Effect of pregnancy versus postpartum maternal isoniazid preventive therapy on infant growth in HIV-exposed uninfected infants: a post-hoc analysis of the TB APPRISE trial

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Study Justification:
This post-hoc analysis aimed to investigate the effects of maternal isoniazid preventive therapy (IPT) during pregnancy versus postpartum on infant growth in HIV-exposed uninfected (HEU) infants. The study was conducted to address the knowledge gap regarding the impact of in utero IPT exposure on infant growth, particularly in relation to underweight, stunting, and wasting. The findings of this analysis could provide valuable insights into the potential risks and benefits of IPT during pregnancy and inform management strategies for HEU infants.
Highlights:
– The study utilized data from the TB APPRISE trial, a multicenter, double-blind, placebo-controlled trial conducted in eight countries with high tuberculosis prevalence.
– A total of 898 HEU infants were included in the analysis, with 447 females and 451 males.
– Infants exposed to IPT during pregnancy had a higher risk of becoming underweight by 12 weeks and 48 weeks postpartum compared to infants exposed to IPT postpartum.
– Male infants in the pregnancy-IPT arm experienced an increased risk of low birth weight, preterm birth, and becoming underweight at both 12 weeks and 48 weeks postpartum.
– Maternal IPT timing did not influence growth in female infants.
– These findings suggest that maternal IPT during pregnancy is associated with an increased risk of adverse infant growth outcomes, particularly in male infants.
Recommendations:
Based on the study findings, the following recommendations can be made:
1. Healthcare providers should carefully consider the timing of IPT initiation in pregnant women living with HIV, taking into account the potential risks to infant growth.
2. Further research is needed to explore the underlying mechanisms by which IPT during pregnancy affects infant growth and to identify strategies for mitigating the adverse effects.
3. Guidelines for the management of HIV-exposed infants should include specific recommendations regarding IPT timing and monitoring of growth parameters.
Key Role Players:
To address the recommendations, the following key role players are needed:
1. Researchers: Conduct further studies to investigate the mechanisms and long-term effects of IPT during pregnancy on infant growth.
2. Healthcare Providers: Implement guidelines and protocols for the management of HIV-exposed infants, including IPT timing and monitoring of growth parameters.
3. Policy Makers: Incorporate the study findings into national policies and guidelines for the prevention and management of HIV in pregnant women and their infants.
Cost Items:
The cost items to include in planning the recommendations are:
1. Research Funding: Allocate resources for conducting further studies on the effects of IPT during pregnancy on infant growth.
2. Training and Education: Provide training and education for healthcare providers on the implementation of guidelines for the management of HIV-exposed infants.
3. Monitoring and Evaluation: Establish systems for monitoring and evaluating the implementation of guidelines and the impact on infant growth outcomes.
4. Policy Development and Dissemination: Allocate resources for the development and dissemination of national policies and guidelines based on the study findings.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong. The study is a post-hoc analysis of a randomized, double-blind, placebo-controlled trial with a large sample size. The analysis includes adjusted multivariable regression models and survival analysis. However, the evidence could be strengthened by providing more details on the statistical methods used and addressing potential limitations such as confounding factors and generalizability. To improve the evidence, the authors could consider conducting additional analyses to explore the mechanisms underlying the observed associations and addressing the limitations mentioned.

