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Record W2775728559 · doi:10.1016/j.jsxm.2017.10.063

Erectile Dysfunction Medications and Treatment for Cardiometabolic Risk Factors: A Pharmacoepidemiologic Study

2017· article· en· W2775728559 on OpenAlex
Sean Skeldon, Lucy Cheng, Steven G. Morgan, Allan S. Detsky, S. Larry Goldenberg, Michael R. Law

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueThe Journal of Sexual Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicSexual function and dysfunction studies
Canadian institutionsMount Sinai HospitalCentre for Family MedicineUniversity Health NetworkInstitute of Population and Public HealthUniversity of TorontoInstitute of Health Services and Policy ResearchUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsMedicineErectile dysfunctionMedical prescriptionInternal medicineType 2 diabetesDiabetes mellitusPopulationStatinRetrospective cohort studyPolypharmacyPharmacoepidemiologyCohortEndocrinologyPharmacologyEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Erectile dysfunction (ED) can be a sentinel marker for future cardiovascular disease and has been described as providing a "window of curability" for men to receive targeted cardiovascular risk assessment. AIM: To determine whether the prescription of phosphodiesterase type 5 inhibitors (PDE5is) for ED leads to the detection and treatment of previously undiagnosed cardiometabolic risk factors. METHODS: We performed a retrospective population-based cohort study of residents of British Columbia, Canada using linked health care databases from 2004 to 2011. An individual-level time series analysis with switching replications was used to determine changes in drug use for hypertension, hypercholesterolemia, and diabetes in men 40 to 59 years old. The observation window for each patient was 720 days before and 360 days after the index date. OUTCOMES: The primary outcome was changes in prescriptions for antihypertensive, statin, and oral antidiabetic drugs, with secondary outcomes being laboratory tests for plasma cholesterol and glucose. RESULTS: 5,858 men 40 to 59 years old newly prescribed a PDE5i were included in the analysis. We found a sudden increase in prescriptions for antihypertensive drugs (40 per 1,000; P < .001), statins (10 per 1,000; P = .001), and antidiabetic drugs (17 per 1,000; P = .002) in the 90 days after a new prescription for a PDE5i. For hypercholesterolemia and diabetes, most of this change was observed in men with relevant screening tests performed in the 30 days after their PDE5i prescription. Only 15% and 17% of men who did not have a screening test for cholesterol and glucose, respectively, in the year before their PDE5i prescription went on to have one in the subsequent 30 days. CLINICAL IMPLICATIONS: The paucity of screening tests observed in our study after PDE5i prescriptions suggests that physicians should be educated on the recommended screening guidelines for men newly diagnosed with ED. STRENGTHS AND LIMITATIONS: The number of men who were ordered a laboratory test or written a prescription but chose not to complete or fill it, respectively, is unknown. CONCLUSION: Treatment for ED with PDE5is can be a trigger or "gateway drug" for the early detection and treatment of cardiometabolic risk factors provided physicians perform the requisite screening investigations. Skeldon SC, Cheng L, Morgan SG, et al. Erectile Dysfunction Medications and Treatment for Cardiometabolic Risk Factors: A Pharmacoepidemiologic Study. J Sex Med 2017;14:1597-1605.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.197
Threshold uncertainty score0.729

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.170
GPT teacher head0.423
Teacher spread0.253 · 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