Tuesday, June 4, 2019

Effects of Adverse Perinatal Outcomes (APO)

Effects of Adverse Perinatal Outcomes (APO)Specific AimsAdverse perinatal outcomes (APO) include infants induce defects, maternal meaning(a) and obstetrical complications. receive defects, including major congenital malformation (MCM) and minor anomaly (MA), become the leading ca dos of infant morbidity, mortality, and years of potential life lost in the join States.1 Low stock weight (LBW), abnormal condition of new born (ACNB), preterm throw, and Developmental Delay or Disability (DDD) argon also ancestry anomalies that impacts the infants wellness.2-5The tie beam of in utero painting to teratogenic medications with infant pitch defects and other anomalies has been astray investigated.6,7 The literature has shown that taking antiepileptic drugs (AEDs) poses an increased venture of having child with congenital malformations in women with epilepsy.79 The most common MCMs ca usanced by in utero exposure to AEDs are orofacial clefts, cardiac abnormalities, neural tube defect s, urologic defects, and skeletal abnormalities.80 In utero exposure to valproate, the most teratogenic AED, was associated with raise risk of impaired cognitive function for children at 3 years of age, and reduced cognitive abilities for children at 6 years old.98,101 However, orbit results for m whatever medications, much(prenominal) as antidepressants, opioids, antipsychotics, and antibiotics, are inconsistent for fetal safety.1*-8* The limited data source and rare incidence of induce defects, ACNBs, and other anomalies restrain the study power, and makes some studies inconclusive.8-10 Our great term goal is to determine the association betwixt teratogenic effects of medications that mothers exposed during motherhood and infants birth defects. The major objective of this study is to build a link database in Rhode Island (RI) to facilitate the subsequent research on teratogenic effects of medication in RI population.The birth defects and birth certificates data from the De partment of health (DoH) and chemists cl masterminds from the Medicaid program offer an necessary resource to investigate these aims. The availability of hospital diagnoses and birth eternalizes offers a signifi push asidet advantage for investigating birth defects with same clinical conditions in large population with a longitudinal onslaught.Our team is well suited to conduct this research given extensive expertise in contemporary pharmacoepidemiology, m distributively years of experience on drug safety research, prior drug utilization and birth defects study with the linked data from some other state, and clinical expertise from obstetric and gynecologic physicians.Our particular(prenominal) aims are to generate a linked data and investigate the medication utilization and assess the check birth defects with the fol sm any(a)ing effortsAim 1 To build a linked database that includes mothers medications prescribed during pregnancy and subsequent adverse perinatal outcomes. We hypothesize that the data from cardinal state departments can be internally linked using identifiers. Mothers medication prescriptions al low-down be extracted from Medicaid claims provided by the RI Executive Office of Health Human service (EOHHS). The adverse perinatal outcomes include MCMs, MAs, abnormal conditions of new born, fetal death, and low birth weight, and maternal adverse pregnancy and obstetrical complications. All of these outcomes will be obtained from birth certificates, institutional and professional claims that are collected and managed by RI Department of Health (DoH). These two parts of data will be linked by the deterministic or probabilistic linking strategy using mothers medical record number, cry, and hear of born. We will apply for IRB approval with a waiver of informed take on by RI DoH, EOHHS, Brown, and URI.Aim 2 To characterize the patterns of medication use in women during pregnancy.We hypothesize that medication use in women during pregnancy changes in recent years. many medications, such as AEDs, statin, or angiotensin converting enzyme (ACE), trait been classified as teratogens and categorized as D or X by the Food and drug Administration (FDA). However, studies have set that these teratogenic drugs still have been prescribed to pregnant women.5-7 Some medications with contradictive results reported from the literature may have increased use in pregnant women. We will examine the prescribing patterns of these medications in pregnant women with varied age, race, comorbidities, co-medications, as well as medication types and doses. The utilization pattern will be delineated in secular trends and mapped geographically, as will facility, provider, and state-level variations.Aim 