Association between maternal employment status and presence of children with major congenital anomalies in Denmark.

IMPORTANCE: The burden of caring for children with complex medical problems such as major congenital anomalies falls principally on mothers, who in turn suffer a variety of potentially severe economic consequences. As well, health consequences of caregiving often further impact the social and economic prospects of mothers of children with major congenital anomalies (MCMCAs). Evaluating the long-term economic consequences of extensive in-home caregiving among MCMCAs can inform strategies to mitigate these effects. OBJECTIVE: To assess whether MCMCAs face reduced employment and increased need for disability benefits over a 20-year period. DESIGN: A population-based matched cohort study. SETTING: Denmark. PARTICIPANTS: All women who gave birth to a singleton child with a major congenital anomaly in Denmark between January 1, 1997 and December 31, 2017 (n = 23,637) and a comparison cohort of mothers matched by maternal age, parity, and infant's year of birth (n = 234,586). EXPOSURES: Liveborn infant with a major congenital anomaly. MAIN OUTCOMES AND MEASURES: The primary outcome was mothers' employment status, stratified by their child's age. Employment status was categorized as employed, outside the workforce (on temporary leave, holding a flexible job, or pursuing education), or unemployed; the number of weeks in each category was measured over time. The secondary outcome was time to receipt of a disability pension, which in Denmark implies permanent exit from the labor market. We used a negative binomial regression model to estimate the number of weeks in each employment category, stratified by the child's age (i.e., 0-1 year, > 1-6 years, 7-13 years, 14-18 years). A Cox proportional hazards regression model was used to compute hazard ratios as a measure of the relative risk of receiving a disability pension. Rate ratios and hazard ratios were adjusted for maternal demographics, pregnancy history, health, and infant's year of birth. RESULTS: During 1-6 years after delivery, MCMCAs were outside the workforce for a median of 50 weeks (IQR, 6-107 weeks), while members of the comparison cohort were outside the workforce for a median of 48 weeks (IQR, 4-98 weeks), corresponding to an adjusted rate ratio [ARR] of 1.05 (95% confidence interval [CI], 1.04-1.07). During the first year after delivery, MCMCAs were more likely to be employed than mothers in the comparison cohort (ARR, 1.08; 95% CI, 1.06-1.10). At all timepoints thereafter, MCMCAs had a lower rate of workforce participation. The rate of being outside the workforce was 5% higher than mothers in the comparison cohort during 1-6 years after delivery (ARR, 1.05; 95% CI, 1.04-1.07), 9% higher during 7-13 years after delivery (ARR, 1.09; 95% CI, 1.06-1.12), and 12% higher during 14-18 years after delivery (ARR, 1.12; 95% CI, 1.07-1.18). Overall, MCMCAs had a 20% increased risk of receiving a disability pension during follow-up than mothers in the matched comparison cohort [incidence rates 3.10 per 1000 person-years (95% CI, 2.89-3.32) vs. 2.34 per 1000 person-years (95% CI, 2.29-2.40), adjusted hazard ratio, 1.20; 95% CI, 1.11-1.29]. CONCLUSION AND RELEVANCE: MCMCAs were less likely to participate in the Danish workforce, less likely to be employed, and more likely to receive disability pensions than mothers of unaffected children. The rate of leaving the workforce intensified as their affected children grew older. The high demands of caregiving among MCMCAs may have long-term employment consequences even in nations with comprehensive and heavily tax-supported childcare systems, such as Denmark.

Population pharmacokinetics and humanized dosage regimens matching the peak, area, trough, and range of amikacin plasma concentrations in immune-competent murine bloodstream and lung infection models.

Amikacin is an FDA-approved aminoglycoside antibiotic that is commonly used. However, validated dosage regimens that achieve clinically relevant exposure profiles in mice are lacking. We aimed to design and validate humanized dosage regimens for amikacin in immune-competent murine bloodstream and lung infection models of Acinetobacter baumannii. Plasma and lung epithelial lining fluid (ELF) concentrations after single subcutaneous doses of 1.37, 13.7, and 137 mg/kg of body weight were simultaneously modeled via population pharmacokinetics. Then, humanized amikacin dosage regimens in mice were designed and prospectively validated to match the peak, area, trough, and range of plasma concentration profiles in critically ill patients (clinical dose: 25-30 mg/kg of body weight). The pharmacokinetics of amikacin were linear, with a clearance of 9.93 mL/h in both infection models after a single dose. However, the volume of distribution differed between models, resulting in an elimination half-life of 48 min for the bloodstream and 36 min for the lung model. The drug exposure in ELF was 72.7% compared to that in plasma. After multiple q6h dosing, clearance decreased by ~80% from the first (7.35 mL/h) to the last two dosing intervals (~1.50 mL/h) in the bloodstream model. Likewise, clearance decreased by 41% from 7.44 to 4.39 mL/h in the lung model. The humanized dosage regimens were 117 mg/kg of body weight/day in mice [administered in four fractions 6 h apart (q6h): 61.9%, 18.6%, 11.3%, and 8.21% of total dose] for the bloodstream and 96.7 mg/kg of body weight/day (given q6h as 65.1%, 16.9%, 10.5%, and 7.41%) for the lung model. These validated humanized dosage regimens and population pharmacokinetic models support translational studies with clinically relevant amikacin exposure profiles.

