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Record W4396669336 · doi:10.1177/09612033241247103

Cytomegalovirus infection and disease in systemic lupus erythematosus patients at a high-complexity hospital in southwestern Colombia

2024· article· en· W4396669336 on OpenAlexaff
Juan Fernando Contreras-Valero, Ingrid Ruíz-Ordóñez, Gabriel David Pinilla-Monsalve, Mario Bautista-Vargas, Vanessa Ocampo-Piraquive, David Aguirre-Valencia

Bibliographic record

VenueLupus · 2024
Typearticle
Languageen
FieldMedicine
TopicCytomegalovirus and herpesvirus research
Canadian institutionsInstitut Universitaire de Gériatrie de Montréal
Fundersnot available
KeywordsMedicineSeptic shockCytomegalovirusGanciclovirIntensive care unitDiseaseSystemic lupus erythematosusInternal medicinePopulationCytomegalovirus infectionImmunologySepsisViral diseaseHuman cytomegalovirusVirusHerpesviridae

Abstract

fetched live from OpenAlex

Cytomegalovirus (CMV) infection and disease is a condition usually described in immunocompromised patients, but among them, those with connective tissue diseases are poorly represented. Here we present the clinical, laboratory characteristics, management and outcomes of systemic lupus erythematosus (SLE) patients who presented with a CMV infection/disease to a high complexity hospital in southwestern Colombia between 2011 and 2020. 16 SLE patients were found to have a CMV infection. SLE was predominantly characterized by renal involvement (10 patients; 62.50%), and 14 patients (87.5%) were receiving steroids previous to the CMV infection. The entire sample required hospital admission, mainly related to acute kidney injury, and nine patients were admitted to the intensive care unit (ICU). Gastrointestinal organ damage was the most common CMV disease manifestation. All patients received ganciclovir, five of them (31.25%) suffered from septic shock, and seven (43.75%) died. Age ≥38 years and the presence of septic shock at admission were correlated to the mortality outcome. To our knowledge, this is the first publication evaluating SLE patients with CMV infection/disease in a Colombian population.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.009
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
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 head0.018
GPT teacher head0.277
Teacher spread0.259 · 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.

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

Citations2
Published2024
Admission routes1
Has abstractyes

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