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THE ECONOMIC IMPACT OF CYTOMEGALOVIRUS INFECTION AFTER LIVER TRANSPLANTATION

2000· article· en· W1994348557 on OpenAlexaff
W. Ray Kim, Andrew D. Badley, Russell H. Wiesner, Michael K. Porayko, Michael R. Keating, Roger W. Evans, E. Rolland Dickson, Ruud A. F. Krom, Carlos V. Payá

Bibliographic record

VenueTransplantation · 2000
Typearticle
Languageen
FieldMedicine
TopicCytomegalovirus and herpesvirus research
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineGanciclovirCytomegalovirusAsymptomaticRegimenInternal medicineLiver transplantationGastroenterologyTransplantationDiseaseBetaherpesvirinaeImmunologyHuman cytomegalovirusViral diseaseHerpesviridaeVirus

Abstract

fetched live from OpenAlex

BACKGROUND: We studied the economic impact of cytomegalovirus (CMV) disease and its effective reduction with antiviral prophylaxis in liver transplant recipients. METHOD: Analysis of institutional charge data accumulated during a prospective, randomized, controlled trial comparing oral acyclovir 800 mg four times daily for 120 days (ACV) and intravenous ganciclovir 5 mg/kg every 12 h for 14 days followed by ACV for 106 days (GCV) was performed. RESULTS: Liver transplant recipients who developed CMV disease had significantly higher charges (median: $148,300) than those who developed asymptomatic CMV infection ($119,600) or experienced no CMV infection ($114,100) (P<0.01). A multiple linear regression analysis indicated that CMV disease is associated with a 49% increase in charges, independent of other factors influencing increased hospitalization charges. In CMV-seronegative patients who received a CMV-seropositive donor organ, GCV prophylaxis was associated with a significant reduction in charges, as compared to ACV prophylaxis ($113,900 vs. $153,300, respectively; P=0.02). CONCLUSIONS: CMV disease is an independent risk factor for increased resource utilization associated with liver transplantation. The use of an effective prophylactic antiviral regimen provides savings in health care resources, particularly in patients at high risk for developing CMV disease.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.776
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.307
Teacher spread0.291 · 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

Citations83
Published2000
Admission routes1
Has abstractyes

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