Integrating Public and Population Health Into Medical Education Curricula: Opportunities and Challenges for Reform.

ABSTRACT: In a review of U.S. medical education curricular guidance, from premedical studies through to continuing medical education, Maeshiro and colleagues found limited examples of public and population health topics. In this Commentary, the authors emphasize the importance of including public and population health in the curriculum, pointing to curricular reform efforts to integrate these topics into teaching of basic sciences and clinical studies. In addition, they consider the expectations placed on physicians to meet the needs of the population and argue that policies that support public health funding, infrastructure, and workers are also critical to improving the health of communities.

Development and Assessment of an Artificial Intelligence-Based Tool for Ptosis Measurement in Adult Myasthenia Gravis Patients Using Selfie Video Clips Recorded on Smartphones.

Introduction: Myasthenia gravis (MG) is a rare autoimmune disease characterized by muscle weakness and fatigue. Ptosis (eyelid drooping) occurs due to fatigue of the muscles for eyelid elevation and is one symptom widely used by patients and healthcare providers to track progression of the disease. Margin reflex distance 1 (MRD1) is an accepted clinical measure of ptosis and is typically assessed using a hand-held ruler. In this work, we develop an AI model that enables automated measurement of MRD1 in self-recorded video clips collected using patient smartphones. Methods: A 3-month prospective observational study collected a dataset of video clips from patients with MG. Study participants were asked to perform an eyelid fatigability exercise to elicit ptosis while filming "selfie" videos on their smartphones. These images were collected in nonclinical settings, with no in-person training. The dataset was annotated by non-clinicians for (1) eye landmarks to establish ground truth MRD1 and (2) the quality of the video frames. The ground truth MRD1 (in millimeters, mm) was calculated from eye landmark annotations in the video frames using a standard conversion factor, the horizontal visible iris diameter of the human eye. To develop the model, we trained a neural network for eye landmark detection consisting of a ResNet50 backbone plus two dense layers of 78 dimensions on publicly available datasets. Only the ResNet50 backbone was used, discarding the last two layers. The embeddings from the ResNet50 were used as features for a support vector regressor (SVR) using a linear kernel, for regression to MRD1, in mm. The SVR was trained on data collected remotely from MG patients in the prospective study, split into training and development folds. The model's performance for MRD1 estimation was evaluated on a separate test fold from the study dataset. Results: On the full test fold (N = 664 images), the correlation between the ground truth and predicted MRD1 values was strong (r = 0.732). The mean absolute error was 0.822 mm; the mean of differences was -0.256 mm; and 95% limits of agreement (LOA) were -0.214-1.768 mm. Model performance showed no improvement when test data were gated to exclude "poor" quality images. Conclusions: On data generated under highly challenging real-world conditions from a variety of different smartphone devices, the model predicts MRD1 with a strong correlation (r = 0.732) between ground truth and predicted MRD1.

Unpaid Family Caregiving-The Next Frontier of Gender Equity in a Postpandemic Future.

This Viewpoint discusses how the COVID-19 pandemic has spotlighted the critical role of unpaid family caregiving.

Improving value for underserved populations with a community-based intervention: a retrospective cohort study.