Background: Isoniazid preventive therapy (IPT) initiation during pregnancy was associated with increased incidence of adverse pregnancy outcomes in the TB APPRISE trial. Effects of in utero IPT exposure on infant growth are unknown. Methods: This post-hoc analysis used data from the TB APPRISE trial, a multicentre, double-blind, placebo-controlled trial, which randomised women to 28-week IPT starting in pregnancy (pregnancy-IPT) or postpartum week 12 (postpartum-IPT) in eight countries with high tuberculosis prevalence. Participants were enrolled between August 2014 and April 2016. Based on modified intent-to-treat analyses, we analysed only live-born babies who had at least one follow-up after birth and compared time to infant growth faltering between arms to 12 weeks and 48 weeks postpartum in overall and sex-stratified multivariable Cox proportional hazards regression. Factors adjusted in the final models include sex of infant, mother’s baseline BMI, age in years, ART regimen, viral load, CD4 count, education, and household food insecurity. Results: Among 898 HIV-exposed uninfected (HEU) infants, 447 (49.8%) were females. Infants in pregnancy-IPT had a 1.47-fold higher risk of becoming underweight by 12 weeks (aHR 1.47 [95% CI: 1.06, 2.03]) than infants in the postpartum-IPT; increased risk persisted to 48 weeks postpartum (aHR 1.34 [95% CI: 1.01, 1.78]). Maternal IPT timing was not associated with stunting or wasting. In sex-stratified analyses, male infants in the pregnancy-IPT arm experienced an increased risk of low birth weight (LBW) (aRR 2.04 [95% CI: 1.16, 3.68), preterm birth (aRR 1.81 [95% CI: 1.04, 3.21]) and becoming underweight by 12 weeks (aHR 2.02 [95% CI: 1.29, 3.18]) and 48 weeks (aHR 1.82 [95% CI: 1.23, 2.69]). Maternal IPT timing did not influence growth in female infants. Interpretation: Maternal IPT during pregnancy was associated with an increased risk of LBW, preterm birth, and becoming underweight among HEU infants, particularly male infants. These data add to prior TB APPRISE data, suggesting that IPT during pregnancy impacts infant growth, which could inform management, and warrants further examination of mechanisms. Funding: The TB APPRISE study Supported by the National Institutes of Health (NIH) (award numbers, UM1AI068632 [IMPAACT LOC], UM1AI068616 [IMPAACT SDMC], and UM1AI106716 [IMPAACT LC]) through the National Institute of Allergy and Infectious Diseases, with cofunding from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (contract number, HHSN275201800001I) and the National Institute of Mental Health.

