Trajectories of antipsychotic use before and during pregnancy and associated maternal and birth characteristics

Association between maternal mental health-related hospitalisation in the 5 years prior to or during pregnancy and adverse birth outcomes: a population-based retrospective cohort data linkage study in the Northern Territory of Australia

Background

Mental health conditions prior to or during pregnancy that are not addressed can have adverse consequences for pregnancy and birth outcomes. This study aimed to determine the extent to which women's mental health-related hospitalisation (MHrH) prior to or during pregnancy was associated with a risk of adverse birth outcomes.

Methods

We linked the perinatal data register for all births in the Northern Territory, Australia, from the year 1999 to 2017, to hospital admissions records to create a cohort of births to women aged 15-44 years with and without MHrH prior to or during pregnancy. We used Modified Poisson Regression and Latent Class Analysis to assess the association between maternal MHrH and adverse birth outcomes (i.e., stillbirth, preterm birth, low birth weight, and short birth length). We explored a mediation effect of covariates on theoretical causal paths. We calculated the adjusted Population Attributable Fraction (PAF) and Preventive Fractions for the Population (PFP) for valid associations.

Findings

From 72,518 births, 70,425 births (36.4% for Aboriginal women) were included in the analysis. The Latent Class Analys identified two classes: high (membership probability of 10.5%) and low adverse birth outcomes. Births to Aboriginal women with MHrH were around two times more likely to be in the class of high adverse birth outcomes. MHrH prior to or during pregnancy increased the risk of all adverse birth outcomes in both populations with risk ranging from 1.19 (95% CI: 1.05, 1.35) to 7.89 (1.17, 53.37). Eight or more antenatal care visits and intrauterine growth restriction mostly played a significant mediation role between maternal MHrH and adverse birth outcomes with mediation effects ranging from 1.04 (1.01, 1.08) to 1.39 (1.14, 1.69). MHrH had a low to high population impact with a PAF ranging from 16.1% (5.1%, 25.7%) to 87.3% (14.3%, 98.1%). Eight or above antenatal care visits avert extra adverse birth outcomes that range from 723 (332-765) stillbirths to 3003 (1972-4434) preterm births.

Interpretation

Maternal MHrH is a modifiable risk factor that explained a low to moderate risk of adverse birth outcomes in the Northern Territory. The knowledge highlights the need for the development and implementation of preconception mental health care into routine health services.

Funding

The Child and Youth Development Research Partnership (CYDRP) data repository is supported by a grant from the Northern Territory Government.

Trajectories of ADHD medication use before, during, and after pregnancy: A population-based study from Norway and Sweden

PURPOSE

To describe ADHD medication use trajectories around pregnancy in Norway and Sweden.

METHODS

We identified pregnancies resulting in births using linked data from birth and prescribed drug registers of Norway (2006-2019, N = 813 107) and Sweden (2007-2018, N = 1 269 146). We restricted to women who filled prescriptions for ADHD medication during pregnancy or in the year before or after. We described exposure as use versus no use, and total amount of drug dispensed in defined daily doses (DDDs). Group-based trajectory modeling was used to identify distinct medication use trajectories.

RESULTS

In total, 13 286 women (0.64%) filled a prescription for ADHD medication. We identified four trajectory groups: continuers (5.7%), interrupters (23.8%), discontinuers (49.5%), and late initiators (21.0%). Discontinuers were younger, continuers were older on average. More women continued medication in recent years (2014-2019). Most discontinuers (60.7%) were nulliparous; more initiators and continuers had one or multiple previous births, respectively. Continuers were least likely to live with a partner (65.8%). Discontinuers were least likely (24.7%) and continuers most likely (37.6%) to smoke at the beginning of pregnancy. More continuers used amphetamine derivatives and were most likely to use other psychotropics. On modeling continuers, we identified three dose-trajectory groups which suggested that most women reduced medication dose during pregnancy.

CONCLUSIONS

Most pregnant women discontinued or interrupted their ADHD medication during pregnancy, but more continued in recent years. Continuers were more likely to have had previous births, less likely to have lived with a partner, and may have had additional comorbidities warranting the use of other psychotropics.

Antipsychotic utilization patterns in pregnant women with psychotic disorders: a 16-year population-based cohort study

