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Record W2741219990 · doi:10.14740/jocmr3131w

Epidemiology of Infective Endocarditis in Rural Upstate New York, 2011 - 2016

2017· article· en· W2741219990 on OpenAlexvenueno aff
Saeeda Fatima, Benajmin Dao, Ayesha Jameel, Konika Sharma, David Strogatz, Melissa Scribani, Harish Raj Seetha Rammohan

Bibliographic record

VenueJournal of Clinical Medicine Research · 2017
Typearticle
Languageen
FieldMedicine
TopicInfective Endocarditis Diagnosis and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEpidemiologyInfective endocarditisIntensive care medicineGerontologyFamily medicineSurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The epidemiology of infective endocarditis (IE) depends on a number of host factors whose prevalence can vary globally. The usual patient population affected by IE is sicker and older, often with many comorbid conditions. The risk is growing in younger populations due to the emerging epidemic of intravenous (IV) drug use. We have performed a temporal trend analysis of various factors of IE in the rural counties covering a major part of central Upstate New York. METHODS: We performed a retrospective analysis of electronic medical records of patients who were admitted in a tertiary care hospital in rural Upstate New York and diagnosed with IE from January 1, 2011 to December 31, 2016. Forty-five patients were identified with definite IE and nine with possible IE. RESULTS: Total incidence of IE was 3.5 cases per 100,000 person years in the total population and 4.4 if we consider total population ≥ 18 years in the denominator. A significant (P = 0.022) increase in incidence of IE from 2011 to 2016 was seen by univariate analysis. Incidence was higher in males (P = 0.029) and for those aged 65 or older (P = 0.0003). IV drug use among cases is noted to be more prevalent in 2015 and 2016 compared to previous years. CONCLUSION: In this study of patients in a rural region of New York, an increase in the incidence of IE was seen over the study period with changes in patient characteristics and etiology over this time. We speculate that an increase in IV drug use could be a leading factor in the recent and future increased incidence of IE in the area.

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 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)0.023
metaresearch head score (Gemma)0.068
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.178
Threshold uncertainty score0.939

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0230.068
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.475
GPT teacher head0.604
Teacher spread0.128 · 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 teacher head, not a consensus.

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

Citations25
Published2017
Admission routes1
Has abstractyes

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