This post-hoc analysis utilised data from the P1078 TB APPRISE trial – a randomised, double-blind, placebo-controlled, multicentre, non-inferiority study designed to evaluate the effect of pregnancy-IPT vs postpartum-IPT on maternal complications and composite adverse birth outcomes. The trial, as reported in detail previously,8 was conducted in eight countries (Botswana, Haiti, India, South Africa, Tanzania, Thailand, Uganda, and Zimbabwe) at 13 different sites with high TB prevalence (>60 cases per 100,000). Participants were randomised to receive a 28-week course of IPT (300 mg daily) either during pregnancy (pregnancy-IPT) or at postpartum week 12 (postpartum-IPT). The pregnancy-IPT arm received isoniazid daily for 28 weeks (initiated between 14- and 34-weeks gestation, immediately after enrolment), then switched to placebo until the 40th week postpartum. The postpartum-IPT arm initiated a placebo immediately after trial entry during pregnancy until the 12th week postpartum and then switched to isoniazid daily until the 40th week postpartum. All participants received vitamin B6 and a prenatal multivitamin from week 0 to week 40 postpartum. The randomisation was stratified by the gestational age at trial entry (≥14 weeks to 35 kg, with >750 absolute neutrophil count cells/mm3, >7.5 g/dL haemoglobin, and >50,000 platelets count/mm3 were eligible. Participants were required to have liver enzymes (aspartate aminotransferase [AST], alanine aminotransferase [ALT], and total bilirubin) at or below 1.25 times the upper limit of the normal range within 30 days prior to study entry. Women with active TB, recent TB exposure, TB treatment for more than 30 days in the previous year, or peripheral neuropathy of grade 1 or higher were excluded. The original study included 956 participants, 477 randomised to pregnancy-IPT and 479 to postpartum-IPT arm. Participants were enrolled between August 2014 and April 2016. This analysis was restricted to HEU infants born to mothers participating in the RCT. Exclusion criteria for this analysis included lack of infant information (withdrawal from the study before birth or no live birth, or lack of any growth measurement), HIV infection of the infant, and twin births. Mother-infant pairs were followed up to 48 weeks postpartum. Weight and length of infants were measured at birth, 4th, 8th, 12th, 24th, 36th, 44th, and 48th weeks postpartum to the nearest 0.1 kg and 0.1 cm. The scales were calibrated regularly as per the manufacturer’s instructions. Shoes and outer layers of clothing were removed before weight measurements were taken. Infants’ lengths were measured with horizontal boards. The data collectors were trained and experienced in weight and length measurement. There was a two-week extension period for mothers who did not attend their last visit. Missing values at the scheduled last visit were replaced by measurements within two weeks after the end of the study. Low birth weight (LBW) was defined as less than 2.5 kg regardless of gestational age. Birth before completion of 37 weeks of pregnancy was regarded as preterm. Small for gestational age (SGA) was defined by weight less than the 10th percentile for gestational age using INTERGROWTH growth standards.14 Weight-for-age z-score [WAZ], weight-for-length z-score [WLZ], and length-for-age z-score [LAZ]) were defined using WHO child growth standards.15 Growth faltering was less than −2 Z-scores; with underweight defined as WAZ < –2, wasting WLZ < –2, and stunting LAZ < –2. Cofactors of growth faltering assessed in the analyses included: Infant sex and maternal characteristics at enrolment, including body mass index (BMI), age, ART regimen, viral non-suppression (viral load ≥40 copies/ml), CD4 count (cells/mm3), education, and household food insecurity. Household food insecurity was considered positive if the respondents answered yes to at least one of the following questions: did you experience a lack of resources to get food, have you gone to bed hungry in the last 30 days, and have you passed the entire day and night hungry? Means and standard deviations (SDs) were used to describe normally distributed continuous variables, medians and interquartile ranges (IQRs) to describe skewed distributions, and frequencies and percentages to describe categorical variables. Baseline maternal and infant characteristics were compared between pregnancy-IPT and postpartum-IPT randomisation groups using two-sided t-tests (Mann–Whitney U tests if assumptions were not met) for continuous variables and Pearson χ2 tests (Fisher's exact tests if assumptions were not met) for categorical variables. In the primary study, randomisation was carried out on pregnant women. The randomisation groups were compared in modified intent-to-treat analyses adjusted for predetermined potential confounding variables. For the measurement of adverse birth outcomes, the effects of pregnancy-IPT on LBW and preterm birth were examined in the primary trial publication; however, sex-stratified analyses of these outcomes were not conducted. We examined the effects of pregnancy-IPT on birth outcomes (LBW, preterm birth, and SGA) using generalised linear models with a Poisson family and a log link (to estimate relative risks) in overall and sex-stratified analyses. Multivariable generalised linear models were fitted to control potential confounders. For the measurement of growth faltering during infancy, mothers in the postpartum-IPT arm initiated IPT at 12 weeks after delivery, therefore data were censored at 12-weeks postpartum to examine the effect of pregnancy-IPT compared to no IPT during pregnancy and postpartum. In addition, to compare the longer-term effects of pregnancy-IPT on growth faltering, randomised arms were compared up to 48 weeks after birth. Growth faltering was compared between randomised groups using Cox proportional hazards regression models and generalised estimated equations (GEE). We used Kaplan–Meier survival analysis to compare, unadjusted, time to the first event of growth faltering (underweight, wasting, or stunting) to 12 weeks postpartum and 48 weeks postpartum in overall and sex-stratified analyses. Univariate and multivariable Cox proportional hazards regression models and models including interaction terms between randomisation arm and infants' sex were fit to compare the risk of experiencing the first episode of growth faltering between the randomised groups and any effect modification by infant sex. For these analyses, time zero was the randomisation date, and no failure (no growth faltering) was assumed prior to birth. Since participants were randomly assigned to either a treatment or a control group during pregnancy, whatever difference occurred between the two arms, such as gestational age at birth or low birth weight, was assumed to be attributable to the intervention. Infants lost to follow-up or who died prior to failure were censored at their last visit date. Growth data from visits following growth faltering were censored. We used multivariate Cox proportional hazards regression models to identify cofactors (maternal BMI, age, ART regimen, viral non-suppression, CD4 count (cells/mm3), education, and household food insecurity and infant sex) of growth faltering. As fewer than 5% of at-risk participants remained in the study after 60 post-randomisation weeks, the values at 60th week and after were censored. In multivariable models, we didn't adjust birth characteristics because adjusting for low birth weight, preterm birth, and/or SGA would underestimate the effect of the intervention on the outcome as they are in the causal pathway between pregnancy IPT exposure and long-term growth. Moreover, univariate and multivariable generalised estimated equations (GEE) were fit with a Poisson family and a log link (to estimate relative risk) and exchangeable correlation structure to compare risks of growth faltering (underweight, wasting, and stunting) at any time up until 12 weeks postpartum and up to 48 weeks, as well as testing for interaction by infants' sex and analyses stratified by sex. Infants who experienced growth faltering anytime were not censored in this analysis. The multivariate GEE model was used to identify cofactors of growth faltering in HEU infants. We also fitted multivariable linear regression to examine the long-term impact of IPT on growth (WAZ, LAZ, WLZ) at 48 weeks of infant age. We used R version 4.1.0 for analyses. The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. BAR, ASC, and GM had access to the dataset. ASC, SML, GJS, AG, and GM were responsible for the final decision on the submission of this manuscript for publication.

