ORCID Profile
0000-0002-8422-9907
Current Organisation
Universidade Estadual Paulista Júlio de Mesquita Filho
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Publisher: Elsevier BV
Date: 2016
DOI: 10.1016/J.PREGHY.2015.12.002
Abstract: A common challenge in medicine, exemplified in the analysis of biomarker data, is that large studies are needed for sufficient statistical power. Often, this may only be achievable by aggregating multiple cohorts. However, different studies may use disparate platforms for laboratory analysis, which can hinder merging. Using circulating placental growth factor (PlGF), a potential biomarker for hypertensive disorders of pregnancy (HDP) such as preecl sia, as an ex le, we investigated how such issues can be overcome by inter-platform standardization and merging algorithms. We studied 16,462 pregnancies from 22 study cohorts. PlGF measurements (gestational age ⩾20 weeks) analyzed on one of four platforms: R&D Systems, AlereTriage, RocheElecsys or AbbottArchitect, were available for 13,429 women. Two merging algorithms, using Z-Score and Multiple of Median transformations, were applied. Best reference curves (BRC), based on merged, transformed PlGF measurements in uncomplicated pregnancy across six gestational age groups, were estimated. Identification of HDP by these PlGF-BRCs was compared to that of platform-specific curves. We demonstrate the feasibility of merging PlGF concentrations from different analytical platforms. Overall BRC identification of HDP performed at least as well as platform-specific curves. Our method can be extended to any set of biomarkers obtained from different laboratory platforms in any field. Merged biomarker data from multiple studies will improve statistical power and enlarge our understanding of the pathophysiology and management of medical syndromes.
Publisher: Springer Science and Business Media LLC
Date: 07-10-2019
DOI: 10.1186/S12884-019-2445-X
Abstract: Preecl sia (PE) is a major cause of short and long-term morbidity for affected infants, including consequences of fetal growth restriction and iatrogenic prematurity. In Brazil, this is a special problem as PE accounts for 18% of preterm births (PTB). In the PREPARE (Prematurity REduction by Pre-ecl sia cARE) study, we will test a novel system of integrated care based on risk stratification and knowledge transfer, to safely reduce PTB. This is a stepped wedge cluster randomised trial that will include women with suspected or confirmed PE between 20 + 0 and 36 + 6 gestational weeks. All pregnant women presenting with these findings at seven tertiary centres in geographically dispersed sites, throughout Brazil, will be considered eligible and evaluated in terms of risk stratification at admission. At randomly allocated time points, sites will transition to risk stratification performed according to sFlt-1/PlGF (Roche Diagnostics) measurement and fullPIERS score with both results will be revealed to care providers. The healthcare providers of women stratified as low risk for adverse outcomes (sFlt-1/PlGF ≤38 AND fullPIERS 10% risk) will receive the recommendation to defer delivery. sFlt-1/PlGF will be repeated once and fullPIERS score twice a week. Rates of prematurity due to preecl sia before and after the intervention will be compared. Additionally, providers will receive an active program of knowledge transfer about WHO recommendations for preecl sia, including recommendations regarding antenatal corticosteroids for foetal benefits, antihypertensive therapy and magnesium sulphate for seizure prophylaxis. This study will have 90% power to detect a reduction in PTB associated with PE from a population estimate of 1.5 to 1.0%, representing a 33% risk reduction, and 80% power to detect a reduction from 2.0 to 1.5% (25% risk reduction). The necessary number of patients recruited to achieve these results is 750. Adverse events, serious adverse events, both anticipated and unanticipated will be recorded. The PREPARE intervention expects to reduce PTB and improve care of women with PE without significant adverse side effects. If successful, this novel pathway of care is designed for rapid translation to healthcare throughout Brazil and may be transferrable to other low and middle income countries. ClinicalTrials.gov : NCT03073317.
Publisher: Elsevier BV
Date: 07-2018
Location: Brazil
No related grants have been discovered for Leandro De Oliveira.