3 To assess infants birth defects and birth anomalies using advanced statistical model.We will rank all corresponding birth defects, including MCM, MA, LBW, ACNB, DDD, preterm birth, and fetal death and compare the birth defect rates in mothe rs with varied demographic characteristics and medication exposure. Previous studies have suggested that the LVM can be used to combine four specific birth defects together to create a severity forefinger.16-18 We hypothesize that this LVM can be modify and optimized to combine any number of fortunes with a proper weight on severity and frequency to evaluate the general health status of infants.B. Significance and foundingBirth defects lapse in 3 5% of children born in the United States and account for 20% of all infant deaths.1,2 During 2010-2012, RI DoH identified 1,390 newborns with at least one birth defect.3 The rate of birth defects in RI increased by 14.2% from 2008 to 2012.3 It was reported that 2-3% of birth defects are due to teratogen-induced malformations, which refer to malformations resulting from environmental or in utero exposure to teratogens.4 In the United States, about 3 million people currently suffer with teratogen-induced malformations.4The FDA defin ed the pregnancy category to enforce the labeling of drugs with compliments to their effects on pregnant women. Some medications, such as AEDs, statin, or ACEs, have been classified in FDA pregnant category D or X due to their teratogenic effects. Previous studies reported a two- to three-fold increase in the malformation rate among infants with in utero exposure to AEDs.21,22,81,82 The incidence rates in infants with in utero exposure to AEDs were 3.1% to 9.0% for MCMs, 37% for one MA, and 11% for two MAs.21,80-83 The risk of malformations for infants with in utero exposure to valproate is 7.3-fold higher(prenominal) than that of non-exposed, and 4-fold higher than those exposed to all other AEDs.7Some widely used medications, such as antidepressants, opioids, antipsychotics, and antibiotics, tend to have increased utilization in pregnant women while the results from teratogenic studies are controversial and inclusive.1*-8* It is difficult to none between the real non-inferior r esults and power deficiency owing to rare outcomes.It has led to an urgent need to determine the fetal safety of these medications and prevent teratogenic medications prescribing to pregnant women. However, the limited data source and rare incidence of birth defect outcomes impact the study power, and makes studies inconclusive.8-10 Traditional claims data (data from Medicaid or private health plans) is not suitable for birth defect research as it only contains medical information for either mother or infant, not both. Birth certificates or birth defects data doesnt include mothers medication information. As such, to investigate utilization patterns and teratogenic effects of medications, we need to link mothers pharmacy claims with infants birth defects assessments. The linkage should be conducted in a secure data server with patients identifiers.The main goal of this proposed one-year pilot study is to collaborate with the RI EOHHS and RI DOH and generate a linked comprehensive d ataset that includes mothers pharmacy claims and infants birth defect outcomes. This linked dataset will facilitate the researchers in Brown and URI to conduct studies regarding drug-induced birth defects in RI and provide a potential for cartel RI linked data with the linked data from other states to conducting drug teratogenic studies in large population.InnovationThis proposed study will generate a linked data with combining Medicaid pharmacy claims from the RI EOHHS and birth certificates and birth defects from the RI DOH. This would make RI become the fourth state that possesses the linked mother-infant data in the United States, besides California, Texas, and Florida. Our move up will provide a large linked dataset to facilitate the researchers from URI and Brown to conduct drug-induced birth defects studies. This linked dataset will provide a potential for succeeding(a) drug teratogenic research in large population with combining the RI linked data with the linked data fro m other states.Our approach will pursue state of the art, innovative pharmacoepidemiologic study designs and statistical models, to improve the study power and efficiency. A potential variable model will be employed in this study to combine all birth defects outcomes into a continuous severity score to assess the overall infants morbidity and mortality.C. ApproachData SourcesThis study is establish on a statewide, retrospective 11-year data sources RI birth certificates and birth defects from January 1, 2006 to December 31, 2016. In Rhode