Based on the provided information, it appears that the study is focused on evaluating the effects of pregnancy-IPT (isoniazid preventive therapy) on infant growth in HIV-exposed uninfected infants. The study found that maternal IPT during pregnancy was associated with an increased risk of low birth weight, preterm birth, and becoming underweight among male infants. However, maternal IPT timing did not influence growth in female infants.

In terms of potential innovations to improve access to maternal health, here are a few recommendations:

1. Telemedicine: Implementing telemedicine services can improve access to maternal health by allowing pregnant women to consult with healthcare providers remotely. This can be particularly beneficial for women in remote or underserved areas who may have limited access to healthcare facilities.

2. Mobile health (mHealth) applications: Developing mobile applications that provide educational resources, appointment reminders, and personalized health information can empower pregnant women to take control of their health and access important maternal health services.

3. Community health workers: Training and deploying community health workers can help bridge the gap between healthcare facilities and pregnant women in underserved communities. These workers can provide education, support, and referrals for maternal health services.

4. Maternal health clinics: Establishing dedicated maternal health clinics can ensure that pregnant women have access to comprehensive prenatal care, including regular check-ups, screenings, and counseling services.

5. Transportation services: Providing transportation services to pregnant women in remote or underserved areas can help overcome barriers to accessing maternal health services. This can include arranging for transportation to healthcare facilities for prenatal visits, delivery, and postpartum care.

These are just a few examples of potential innovations that can improve access to maternal health. It’s important to consider the specific needs and challenges of the target population when implementing these innovations.
AI Innovations Description
The recommendation to improve access to maternal health based on the provided description is to further examine the effects of maternal isoniazid preventive therapy (IPT) on infant growth. The post-hoc analysis of the TB APPRISE trial showed that IPT initiation during pregnancy was associated with an increased risk of low birth weight, preterm birth, and underweight infants, particularly among male infants. This information suggests that the timing of IPT during pregnancy may impact infant growth. Therefore, it is recommended to conduct further research to understand the mechanisms behind these effects and to develop strategies to mitigate any potential negative impacts on infant growth while still providing the benefits of IPT for maternal health. This research could inform the management of maternal health interventions and contribute to improving access to maternal health services.
AI Innovations Methodology
Based on the provided information, the study conducted a post-hoc analysis of the TB APPRISE trial to evaluate the effect of pregnancy-IPT (isoniazid preventive therapy) versus postpartum-IPT on infant growth in HIV-exposed uninfected infants. The study aimed to assess the impact of IPT timing on adverse birth outcomes and growth faltering in infants.

To simulate the impact of recommendations on improving access to maternal health, a methodology could include the following steps:

1. Identify the recommendations: Review the findings of the study and identify the specific recommendations that can improve access to maternal health. For example, the study suggests examining the impact of IPT timing on LBW (low birth weight), preterm birth, and growth faltering in infants.

2. Define the simulation parameters: Determine the variables and parameters that need to be considered in the simulation. This may include factors such as maternal characteristics (BMI, age, ART regimen, viral load, CD4 count, education, household food insecurity), infant sex, and growth indicators (weight-for-age, weight-for-length, length-for-age z-scores).

3. Collect data: Gather relevant data on maternal health indicators, access to healthcare services, and other relevant factors from reliable sources such as health records, surveys, or existing databases. Ensure that the data is representative and covers the target population.

4. Develop a simulation model: Use statistical or mathematical modeling techniques to develop a simulation model that incorporates the identified recommendations and relevant parameters. The model should simulate the impact of the recommendations on improving access to maternal health, specifically focusing on the outcomes of interest (e.g., LBW, preterm birth, growth faltering).

5. Validate the model: Validate the simulation model by comparing its outputs with real-world data or existing studies to ensure its accuracy and reliability. This step helps to verify that the model accurately represents the impact of the recommendations on improving access to maternal health.

6. Run the simulation: Execute the simulation model using the collected data and defined parameters. The simulation will generate results that estimate the potential impact of the recommendations on improving access to maternal health indicators.

7. Analyze the results: Analyze the simulation results to understand the potential effects of the recommendations on maternal health outcomes. This may involve comparing different scenarios, assessing the magnitude of the impact, and identifying any potential limitations or challenges.

8. Interpret and communicate the findings: Interpret the simulation results and communicate them in a clear and concise manner. Present the findings to relevant stakeholders, such as healthcare providers, policymakers, and researchers, to inform decision-making and potential interventions to improve access to maternal health.

It is important to note that the methodology described above is a general framework and may need to be adapted based on the specific recommendations and context of the study. Additionally, the accuracy and reliability of the simulation results depend on the quality of the data and the assumptions made in the model.

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