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Hospitalizations and mortality among patients with fetal alcohol spectrum disorders: a prospective study.

ABSTRACT: With nearly 10% of women consuming alcohol during pregnancy, fetal alcohol spectrum disorders (FASDs) are becoming an increasing concern for clinicians and policymakers interested in the field of healthcare. Known as the range of mental and/or physical disabilities that occur among individuals with prenatal alcohol exposure, FASDs can result in dysmorphic features, problems with physical growth, neurobehavioral and cognitive problems that not only increase risk of various diseases, but also premature mortality. We investigated whether the diagnosis of FASDs result in increased risk of hospitalizations and mortality, with respect to FASD domains and relative diseases, when age effects are controlled for. The data for this study was taken from the National Health Insurance Service - National Sample Cohort (NHIS-NSC) between 2003 and 2013. The population attributable risk (PAR) statistic was used to estimate the percentage of hospitalizations and mortality attributable to FASDs and other factors. A time-dependent Cox proportional hazards model with age of diagnosis as the time-scale was employed to calculate adjusted hazard ratios and 95% CIs for hospitalizations and mortality among FASD populations compared to their general population peers. Among the 3,103 FASD cases, 27.5% experienced hospitalizations and 12.5% died. Overall, FASDs accounted for 853 FASD-attributable hospitalizations (51.0% of all hospitalizations in the study population) and 387 mortality events (34.5% of all deaths in the study population). 20.52% of hospitalizations and 21.35% of mortalities were attributable to FASDs in this population. Compared to the control group, FASD patients had a 1.25-fold (HR: 1.25, 95% CI: 1.05-1.49, p?=?0.0114) increased risk of hospitalizations and a 1.33-fold (HR: 1.33, 95% CI: 1.07-1.67, p?=?0.0118) increased risk of all-cause mortality. The most common cause for hospitalization was diseases of the nervous system, which accounted for 450 FASD-attributable hospitalizations (96.2% of all nervous system hospitalizations in the study population). In fact, FASD patients were 52 times more likely to be hospitalized for nervous system diseases than their peers (HR: 51.78, 95% CI: 29.09-92.17, p?

SUBMITTER: Oh SS

PROVIDER: S-EPMC7658994 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Hospitalizations and mortality among patients with fetal alcohol spectrum disorders: a prospective study.

Oh Sarah Soyeon SS Kim Young Ju YJ Jang Sung-In SI Park Sohee S Nam Chung Mo CM Park Eun-Cheol EC

Scientific reports 20201111 1

With nearly 10% of women consuming alcohol during pregnancy, fetal alcohol spectrum disorders (FASDs) are becoming an increasing concern for clinicians and policymakers interested in the field of healthcare. Known as the range of mental and/or physical disabilities that occur among individuals with prenatal alcohol exposure, FASDs can result in dysmorphic features, problems with physical growth, neurobehavioral and cognitive problems that not only increase risk of various diseases, but also prem ...[more]

PMID: 33177533

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Project description:The pathology of fetal alcohol syndrome and the less severe fetal alcohol spectrum disorders includes brain dysmyelination. Recent studies have shed light on the molecular mechanisms underlying these white matter abnormalities. Rodent models of fetal alcohol syndrome and human studies have shown suppressed oligodendrocyte differentiation and apoptosis of oligodendrocyte precursor cells. Ethanol exposure led to reduced expression of myelin basic protein and delayed myelin basic protein expression in rat and mouse models of fetal alcohol syndrome and in human histopathological specimens. Several studies have reported increased expression of many chemokines in dysmyelinating disorders in central nervous system, including multiple sclerosis and fetal alcohol syndrome. Acute ethanol exposure reduced levels of the neuroprotective insulin-like growth factor-1 in fetal and maternal sheep and in human fetal brain tissues, while ethanol increased the expression of tumor necrosis factor α in mouse and human neurons. White matter lesions have been induced in the developing sheep brain by alcohol exposure in early gestation. Rat fetal alcohol syndrome models have shown reduced axon diameters, with thinner myelin sheaths, as well as reduced numbers of oligodendrocytes, which were also morphologically aberrant oligodendrocytes. Expressions of markers for mature myelination, including myelin basic protein, also were reduced. The accumulating knowledge concerning the mechanisms of ethanol-induced dysmyelination could lead to the development of strategies to prevent dysmyelination in children exposed to ethanol during fetal development. Future studies using fetal oligodendrocyte- and oligodendrocyte precursor cell-derived exosomes isolated from the mother's blood may identify biomarkers for fetal alcohol syndrome and even implicate epigenetic changes in early development that affect oligodendrocyte precursor cell and oligodendrocyte function in adulthood. By combining various imaging modalities with molecular studies, it may be possible to determine which fetuses are at risk and to intervene therapeutically early in the pregnancy.