Island, birth certificates are collected in the hospital within 24 to 48 hours aft(prenominal) the baby birth. The RI DoH collects and manages birth certificate data for all infants born in RI. Birth determines and places for infants, and demographic characteristics for infants, mothers, and fathers are all record in birth certificates. The RI Birth Defects dataset consists of birth defects registry data prepared and maintained by RI DoH. Infan t birth defects, including MCMs and MAs, were identified 0-365 old age after live birth from hospital inpatient and outpatient claims. This study includes infants who were born in RI between January 01, 2006 and December 31, 2016.Medication information will be provided by the RI EOHHS. The data is comprised of eligibility, medical, and pharmacy claims for services from inpatient hospitals, outpatient clinics, emergency rooms, and pharmacies from January 01 2005 to December 31 2016. Brief demographics for enrolled members are included in Medicaid claims data, such as age, gender, race, residency, etc.Medicaid claims data do not include claims for managed conduct or Medicare enrollees. We excluded patients with dual eligibility, and thus restricted the drug exposure cohort to pregnant women who were only in the fee-for-service or primary care case management program.Each data source will be cleaned first, and then linked with other corresponding datasets using a multi-step linkage ap proach in which three methods of linkage are applied in sequence Deterministic, Fuzzy Matching, and Probabilistic.156 Records will be first matched deterministically, base on exact matches of erratic combinations of personal identifiers including Social Security Numbers, Date of Birth, and Mothers Names (used for the linkage of BVS to Medicaid only). Records that cannot be exactly matched due to missing or poor data quality will be linked using Fuzzy Matching.156,157 Fuzzy Matching allows at least one occurrence of Social Security Number digit transpositions, name misspelling, or day or month errors in birth date fields.157Remaining unmatched records will be linked using probabilistic techniques, based on statistical weighting of combinations of personal identifiers. Probabilistic linkage involved a two-step process. 1) Deterministic matching from the first merging step by trial and error derived weights to the non-missing fields based on successful linkages. 2) After the unlinke d data matched with several records by weights, the matches with the highest statistical probability (indicating by high weights) will be chosen. The record remained unmatched when no high weights could be obtained.Study CohortThis study includes female Rhode Island Medicaid enrollees who were older than 15 years of age, delivered a live singleton infant between January 01, 2006 and December 31, 2016, and are enrolled in the Medicaid program as identified by pregnancy status. The study cohort of mother-infant pairs will be generated by linking the Rhode Island Medicaid claims data and Rhode Island Birth defects data using strategies distinguishd above.Many women joined the Medicaid program after becoming pregnant. We excluded the women who were enrolled in Medicaid program after a positive pregnant test. more than exclusion criteria for maternal-infant pair include mothers with less than 6 months of Medicaid eligibility before pregnancy mothers who lost Medicaid eligibility during pregnancy mothers with dual enrollment with Medicare, HMO, or other private health plans mothers giving multiple births mothers with diabetes mellitus (ICD-9-CM 249.x, 250.x, 790.29, or used of any antidiabetics during baseline), hypertension (ICD-9-CM 401.x, 416.x, 796.2, , 997.91, 459.3, or used of any antihypertensive drugs during baseline), or HIV pre-pregnancy (ICD-9-CM 042, 079.53, V08, V01.79, 795.71, or used of any antiretroviral drugs) Infants who were twins, triplets, quadruplets or more outliers involving infants with birth weight less than 350 g or above 6000 g mothers or infants missing critical information, such as infants birth weight, mothers demographic information, or perinatal medical information. Only less than 1% of infants are missing birth weight records in the birth certificate, these will be excluded from the study.20Overall Study DesignThis is a retrospective cohort study based on linked mothers Medicaid claims and state birth registry data. The infants bi rth date will be the study index date. The drug exposure window will be defined as the subsequent 9-month pregnancy consequence after the first day of mothers last menstrual date. We will use a 6-month baseline period prior to the first date of mothers last menstrual date to obtain the baseline demographic and clinical information. Birth defect