Despite growing concern about reproductive safety of antipsychotics, there is a paucity of research specifically assessing prenatal antipsychotic prescribing practices for psychotic disorders. This population-based cohort study identified women aged 15-50 years with diagnosis of psychotic disorders, who delivered their first and singleton child between 2003-2018 in Hong Kong, with an aim to examine temporal trends and predictors of prenatal antipsychotic use as well as antipsychotic utilization patterns before and during pregnancy. Data were retrieved from territory-wide medical-record database of public healthcare services. Of 804 women, 519 (65%) redeemed at least one prescription for antipsychotics during pregnancy. Older age at conception (25-34 years: OR 2.12 [95% CI 1.22-3.67]; 35-50 years: 2.52 [1.38-4.61]; 15-24 years as reference category) and antipsychotic treatment within 12 months pre-pregnancy (24.22 [16.23-36.16]) were significantly associated with prenatal antipsychotic use. Second-generation-antipsychotic (SGA) use during pregnancy increased over 16-year study period, while prenatal first-generation-antipsychotic (FGA) use showed declining trend. Overall antipsychotic and SGA use progressively decreased across pre-pregnancy and trimesters of pregnancy. Further analyses on antipsychotic use trajectories revealed that 87.4% (n = 459) of 529 women receiving antipsychotics in 12-month pre-pregnancy redeemed antipsychotic prescription during pregnancy, and 63.4% (n = 333) continued antipsychotic treatment throughout pregnancy. Only 7.5% of the cohort (n = 60) commenced antipsychotics in pregnancy. This is one of the few studies evaluating real-world prenatal antipsychotic utilization among women with psychotic disorders. Future research delineating risk conferred by illness-related factors and antipsychotic exposure on adverse maternal and fetal outcomes is warranted to facilitate treatment guideline development.

Systematic review and meta-analysis of risk of gestational diabetes in women with preconception mental disorders

There is a well-established bidirectional association between Type 2 diabetes and mental disorder and emerging evidence for an increased risk of perinatal mental disorder in women with gestational diabetes (GDM). However, the relation between mental disorder prior to pregnancy and subsequent risk of GDM remains relatively unexplored. This is a systematic review and meta-analysis of the risk of GDM in women with a range of preconception mental disorders. Peer-reviewed literature measuring odds of GDM and preconception mood, anxiety, psychotic and eating disorders was systematically reviewed. Risk of bias was assessed using a checklist. Two independent reviewers were involved. 22 observational studies met inclusion criteria; most were retrospective cohorts from English speaking, high income countries. 14 studies were at high risk of bias. There was evidence for an increased risk of GDM in women with schizophrenia (pooled OR 2.44; 95% CI 1.17,5.1; 5 studies) and a reduced risk of GDM in women with anorexia nervosa (pooled OR 0.63; 95% CI 0.49,0.80; 5 studies). There was some limited evidence of an increased risk in women with bipolar disorder. There was no evidence for an association with preconception depression or bulimia nervosa on meta-analysis. There were insufficient studies on anxiety disorders for meta-analysis. This review indicates that there is not a significant risk of GDM associated with many preconception mental disorders but women with psychotic disorders represent a group uniquely vulnerable to GDM. Early detection and management of GDM could improve physical and mental health outcomes for these women and their children.

Trajectories of pregabalin use and their association with longitudinal changes in opioid and benzodiazepine use

ABSTRACT

Concomitant use of pregabalin with opioids and/or benzodiazepines is common, despite the increased risks. However, clinical trials suggest pregabalin can have an opioid-sparing effect when treating acute postoperative pain. We explored how opioid and benzodiazepine use changed over time in people initiating pregabalin, using dispensing claims data for a 10% sample of Australians (2013-19). Among 142,776 people initiating pregabalin (median age = 61 years, 57% female), we used group-based trajectory modelling to identify 6 pregabalin dose trajectories in the first year postinitiation. Two trajectories involved discontinuation: after one dispensing (49%), and after 6 months of treatment (14%). Four trajectories involved persistent use with variable estimated median daily doses of 39 mg (16%), 127 mg (14%), 276 mg (5%), and 541 mg (2%). We quantified opioid and benzodiazepine use in the year before and after pregabalin initiation using generalised linear models. Over the study period, 71% were dispensed opioids and 34% benzodiazepines, with people on the highest pregabalin dose having highest rates of use. Opioid use increased postpregabalin initiation. Among people using both opioids and pregabalin, the geometric mean daily dose in oral morphine equivalents increased after pregabalin initiation in all trajectories, ranging from +5.9% (99% confidence interval 4.8%-7.0%) to +39.8% (99% confidence interval 38.3%-41.5%) in people on the highest daily pregabalin dose. Among people using both pregabalin and benzodiazepines, the dose remained constant over time for people in all trajectories. Notwithstanding its reputation as opioid-sparing, in this outpatient setting, we observed that people using opioids tended to use higher opioid daily doses after pregabalin initiation, especially those on high pregabalin doses.

Longitudinal Methods for Modeling Exposures in Pharmacoepidemiologic Studies in Pregnancy

In many perinatal pharmacoepidemiologic studies, exposure to a medication is classified as "ever exposed" versus "never exposed" within each trimester or even over the entire pregnancy. This approach is often far from real-world exposure patterns, may lead to exposure misclassification, and does not to incorporate important aspects such as dosage, timing of exposure, and treatment duration. Alternative exposure modeling methods can better summarize complex, individual-level medication use trajectories or time-varying exposures from information on medication dosage, gestational timing of use, and frequency of use. We provide an overview of commonly used methods for more refined definitions of real-world exposure to medication use during pregnancy, focusing on the major strengths and limitations of the techniques, including the potential for method-specific biases. Unsupervised clustering methods, including k-means clustering, group-based trajectory models, and hierarchical cluster analysis, are of interest because they enable visual examination of medication use trajectories over time in pregnancy and complex individual-level exposures, as well as providing insight into comedication and drug-switching patterns. Analytical techniques for time-varying exposure methods, such as extended Cox models and Robins' generalized methods, are useful tools when medication exposure is not static during pregnancy. We propose that where appropriate, combining unsupervised clustering techniques with causal modeling approaches may be a powerful approach to understanding medication safety in pregnancy, and this framework can also be applied in other areas of epidemiology.

