Evidence map›Paper›PMID 33202102›Full record

Observational studyClinical and translational science2021

Predictors of Adverse Events and Determinants of the Voriconazole Trough Concentration in Kidney Transplantation Recipients.

Yi-Chang Zhao, Xiao-Bin Lin, Bi-Kui Zhang, Yi-Wen Xiao, Ping Xu, Feng Wang, Da-Xiong Xiang, Xu-Biao Xie, Feng-Hua Peng, Miao Yan

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in Clinical and translational science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
0.2field-weighted citation impact, top 32% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 16 citations in OpenAlex.

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  8. Comparison of LC-MSMolecules (Basel, Switzerland) · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 1 country.

Yi-Chang ZhaoDepartment of Clinical Pharmacy, The Second Xiangya Hospital of Central South University, Changsha, China.
Xiao-Bin LinDepartment of Pharmacy, the First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Bi-Kui ZhangDepartment of Clinical Pharmacy, The Second Xiangya Hospital of Central South University, Changsha, China.
Yi-Wen XiaoDepartment of Clinical Pharmacy, The Second Xiangya Hospital of Central South University, Changsha, China.
Ping XuDepartment of Clinical Pharmacy, The Second Xiangya Hospital of Central South University, Changsha, China.
Feng WangDepartment of Clinical Pharmacy, The Second Xiangya Hospital of Central South University, Changsha, China.
Da-Xiong XiangDepartment of Clinical Pharmacy, The Second Xiangya Hospital of Central South University, Changsha, China.
Xu-Biao XieDepartment of Urological Organ Transplantation, the Second Xiangya Hospital of Central South University, Changsha, China.
Feng-Hua PengDepartment of Urological Organ Transplantation, the Second Xiangya Hospital of Central South University, Changsha, China.
Miao YanDepartment of Clinical Pharmacy, The Second Xiangya Hospital of Central South University, Changsha, China.
Central South University · CNSecond Xiangya Hospital of Central South University · CNThe First Affiliated Hospital, Sun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Voriconazole is the mainstay for the treatment of invasive fungal infections in patients who underwent a kidney transplant. Variant CYP2C19 alleles, hepatic function, and concomitant medications are directly involved in the metabolism of voriconazole. However, the drug is also associated with numerous adverse events. The purpose of this study was to identify predictors of adverse events using binary logistic regression and to measure its trough concentration using multiple linear modeling. We conducted a prospective analysis of 93 kidney recipients cotreated with voriconazole and recorded 213 trough concentrations of it. Predictors of the adverse events were voriconazole trough concentration with the odds ratios (OR) of 2.614 (P = 0.016), cytochrome P450 2C19 (CYP2C19), and hemoglobin (OR 0.181, P = 0.005). The predictive power of these three factors was 91.30%. We also found that CYP2C19 phenotypes, hemoglobin, platelet count, and concomitant use of ilaprazole had quantitative relationships with voriconazole trough concentration. The fit coefficient of this regression equation was R

Indexed as

2-PyridinylmethylsulfinylbenzimidazolesAdultAntifungal AgentsCytochrome P-450 CYP2C19Dose-Response Relationship, DrugDrug Therapy, CombinationFemaleHemoglobinsHumansInvasive Fungal InfectionsKidney TransplantationMalePharmacogenomic VariantsPlatelet CountProspective StudiesVoriconazole2-PyridinylmethylsulfinylbenzimidazolesAntifungal AgentsCYP2C19 protein, humanCytochrome P-450 CYP2C19HemoglobinsilaprazoleVoriconazole

Identifiers

PMID33202102
PMCPMC7993276
OpenAlexW3104574818

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.