outcomes will be detected 0-365 days after the live birth. The entire study period lasts from January 01 2005 to December 31 2016.Drug ExposurePharmacy claims in Medicaid have been approved as an accurate source for the assessment of drug exposure in observational studies.158 Mothers medication exposure during pregnancy will be obtained from Medicaid pharmacy claims using NDC codes for filled prescription medications, and the number of days for which the medication is supplied.160 The birth anomalies are associated with exposure during entire pregnancy, MCM relates to the teratogen exposure during the first trimester, and MA and LBW associat es with the maternal medication exposure at the third trimester.161 Maternal medication exposure during entire pregnancy period can affect the occurrence of varied birth defects. The exposure window, thus, will be established as a period of 14 days prior to the first day of the mothers last menstrual period (LMP) to the date when infant is born. The drug exposure will be defined as any one dose of study medications dispensed during the exposure window, including which the medication is dispensed before the exposure window but its supply days cover at least 1 day of the exposure window. Adding 14 days prior to the pregnancy is to include the conception period and the residual effects of medications. Sensitivity study will be conducted to examine the different definitions of medication exposure windows.The mothers LMP will be obtained from birth certificates. If the dates are not available in birth certificates (about 13% of LMP in birth certificates are missing), then this informatio n will be imputed from clinical estimates.163-165 The literature suggests that LMP from birth certificates and clinical estimates agrees within 2 calendar weeks.166Outcome sound judgmentIn this study, we will identify all individual adverse infant outcomes birth defects (involving MCM and MA), ACNB, LBW, DDD, and preterm birth from the DoH birth defects data.MCM is defined as an abnormality of an essential anatomic structure that is present at birth and interferes significantly with function and/or requires major intervention.38,39 MCM includes heart malformations, urological defects, oro-facial defects, neural tube defects, and skeletal abnormalities, etc..38,40,41 Drug-induced MCMs mostly occur between the third and eighth week of gestation.44 Any impairment before three weeks is more likely to result in fatality. The fetus becomes less handsome to teratogenic effects after the eighth week, when the organs have developed. 2-1 delineates the time window of exposure to teratogens and associated MCMs and MAs.44 MA, also called minor congenital malformations, is the abnormal morphologic feature that does not cause serious medical or cosmetic consequences45. Identification of MA can be difficult due to the definition and the easy-variable occurrence area.46 or so 70% of MAs occur on the face or hands.46 The prevalence of MA is less than 4% in the general population, and varies by race, ethnicity, and gender.45,46 In healthy newborns, about 15% to 20% have one MA, 0.8% have two MAs, and 0.5% have three or more MAs.46 MA mostly occurs after the eighth week of gestation, which is so-called fetal period.44 The use of teratogens during this period may induce MAs by disturbing the growth of tissues or organs.44 ACNB includes seven medical conditions for new born infants. Infants birth weight less than 2500g, 1500g, and 1000g are categorized respectively as low birth weight (LBW), very low birth weight (VLBW), and extremely low birth weight (ELBW). Infants with low birth weight are likely to be born before 37 weeks of pregnancy. In 2009, 8.16% of live born infants showed low birth weight.50 The high risk of infant mortality and morbidity associated with low birth weight has been documented.51 Although this positive association has been ameliorated over time with improved perinatal technology and intensive care, low birth weight and prematurity still have been identified as risk factors predisposing to cardiovascular dysfunction, lung disorder, hypertension, type 2 diabetes, renal diseases, autism, and developmental delay.52-56MCM, MA, DDD, and fetal death will be collected from birth to the first 365 days of life using the ICD-9 CM code (740-759.9, 315, 768.0, 768.1) from inpatient and outpatient claims. ACNB and preterm birth will be identified from Rhode Island birth certificatedata, and one year follow ups in infant hospital discharge data. Infant birth weight is accurately recorded in the birth certificate.19It was noted in previous studie s that these birth defects outcomes are highly related to each other.59,70-75 MCM, MA, VLBW, and ELBW relate to significant morbidity, mortality, and childhood deterioration or serious pregnancy or obstetric complications. 