Antipsychotic Use During Pregnancy and Risk for Gestational Diabetes: A National Register-Based Cohort Study in Sweden

OBJECTIVE

We aimed to study whether antipsychotic use during pregnancy is associated with gestational diabetes.

METHODS

This was a Swedish national register-based cohort study on the Medical Birth Register and the Prescribed Drug Register including all 1,307,487 singleton births between July 2006 and December 2017. Antipsychotics were divided into first-generation antipsychotics (n = 728), high-risk metabolic second-generation antipsychotics including olanzapine, clozapine and quetiapine (n = 1710), and other second-generation antipsychotics (n = 541). The risks for gestational diabetes, foetal growth disturbances, pre-eclampsia, caesarean section and preterm labour were assessed. Women treated during pregnancy were compared to women not treated during pregnancy and to women who used antipsychotics before/after but not during pregnancy.

RESULTS

The crude risk ratio for gestational diabetes for women treated with high-risk metabolic second-generation antipsychotics during pregnancy was 2.2 (95% confidence interval [CI] 1.6-2.9) compared to untreated pregnant women (n = 1,296,539) and 1.8 (95% CI 1.4-2.5) compared to women treated before/after pregnancy (n = 34,492). After adjustment for maternal factors including body mass index, the risk ratios were 1.8 (95% CI 1.3-2.4) and 1.6 (95% CI 1.2-2.1). Exposed infants had an increased risk of being large for gestational age: adjusted risk ratios 1.6 (95% CI 1.3-1.9) and 1.3 (95% CI 1.1-1.6) compared to no maternal antipsychotic use during pregnancy and maternal use before/after the pregnancy. Other antipsychotics were not associated with metabolic risks.

CONCLUSIONS

Olanzapine, clozapine and quetiapine used during pregnancy were associated with increased risks for gestational diabetes and the infant being large for gestational age. Enhanced metabolic monitoring should be considered for pregnant women using these drugs.

Severe and persistent mental illness (SPMI) in pregnancy and breastfeeding: focus on second-generation long acting injectable antipsychotics

Introduction: Pregnant women and fetuses are more likely than ever to be exposed to antipsychotic drugs (APs) during pregnancy and postpartum period. Second-generation APs (SGA) are increasingly used among women in reproductive age. Key outcomes (i.e., congenital malformations, pregnancy and maternal outcomes, neonatal/infant risks, and developmental/long-term outcomes) following the exposure to APs remain limited in number and size and yield of inconsistent findings overall, particularly regarding long-acting injectable AP (LAI-APs) formulations.Areas covered: The review aims at providing a summary of current knowledge on potential risks and safety profile of LAI-APs during pregnancy and breastfeeding, specifically focusing on SGA.Expert opinion: The management of safety and tolerability of long-acting injectable AP (LAI-APs) is far from having solid scientific evidence. In fact, due to ethical reasons, there is a lack of randomized clinical trials that limits the reliability and generalizability of the available data on LAI-APs safety profile during the perinatal period, being limited in the scientific literature only to isolated case reports. Therefore, it seems to be important for the future pathways to perinatal mental health care, providing a network of specialized clinicians and systematically collecting data of pregnant/puerperal women on oral and/or LAI APs-therapy about mother and infant outcomes.

Big data and real-world data-based medicine in the management of hypertension

Big data has been a hot topic in medical and healthcare research. Big data in healthcare is considered to comprise massive amounts of information from various sources, including electronic health records (EHRs), administrative or claims data, and data from self-monitoring devices. Biomedical research has also generated a significant portion of big data relevant to healthcare. Other large datasets arise from cohorts that are recruited and followed on the basis of specific questions, although such research questions may later be expanded to enable other investigations. While the availability of big data offers many possibilities for an improved understanding of disease and treatment, the need for careful and productive use of statistical concepts should be kept in mind. Patient data routinely collected via electronic means are called real-world data (RWD) and are becoming common in healthcare research. RWD and big data are not synonymous with each other, but the two terms seem to be used without distinction with respect to observational studies. In this article, we review hypertension-related papers that use big data or RWD. There are many other sources of big data or RWD that are not covered here, each of which may pose special challenges and opportunities. While randomized clinical trials (RCTs) are considered to be the criterion standard for generating clinical evidence, the use of real-world evidence (RWE) to evaluate the efficacy and safety of medical interventions is gaining interest. On-going efforts to make use of RWD to generate RWE for regulatory decisions, as well as the challenges confronted, including reliability (quality) and relevance (fitness for purpose) of data, will also be addressed.