Dataset Information

Assessment of microalbuminuria for early diagnosis and risk prediction in dengue infections.

ABSTRACT:

Background

Dengue is the most important arboviral infection of humans. Following an initial febrile period, a small proportion of infected patients develop a vasculopathy, with children at particular risk for severe vascular leakage and shock. Differentiation between dengue and other common childhood illnesses is difficult during the early febrile phase, and risk prediction for development of shock is poor. The presence of microalbuminuria is recognized as a useful early predictor for subsequent complications in a number of other disorders with vascular involvement. Significant proteinuria occurs in association with dengue shock syndrome and it is possible that early-phase microalbuminuria may be helpful both for diagnosis of dengue and for identification of patients likely to develop severe disease.

Methodology/principal findings

We measured formal urine albumin to creatinine ratios (UACRs) in daily samples obtained from a large cohort of children with suspected dengue recruited at two outpatient clinics in Ho Chi Minh City, Vietnam. Although UACRs were increased in the 465 confirmed dengue patients, with a significant time trend showing peak values around the critical period for dengue-associated plasma leakage, urine albumin excretion was also increased in the comparison group of 391 patients with other febrile illnesses (OFI). The dengue patients generally had higher UACRs than the OFI patients, but microalbuminuria, using the conventional cutoff of 30 mg albumin/g creatinine discriminated poorly between the two diagnostic groups in the early febrile phase. Secondly UACRs did not prove useful in predicting either development of warning signs for severe dengue or need for hospitalization.

Conclusion/significance

Low-level albuminuria is common, even in relatively mild dengue infections, but is also present in many OFIs. Simple point-of-care UACR tests are unlikely to be useful for early diagnosis or risk prediction in dengue endemic areas.

SUBMITTER: Hanh Tien NT

PROVIDER: S-EPMC3551767 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Publications

Assessment of microalbuminuria for early diagnosis and risk prediction in dengue infections.

Hanh Tien Nguyen Thi NT Lam Phung Khanh PK Duyen Huynh Thi Le HT Ngoc Tran Van TV Ha Phan Thi Thanh PT Kieu Nguyen Tan Thanh NT Simmons Cameron C Wolbers Marcel M Wills Bridget B

PloS one 20130122 1

<h4>Background</h4>Dengue is the most important arboviral infection of humans. Following an initial febrile period, a small proportion of infected patients develop a vasculopathy, with children at particular risk for severe vascular leakage and shock. Differentiation between dengue and other common childhood illnesses is difficult during the early febrile phase, and risk prediction for development of shock is poor. The presence of microalbuminuria is recognized as a useful early predictor for su ...[more]

PMID: 23349922

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Project description:BACKGROUND: Currently dengue viruses (DENV) pose an increasing threat to over 2.5 billion people in over 100 tropical and sub-tropical countries worldwide. International air travel is facilitating rapid global movement of DENV, increasing the risk of severe dengue epidemics by introducing different serotypes. Accurate diagnosis is critical for early initiation of preventive measures. Different reverse transcriptase PCR (RT-PCR) methods are available, which should be evaluated and standardized. Epidemiological and laboratory-based surveillance is required to monitor and guide dengue prevention and control programmes, i.e., by mosquito control or possible vaccination (as soon as an effective and safe vaccine becomes available). OBJECTIVE: The purpose of the external quality assurance (EQA) study described is to assess the efficiency and accuracy of dengue molecular diagnosis methods applied by expert laboratories. STUDY DESIGN: A panel of 12 human plasma samples was distributed and tested for DENV-specific RNA. The panel comprised 9 samples spiked with different DENV serotypes (DENV-1 to DENV-4), including 10-fold dilution series of DENV-1 and DENV-3. Two specificity controls consisted of a sample with a pool of 4 other flaviviruses and a sample with chikungunya virus. A negative control sample was also included. RESULTS: Thirty-seven laboratories (from Europe, Middle East Asia, Asia, the Americas/Caribbean, and Africa) participated in this EQA study, and reports including 46 sets of results were returned. Performance among laboratories varied according to methodologies used. Only 5 (10.9%) data sets met all criteria with optimal performance, and 4 (8.7%) with acceptable performance, while 37 (80.4%) reported results showed the need for improvement regarding accomplishment of dengue molecular diagnosis. Failures were mainly due to lack of sensitivity and the presence of false positives. CONCLUSIONS: The EQA provides information on each laboratory's efficacy of RT-PCR techniques for dengue diagnosis and indicates for most laboratories an urgent need to improve sensitivity and specificity.

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Project description:PurposeThis study aims to develop and validate a nomogram for predicting the risk of bloodstream infections (BSI) in critically ill patients based on their admission status to the Intensive Care Unit (ICU).Patients and methodsPatients' data were extracted from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database (training set), the Beijing Friendship Hospital (BFH) database (validation set) and the eICU Collaborative Research Database (eICU-CRD) (validation set). Univariate logistic regression analyses were used to analyze the influencing factors, and lasso regression was used to select the predictive factors. Model performance was assessed using area under receiver operating characteristic curve (AUROC) and Presented as a Nomogram. Various aspects of the established predictive nomogram were evaluated, including discrimination, calibration, and clinical utility.ResultsThe model dataset consisted of 14930 patients (1444 BSI patients) from the MIMIC-IV database, divided into the training and internal validation datasets in a 7:3 ratio. The eICU dataset included 2100 patients (100 with BSI) as the eICU validation dataset, and the BFH dataset included 419 patients (21 with BSI) as the BFH validation dataset. The nomogram was constructed based on Glasgow Coma Scale (GCS), sepsis related organ failure assessment (SOFA) score, temperature, heart rate, respiratory rate, white blood cell (WBC), red width of distribution (RDW), renal replacement therapy and presence of liver disease on their admission status to the ICU. The AUROCs were 0.83 (CI 95%:0.81-0.84) in the training dataset, 0.88 (CI 95%:0.88-0.96) in the BFH validation dataset, and 0.75 (95%CI 0.70-0.79) in the eICU validation dataset. The clinical effect curve and decision curve showed that most areas of the decision curve of this model were greater than 0, indicating that this model has a certain clinical effectiveness.ConclusionThe nomogram developed in this study provides a valuable tool for clinicians and nurses to assess individual risk, enabling them to identify patients at a high risk of bloodstream infections in the ICU.

Dataset Information

Assessment of microalbuminuria for early diagnosis and risk prediction in dengue infections.

Background

Methodology/principal findings

Conclusion/significance

Publications

Assessment of microalbuminuria for early diagnosis and risk prediction in dengue infections.

Similar Datasets

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