Project description:Fetal alcohol spectrum disorders (FASD) describe many of the well-known neurodevelopmental deficits afflicting children exposed to alcohol in utero. The effects of alcohol on the maternal-fetal interface, especially the placenta, have been less explored. We herein hypothesized that chronic binge alcohol exposure during pregnancy significantly alters the placental protein profile in a rat FASD model.Pregnant rats were orogastrically treated daily with alcohol (4.5 g/kg, gestational day [GD] 5 to 10; 6.0 g/kg, GD 11 to 19) or 50% maltose dextrin (isocalorically matched pair-fed controls). On GD 20, placentae were collected, flash-frozen, and stored until tissues were homogenized. Protein lysates were denatured, reduced, captured on a 10-kDa spin filter, and digested. Peptides were eluted, reconstituted, and analyzed by a Q Exactive™ Hybrid Quadrupole-Orbitrap™ mass spectrometer.Mass spectrometry (MS) analysis identified 2,285 placental proteins based on normalized spectral counts and 2,000 proteins by intensity-based absolute quantification. Forty-five placental proteins were significantly (p < 0.05) altered by gestational alcohol exposure by both quantification approaches. These included proteins directly related to alcohol metabolism; specific isoforms of alcohol dehydrogenase and aldehyde dehydrogenase were up-regulated in the alcohol group. Ingenuity analysis identified ethanol degradation as the most significantly altered canonical pathway in placenta, and fetal/organ development as most altered function, with increased risk for metabolic, neurological, and cardiovascular diseases. Physiological roles of the significantly altered proteins were related to early pregnancy adaptations, implantation, gestational diseases, fetal organ development, neurodevelopment, and immune functions.We conclude that the placenta is a valuable organ not only to understand FASD etiology but it may also serve as a diagnostic tool to identify novel biomarkers for detecting the outcome of fetal alcohol exposure. Placental MS analysis can offer sophisticated insights into identifying alcohol metabolism-related enzymes and regulators of fetal development.

Project description:BackgroundFetal alcohol syndrome (FAS) is a lifelong developmental disability that occurs among individuals with prenatal alcohol exposure (PAE). With improved prediction models, FAS can be diagnosed or treated early, if not completely prevented.ObjectiveIn this study, we sought to compare different machine learning algorithms and their FAS predictive performance among women who consumed alcohol during pregnancy. We also aimed to identify which variables (eg, timing of exposure to alcohol during pregnancy and type of alcohol consumed) were most influential in generating an accurate model.MethodsData from the collaborative initiative on fetal alcohol spectrum disorders from 2007 to 2017 were used to gather information about 595 women who consumed alcohol during pregnancy at 5 hospital sites around the United States. To obtain information about PAE, questionnaires or in-person interviews, as well as reviews of medical, legal, or social service records were used to gather information about alcohol consumption. Four different machine learning algorithms (logistic regression, XGBoost, light gradient-boosting machine, and CatBoost) were trained to predict the prevalence of FAS at birth, and model performance was measured by analyzing the area under the receiver operating characteristics curve (AUROC). Of the total cases, 80% were randomly selected for training, while 20% remained as test data sets for predicting FAS. Feature importance was also analyzed using Shapley values for the best-performing algorithm.ResultsOverall, there were 20 cases of FAS within a total population of 595 individuals with PAE. Most of the drinking occurred in the first trimester only (n=491) or throughout all 3 trimesters (n=95); however, there were also reports of drinking in the first and second trimesters only (n=8), and 1 case of drinking in the third trimester only (n=1). The CatBoost method delivered the best performance in terms of AUROC (0.92) and area under the precision-recall curve (AUPRC 0.51), followed by the logistic regression method (AUROC 0.90; AUPRC 0.59), the light gradient-boosting machine (AUROC 0.89; AUPRC 0.52), and XGBoost (AUROC 0.86; AURPC 0.45). Shapley values in the CatBoost model revealed that 12 variables were considered important in FAS prediction, with drinking throughout all 3 trimesters of pregnancy, maternal age, race, and type of alcoholic beverage consumed (eg, beer, wine, or liquor) scoring highly in overall feature importance. For most predictive measures, the best performance was obtained by the CatBoost algorithm, with an AUROC of 0.92, precision of 0.50, specificity of 0.29, F1 score of 0.29, and accuracy of 0.96.ConclusionsMachine learning algorithms were able to identify FAS risk with a prediction performance higher than that of previous models among pregnant drinkers. For small training sets, which are common with FAS, boosting mechanisms like CatBoost may help alleviate certain problems associated with data imbalances and difficulties in optimization or generalization.

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Hospitalizations and mortality among patients with fetal alcohol spectrum disorders: a prospective study.

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Hospitalizations and mortality among patients with fetal alcohol spectrum disorders: a prospective study.

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