BACKGROUND: Healthcare inequity drives high costs, worse outcomes and is heavily influenced by social determinants of health (SDOH). Addressing health behaviors and SDOH through a culturally competent community-based exposure may be effective in improving value for Medicaid enrollees. This study aims to evaluate whether such an exposure lowers costs at equal or improved quality. METHODS: A retrospective cohort study leveraging claims data was conducted in Detroit, Michigan from April 2021 to April 2022 to examine the impact of a community-based peer support program on clinical, utilization and financial outcomes. A one-to-one propensity matching of 738 pairs of African American Medicaid enrollees was generated, and compared the difference of differences between inpatient, emergency department, prescription and outpatient paid amounts, utilization, and available claims-based quality metrics. RESULTS: Compared to controls, peer support recipients generated significantly lower per member per month costs ($115, (95% CI $20.2 to $210)). Recipients showed a significant increase in the Adult Access to Preventative/Ambulatory Health Services 20-44 year old quality metric (8.31% (95% CI 0.35-16.3%)). Member retention in the health insurance plan was significantly higher for peer support recipients vs. the control group by 3.62% (p < 0.05). Peer support recipients displayed non-significant improvement on all other utilization and actuarial measures. No significant difference was found for any of the other examined quality metrics. CONCLUSIONS: Among a population of African American Medicaid enrollees, a culturally competent community-based intervention was associated with lower cost and better member retention with preserved or improved quality.

Corrigendum: Personalized digital intervention for depression based on social rhythm principles adds significantly to outpatient treatment.

[This corrects the article DOI: 10.3389/fdgth.2022.870522.].

Continuous monitoring of eating and sleeping behaviors in the home environments of older adults: a case study demonstration.

Accurate observation of patient functioning is necessary for rigorous clinical research and for improving the quality of patient care. However, clinic or laboratory environments systematically differ from the contexts of everyday life. Further, assessments that are completed in a single institutional session may not be generalizable. Here, we describe a computer vision methodology that measures human functioning continuously in the environments where patients live, sleep, and eat.

Personalized digital intervention for depression based on social rhythm principles adds significantly to outpatient treatment.

We conducted a 16-week randomized controlled trial in psychiatric outpatients with a lifetime diagnosis of a mood and/or anxiety disorder to measure the impact of a first-of-its-kind precision digital intervention software solution based on social rhythm regulation principles. The full intent-to-treat (ITT) sample consisted of 133 individuals, aged 18-65. An exploratory sub-sample of interest was those individuals who presented with moderately severe to severe depression at study entry (baseline PHQ-8 score ≥15; N = 28). Cue is a novel digital intervention platform that capitalizes on the smartphone's ability to continuously monitor depression-relevant behavior patterns and use each patient's behavioral data to provide timely, personalized "micro-interventions," making this the first example of a precision digital intervention of which we are aware. Participants were randomly allocated to receive Cue plus care-as-usual or digital monitoring only plus care as usual. Within the full study and depressed-at-entry samples, we fit a mixed effects model to test for group differences in the slope of depressive symptoms over 16 weeks. To account for the non-linear trajectory with more flexibility, we also fit a mixed effects model considering week as a categorical variable and used the resulting estimates to test the group difference in PHQ change from baseline to 16 weeks. In the full sample, the group difference in the slope of PHQ-8 was negligible (Cohen's d = -0.10); however, the Cue group demonstrated significantly greater improvement from baseline to 16 weeks (p = 0.040). In the depressed-at-entry sample, we found evidence for benefit of Cue. The group difference in the slope of PHQ-8 (Cohen's d = -0.72) indicated a meaningfully more rapid rate of improvement in the intervention group than in the control group. The Cue group also demonstrated significantly greater improvement in PHQ-8 from baseline to 16 weeks (p = 0.009). We are encouraged by the size of the intervention effect in those who were acutely ill at baseline, and by the finding that across all participants, 80% of whom were receiving pharmacotherapy, we observed significant benefit of Cue at 16 weeks of treatment. These findings suggest that a social rhythm-focused digital intervention platform may represent a useful and accessible adjunct to antidepressant treatment (https://clinicaltrials.gov/ct2/show/NCT03152864?term=ellen+frank&draw=2&rank=3).

A Brief History of Exposure Notification During the COVID-19 Pandemic in the United States, 2020-2021.

The swift global spread of COVID-19 prompted public health authorities to explore digital technologies to aid in contact tracing for infection control. Exposure notification, a mobile device-based technology that notifies individuals of potential exposure to COVID-19 without requiring personally identifiable information, has been broadly favored because of its relative ease of use, scalability, and protection of personal privacy. Although several exposure notification protocols were developed, a partnership between Google and Apple led to the development of the most widely implemented exposure notification protocol in the world, including in the United States. In this article, we first describe the development of the Google Apple Exposure Notification (GAEN) protocol, noting the value of the discourse among software developers and public health authorities concerning the protocol's design and features. We track states' deployment of GAEN mobile applications (apps) and population-level adoption rates, finding the nationwide rollout of GAEN apps to be more fragmented than anticipated. We then discuss how the limited data collected from these apps make assessments of their effectiveness challenging. Finally, we consider the importance of the federal government playing a greater role in GAEN's early development, emphasize the power of public-private partnerships, and highlight the overriding importance of public messaging over technological details.