58,70-75 About 6-42% of evolving cognitive dysfunction, 9-26% of neurosensory disabilities, 1-15% of blindness, and 0-9% of deafness occurred in infants born with VLBW and ELBW.71 A significantly higher risk of DDD was found in infants born with MCM (prevalence rate 8.3, 95%CI 7.6-9.0).72 A 44% 86% of mortality rate occurs in infants with ELBW (500-750g).73 Moreover, infants with 1, 2, or 3 MAs had a risk rate of corresponding MCMs at 3%, 10%, or 20%, respectively.46Some risk factors, such as infant gender, maternal age, race, social-economic status, BMI, smoking, alcohol use, nulliparity, comorbidity, and comedication during pregnancy are risk factors for all of these outcomes.75-78Latent Variable ModelLiu and Roth developed an LVM to incorporate four important BD outcomes into a single measurement, the infant morbidity index, to describe an infants overall tendency to BD.13 We will apply this model to combine all birth defects outcomes defined in this study into a continuous index of overall adverse perinatal outcome (APO) in this study. The combined outcome will be evaluated in terms of validity and reliability to ensure the appropriate use of this new methodology.MCM, MA, ACNB, Fetal Death, and DDD will be categorized as a binary variable, and assumed Bernoulli distributed.21 Four levels of LBW will be modeled as a multinomial variable since the four birth weight categories are mutually exclusive and each has its own probability. The summation of the individual probabilities of birth defects outcomes equals one. The unobserved index score will be assumed log-normally distributed. Based upon the assumption of local independence, responses of individual component outcomes are independent given the latent variable.22,23 Thus, the overall probabilities of component outcomes conditional on the latent variable are equal to the products of conditional probability for each individual component outcome.21Based on the local independence and Bayes rule, the joint distribution for component outcomes can be expressed as an integral of product of multinomial variable for conditional distribution of each component outcome and marginal distribution of latent variable.22-24 Marginal distribution of the latent variable is described as log normal. Given the observed outcomes, we can obtain the posterior distribution of the latent severity score.Furthermore, we assume that the conditional distribution of each categorical observed outcome is nonlinear function of the latent variable.13 The conditional distribution of observed outcome and the latent variable will be linked by two parameters in the non-linear function.The probability of any specific observed outcome equals to 0 when the value of the latent variable equals to 0 because the latent variable accounts for all variation of the observed component outcomes and the relationship among these component outcomes.13 In the non-linear function, the probability of an infant having an individual birth defect outcome is assumed zero if the latent variable is zero, and every normal level (no birth defect or normal weight) will be treated as a reference. The latent variable positively associates with observed outcomes. The larger the latent variable, the higher the probability of the observed outcome.13Latent Trait Model will be conducted using SAS Proc IML. The proportion of each outcome combination will be calculated. thusly each parameter will be estimated using the iteration function for EGNLS starting from iteration 0 with initialized value until the stepping coefficient is less than 10-9. The final results are the estimates of all parameters. The estimate of latent variable will be obtained by entering the computed parameters into posterior function.13 Sensi tivity StudiesIn order to examine the proper definition of exposure window, sensitive studies will be conducted with the exposure window defined as the period of 3, 7, 21, or 30 days prior to the first day of the mothers LMP to the infants birth date.D. TimelineTable. Study Timeline of the Study.Time PeriodStudy ProgressBefore 07/01/2017Obtain IRB approval from URI, Brown, RI DoH, and RI EOHHS. Complete DUA with RI DoH and RI EOHHS.07/01/2017 08/01/2017Complete data linkage for specific aim 108/01/2017 10/01/2017Complete data cleaning, manipulating, variable editing, andanalyses for demographic and clinical characteristics10/01/2017 01/31/2018Complete specific aim 202/01/2018 02/28/2018 require an abstract to the annual meeting of International Society of Pharmacoepidemiology (ISPE)03/01/2018 06/30/2018Complete specific aim 3 and submit a journal article

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