. All authors: No reported disclosures.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.012
GPT teacher head0.268
Teacher spread0.256 · 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 designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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