Direct regression models for longitudinal rates of change

Associations between prenatal metal exposure and growth rate in children: Based on Hangzhou Birth Cohort Study

BACKGROUND

It has been reported that prenatal metal exposure is associated with child anthropometry. However, studies focusing on the growth rate of anthropometry among children have not been conducted. This study aimed to examine associations between the exposure of multiple metals during pregnancy and the growth rate of anthropometry among offspring.

METHODS

743 mother-child pairs from the Hangzhou Birth Cohort Study (HBCS) were included. Levels of eleven metals in mother's blood during pregnancy were measured. Offspring had a mean of 5.7 measurements on anthropometric indicators including weight, length/height, head circumference, and body mass index (BMI) within 1.5 years of birth. Generalized estimating equation (GEE) model was used to investigate the associations between maternal metal exposure and growth rate of anthropometric indicators in children. Stratification analysis by sex was also examined.

RESULTS

Levels of selenium (Se, β = 0.213, 95 % CI = 0.017 to 0.409, P = 0.033) were positively associated with length/height gain per month in children. Levels of chromium (Cr, β = 0.025, 95 % CI = 0.018 to 0.033, P < 0.001) were positively associated with the rate of weight gain. Levels of manganese (Mn, β = -0.030, 95 % CI = -0.052 to -0.008, P = 0.009) and cobalt (Co, β = -0.012, 95 % CI = -0.024 to -0.000, P = 0.044) were inversely associated with growth rate of head circumference. Children with higher maternal Mn levels had a lower BMI change rate. Associations between metals and growth rate were stronger in girls than in boys. Besides, significant associations between metal mixtures and growth rate were found.

CONCLUSION

Prenatal exposure to Se, Cr, Mn, and Co was associated with growth rate in children, with sex-specific disparities. Our results suggested important effects of maternal exposure to multiple metals on development in offspring.

Sensor-Controlled Digital Game for Heart Failure Self-management: Protocol for a Randomized Controlled Trial

BACKGROUND

Heart failure (HF) is the leading cause of hospitalization among older adults in the United States. There are substantial racial and geographic disparities in HF outcomes, with patients living in southern US states having a mortality rate 69% higher than the national average. Self-management behaviors, particularly daily weight monitoring and physical activity, are extremely important in improving HF outcomes; however, patients typically have particularly low adherence to these behaviors. With the rise of digital technologies to improve health outcomes and motivate health behaviors, sensor-controlled digital games (SCDGs) have become a promising approach. SCDGs, which leverage sensor-connected technologies, offer the benefits of being portable and scalable and allowing for continuous observation and motivation of health behaviors in their real-world contexts. They are also becoming increasingly popular among older adults and offer an immersive and accessible way to measure self-management behaviors and improve adherence. No SCDGs have been designed for older adults or evaluated to test their outcomes.

OBJECTIVE

This randomized clinical trial aims to assess the efficacy of a SCDG in integrating the behavioral data of participants with HF from weight scale and activity tracker sensors to activate game progress, rewards, and feedback and, ultimately, to improve adherence to important self-management behaviors.

METHODS

A total of 200 participants with HF, aged ≥45 years, will be recruited and randomized into 2 groups: the SCDG playing group (intervention group) and sensor-only group (control group). Both groups will receive a weight scale, physical activity tracker, and accompanying app, whereas only the intervention group will play the SCDG. This design, thereby, assesses the contributions of the game. All participants will complete a baseline survey as well as posttests at 6 and 12 weeks to assess the immediate effect of the intervention. They will also complete a third posttest at 24 weeks to assess the maintenance of behavioral changes. Efficacy and benefits will be assessed by measuring improvements in HF-related proximal outcomes (self-management behaviors of daily weight monitoring and physical activity) and distal outcomes (HF hospitalization, quality of life, and functional status) between baseline and weeks 6, 12, and 24. The primary outcome measured will be days with weight monitoring, for which this design provides at least 80% power to detect differences between the 2 groups.

RESULTS

Recruitment began in the fall of 2022, and the first patient was enrolled in the study on November 7, 2022. Recruitment of the last participant is expected in quarter 1 of 2025. Publication of complete results and data from this study is expected in 2026.

CONCLUSIONS

This project will generate insight and guidance for scalable and easy-to-use digital gaming solutions to motivate persistent adherence to HF self-management behaviors and improve health outcomes among individuals with HF.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05056129; https://clinicaltrials.gov/ct2/show/NCT05056129.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/45801.

Antibiotics prior to age 2 years have limited association with preschool growth trajectory

BACKGROUND

Prior studies of early antibiotic use and growth have shown mixed results, primarily on cross-sectional outcomes. This study examined the effect of oral antibiotics before age 24 months on growth trajectory at age 2-5 years.

METHODS

We captured oral antibiotic prescriptions and anthropometrics from electronic health records through PCORnet, for children with ≥1 height and weight at 0-12 months of age, ≥1 at 12-30 months, and ≥2 between 25 and 72 months. Prescriptions were grouped into episodes by time and by antimicrobial spectrum. Longitudinal rate regression was used to assess differences in growth rate from 25 to 72 months of age. Models were adjusted for sex, race/ethnicity, steroid use, diagnosed asthma, complex chronic conditions, and infections.

RESULTS

430,376 children from 29 health U.S. systems were included, with 58% receiving antibiotics before 24 months. Exposure to any antibiotic was associated with an average 0.7% (95% CI 0.5, 0.9, p < 0.0001) greater rate of weight gain, corresponding to 0.05 kg additional weight. The estimated effect was slightly greater for narrow-spectrum (0.8% [0.6, 1.1]) than broad-spectrum (0.6% [0.3, 0.8], p < 0.0001) drugs. There was a small dose response relationship between the number of antibiotic episodes and weight gain.

