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  1. Article ; Online: A data-driven health index for neonatal morbidities.

    De Francesco, Davide / Blumenfeld, Yair J / Marić, Ivana / Mayo, Jonathan A / Chang, Alan L / Fallahzadeh, Ramin / Phongpreecha, Thanaphong / Butwick, Alex J / Xenochristou, Maria / Phibbs, Ciaran S / Bidoki, Neda H / Becker, Martin / Culos, Anthony / Espinosa, Camilo / Liu, Qun / Sylvester, Karl G / Gaudilliere, Brice / Angst, Martin S / Stevenson, David K /
    Shaw, Gary M / Aghaeepour, Nima

    iScience

    2022  Volume 25, Issue 4, Page(s) 104143

    Abstract: Whereas prematurity is a major cause of neonatal mortality, morbidity, and lifelong impairment, the degree of prematurity is usually defined by the gestational age (GA) at delivery rather than by neonatal morbidity. Here we propose a multi-task deep ... ...

    Abstract Whereas prematurity is a major cause of neonatal mortality, morbidity, and lifelong impairment, the degree of prematurity is usually defined by the gestational age (GA) at delivery rather than by neonatal morbidity. Here we propose a multi-task deep neural network model that simultaneously predicts twelve neonatal morbidities, as the basis for a new data-driven approach to define prematurity. Maternal demographics, medical history, obstetrical complications, and prenatal fetal findings were obtained from linked birth certificates and maternal/infant hospitalization records for 11,594,786 livebirths in California from 1991 to 2012. Overall, our model outperformed traditional models to assess prematurity which are based on GA and/or birthweight (area under the precision-recall curve was 0.326 for our model, 0.229 for GA, and 0.156 for small for GA). These findings highlight the potential of using machine learning techniques to predict multiple prematurity phenotypes and inform clinical decisions to prevent, diagnose and treat neonatal morbidities.
    Language English
    Publishing date 2022-03-22
    Publishing country United States
    Document type Journal Article
    ISSN 2589-0042
    ISSN (online) 2589-0042
    DOI 10.1016/j.isci.2022.104143
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: The Society for Obstetric Anesthesia and Perinatology Coronavirus Disease 2019 Registry: An Analysis of Outcomes Among Pregnant Women Delivering During the Initial Severe Acute Respiratory Syndrome Coronavirus-2 Outbreak in the United States.

    Katz, Daniel / Bateman, Brian T / Kjaer, Klaus / Turner, Dana P / Spence, Nicole Z / Habib, Ashraf S / George, Ronald B / Toledano, Roulhac D / Grant, Gilbert / Madden, Hannah E / Butwick, Alex J / Lynde, Grant / Minehart, Rebecca D / Beilin, Yaakov / Houle, Timothy T / Sharpe, Emily E / Kodali, Bhavani / Bharadwaj, Shobana / Farber, Michaela K /
    Palanisamy, Arvind / Prabhu, Malavika / Gonzales, Nikolai Y / Landau, Ruth / Leffert, Lisa

    Anesthesia and analgesia

    2021  Volume 133, Issue 2, Page(s) 462–473

    Abstract: Background: Early reports associating severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection with adverse pregnancy outcomes were biased by including only women with severe disease without controls. The Society for Obstetric Anesthesia ... ...

    Abstract Background: Early reports associating severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection with adverse pregnancy outcomes were biased by including only women with severe disease without controls. The Society for Obstetric Anesthesia and Perinatology (SOAP) coronavirus disease 2019 (COVID-19) registry was created to compare peripartum outcomes and anesthetic utilization in women with and without SARS-CoV-2 infection delivering at institutions with widespread testing.
    Methods: Deliveries from 14 US medical centers, from March 19 to May 31, 2020, were included. Peripartum infection was defined as a positive SARS-CoV-2 polymerase chain reaction test within 14 days of delivery. Consecutive SARS-CoV-2-infected patients with randomly selected control patients were sampled (1:2 ratio) with controls delivering during the same day without a positive test. Outcomes were obstetric (eg, delivery mode, hypertensive disorders of pregnancy, and delivery <37 weeks), an adverse neonatal outcome composite measure (primary), and anesthetic utilization (eg, neuraxial labor analgesia and anesthesia). Outcomes were analyzed using generalized estimating equations to account for clustering within centers. Sensitivity analyses compared symptomatic and asymptomatic patients to controls.
    Results: One thousand four hundred fifty four peripartum women were included: 490 with SARS-CoV-2 infection (176 [35.9%] symptomatic) and 964 were controls. SARS-CoV-2 patients were slightly younger, more likely nonnulliparous, nonwhite, and Hispanic than controls. They were more likely to have diabetes, obesity, or cardiac disease and less likely to have autoimmune disease. After adjustment for confounders, individuals experiencing SARS-CoV-2 infection exhibited an increased risk for delivery <37 weeks of gestation compared to controls, 73 (14.8%) vs 98 (10.2%) (adjusted odds ratio [aOR], 1.47; 95% confidence interval [CI], 1.03-2.09). Effect estimates for other obstetric outcomes and the neonatal composite outcome measure were not meaningfully different between SARS-CoV-2 patients versus controls. In sensitivity analyses, compared to controls, symptomatic SARS-CoV-2 patients exhibited increases in cesarean delivery (aOR, 1.57; 95% CI, 1.09-2.27), postpartum length of stay (aOR, 1.89; 95% CI, 1.18-2.60), and delivery <37 weeks of gestation (aOR, 2.08; 95% CI, 1.29-3.36). These adverse outcomes were not found in asymptomatic women versus controls. SARS-CoV-2 patients (asymptomatic and symptomatic) were less likely to receive neuraxial labor analgesia (aOR, 0.52; 95% CI, 0.35-0.75) and more likely to receive general anesthesia for cesarean delivery (aOR, 3.69; 95% CI, 1.40-9.74) due to maternal respiratory failure.
    Conclusions: In this large, multicenter US cohort study of women with and without peripartum SARS-CoV-2 infection, differences in obstetric and neonatal outcomes seem to be mostly driven by symptomatic patients. Lower utilization of neuraxial analgesia in laboring patients with asymptomatic or symptomatic infection compared to patients without infection requires further investigation.
    MeSH term(s) Adult ; Analgesia, Obstetrical ; Anesthesia, General ; Anesthesia, Obstetrical ; COVID-19/complications ; COVID-19/diagnosis ; Case-Control Studies ; Cesarean Section ; Delivery, Obstetric/adverse effects ; Female ; Gestational Age ; Humans ; Infant, Premature ; Pregnancy ; Pregnancy Complications, Infectious/diagnosis ; Premature Birth/etiology ; Registries ; Risk Assessment ; Risk Factors ; United States ; Young Adult
    Language English
    Publishing date 2021-04-23
    Publishing country United States
    Document type Journal Article ; Multicenter Study
    ZDB-ID 80032-6
    ISSN 1526-7598 ; 0003-2999
    ISSN (online) 1526-7598
    ISSN 0003-2999
    DOI 10.1213/ANE.0000000000005592
    Database MEDical Literature Analysis and Retrieval System OnLINE

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