CONCLUSION

Oral antibiotic use prior to 24 months of age was associated with very small changes in average growth rate at ages 2-5 years. The small effect size is unlikely to affect individual prescribing decisions, though it may reflect a biologic effect that can combine with others.

Persistent metabolomic alterations characterize chronic critical illness after severe trauma

BACKGROUND

Following trauma, persistent inflammation, immunosuppression, and catabolism may characterize delayed recovery or failure to recover. Understanding the metabolic response associated with these adverse outcomes may facilitate earlier identification and intervention. We characterized the metabolic profiles of trauma victims who died or developed chronic critical illness (CCI) and hypothesized that differences would be evident within 1-week postinjury.

METHODS

Venous blood samples from trauma victims with shock who survived at least 7 days were analyzed using mass spectrometry. Subjects who died or developed CCI (intensive care unit length of stay of ≥14 days with persistent organ dysfunction) were compared with subjects who recovered rapidly (intensive care unit length of stay, ≤7 days) and uninjured controls. We used partial least squares discriminant analysis, t tests, linear mixed effects regression, and pathway enrichment analyses to make broad comparisons and identify differences in metabolite concentrations and pathways.

RESULTS

We identified 27 patients who died or developed CCI and 33 who recovered rapidly. Subjects were predominantly male (65%) with a median age of 53 years and Injury Severity Score of 36. Healthy controls (n = 48) had similar age and sex distributions. Overall, from the 163 metabolites detected in the samples, 56 metabolites and 21 pathways differed between injury outcome groups, and partial least squares discriminant analysis models distinguished injury outcome groups as early as 1-day postinjury. Differences were observed in tryptophan, phenylalanine, and tyrosine metabolism; metabolites associated with oxidative stress via methionine metabolism; inflammatory mediators including kynurenine, arachidonate, and glucuronic acid; and products of the gut microbiome including indole-3-propionate.

CONCLUSIONS

The metabolic profiles in subjects who ultimately die or develop CCI differ from those who have recovered. In particular, we have identified differences in markers of inflammation, oxidative stress, amino acid metabolism, and alterations in the gut microbiome. Targeted metabolomics has the potential to identify important metabolic changes postinjury to improve early diagnosis and targeted intervention.

LEVEL OF EVIDENCE

Prognostic/epidemiologic, level III.

Risk Factors for Cerebrospinal Fluid Leak Following Anterior Cervical Discectomy and Fusion

STUDY DESIGN/SETTING

This was a retrospective cohort study.

PURPOSE

The purpose of this study was to examine the association between postoperative cerebrospinal fluid (CSF) leak and anterior cervical discectomy and fusion (ACDF). Specifically, we evaluated: (1) demographic risk factors; (2) comorbid risk factors; (3) indications for surgery; and (4) lengths of stay.

SUMMARY OF BACKGROUND DATA

CSF leak is a rare but serious complication of ACDF. Currently, there is a paucity of literature describing the risk factors for CSF leak following ACDF.

METHODS

The Nationwide Inpatient Sample was used to identify all patients who underwent cervical fusion using the anterior approach with excision of intervertebral disc between 1998 and 2010. Patients who had a diagnosis of ossification of the posterior longitudinal ligament in the cervical region were excluded. All patients who had a CSF leak were identified. Demographics and comorbidities were compared via χ analysis, and logistic regression to calculate the odds of having a CSF leak.

RESULTS

Of the 1,261,140 patients identified, 3048 patients (0.24%) had a postoperative CSF leak. Patients who were between the ages of 55 and 69 years (P=0.038) and 70 years or older (P=0.001) were at an increased risk of CSF leak compared with patients who were aged 40-54 years. Non-white race (P=0.021), obesity, (P<0.001) and hypertension (P=0.025) were associated with an increased risk of CSF leak, but diabetes (P=0.966) and hyperlipidemia (P=0.226) were not. Herniated disc diagnosis was associated with decreased risk of CSF leak (P=0.032), but cervical spondylosis with myelopathy patients had an increased risk (P<0.001). Patients with CSF leak had a mean length of stay of 6.0 days compared with 2.1 days among controls.

CONCLUSIONS

Surgical candidates who are older and non-white should be counseled of their increased risk for CSF leak in preoperative planning. Patients who are obese and have hypertension may benefit from medical optimization before surgery.

LEVEL OF EVIDENCE

Level III.

Multivariate analysis of longitudinal rates of change

Longitudinal data allow direct comparison of the change in patient outcomes associated with treatment or exposure. Frequently, several longitudinal measures are collected that either reflect a common underlying health status, or characterize processes that are influenced in a similar way by covariates such as exposure or demographic characteristics. Statistical methods that can combine multivariate response variables into common measures of covariate effects have been proposed in the literature. Current methods for characterizing the relationship between covariates and the rate of change in multivariate outcomes are limited to select models. For example, 'accelerated time' methods have been developed which assume that covariates rescale time in longitudinal models for disease progression. In this manuscript, we detail an alternative multivariate model formulation that directly structures longitudinal rates of change and that permits a common covariate effect across multiple outcomes. We detail maximum likelihood estimation for a multivariate longitudinal mixed model. We show via asymptotic calculations the potential gain in power that may be achieved with a common analysis of multiple outcomes. We apply the proposed methods to the analysis of a trivariate outcome for infant growth and compare rates of change for HIV infected and uninfected infants. Copyright © 2016 John Wiley & Sons, Ltd.