Mothers of children with major congenital anomalies have increased health care utilization over a 20-year post-birth time horizon.

OBJECTIVE: This population-based, matched cohort study aimed to evaluate utilization of health care services by mothers of children with major congenital anomalies (MCAs), compared to mothers of children without MCAs over a 20-year post-birth time horizon in Denmark. METHODS: Our analytic sample included mothers who gave birth to an infant with a MCA (n = 23,927) and a cohort of mothers matched to them by maternal age, parity and infant's year of birth (n = 239,076). Primary outcomes were period prevalence and mothers' quantity of health care utilization (primary, inpatient, outpatient, surgical, and psychiatric services) stratified by their child's age (i.e., ages 0-6 = before school, ages 7-13 = pre-school + primary education, and ages 14-18 = secondary education or higher). The secondary outcome measure was length of hospital stays. Outcome measures were adjusted for maternal age at delivery, parity, marital status, income quartile, level of education in the year prior to the index birth, previous spontaneous abortions, maternal pregnancy complications, maternal diabetes, hypertension, alcohol-related diseases, and maternal smoking. RESULTS: In both cohorts the majority of mothers were between 26 and 35 years of age, married, and employed, and 47% were primiparous. Mothers of infants with anomalies had greater utilization of outpatient, inpatient, surgical, and psychiatric services, compared with mothers in the matched cohort. Inpatient service utilization was greater in the exposed cohort up to 13 years after a child's birth, with the highest risk in the first six years after birth [adjusted risk ratio, 1.13; 95% confidence interval (CI), 1.12-1.14], with a decrease over time. Regarding the quantity of health care utilization, the greatest difference between the two groups was in inpatient service utilization, with a 39% increased rate in the exposed cohort during the first six years after birth (adjusted rate ratio, 1.39; 95% CI, 1.37-1.42). During the first 6 years after birth, mothers of children with anomalies stayed a median of 6 days (interquartile range [IQR], 3-13) in hospital overall, while the comparison cohort stayed a median of 4 days (IQR, 2-7) in hospital overall. Rates of utilization of outpatient clinics (adjusted rate ratio, 1.36; 95% CI, 1.29-1.42), as well as inpatient (adjusted rate ratio, 1.77; 95% CI, 1.68-1.87), and surgical services (adjusted rate ratio, 1.33; 95% CI, 1.26-1.41) was higher in mothers of children with multiple-organ MCAs during 0 to 6 years after birth. Among mothers at the lowest income levels, utilization of psychiatric clinic services increased to 59% and when their child was 7 to 13 years of age (adjusted rate ratio, 1.59; 95% CI, 1.24-2.03). CONCLUSION: Mothers of infants with a major congenital anomaly had greater health care utilization across services. Health care utilization decreased over time or remained stable for outpatient, inpatient, and surgical care services, whereas psychiatric utilization increased for up to 13 years after an affected child's birth. Healthcare utilization was significantly elevated among mothers of children with multiple MCAs and among those at the lowest income levels.

Combating Multidrug-Resistant Bacteria by Integrating a Novel Target Site Penetration and Receptor Binding Assay Platform Into Translational Modeling.

Multidrug-resistant bacteria are causing a serious global health crisis. A dramatic decline in antibiotic discovery and development investment by pharmaceutical industry over the last decades has slowed the adoption of new technologies. It is imperative that we create new mechanistic insights based on latest technologies, and use translational strategies to optimize patient therapy. Although drug development has relied on minimal inhibitory concentration testing and established in vitro and mouse infection models, the limited understanding of outer membrane permeability in Gram-negative bacteria presents major challenges. Our team has developed a platform using the latest technologies to characterize target site penetration and receptor binding in intact bacteria that inform translational modeling and guide new discovery. Enhanced assays can quantify the outer membrane permeability of ß-lactam antibiotics and ß-lactamase inhibitors using multiplex liquid chromatography tandem mass spectrometry. While ß-lactam antibiotics are known to bind to multiple different penicillin-binding proteins (PBPs), their binding profiles are almost always studied in lysed bacteria. Novel assays for PBP binding in the periplasm of intact bacteria were developed and proteins identified via proteomics. To characterize bacterial morphology changes in response to PBP binding, high-throughput flow cytometry and time-lapse confocal microscopy with fluorescent probes provide unprecedented mechanistic insights. Moreover, novel assays to quantify cytosolic receptor binding and intracellular drug concentrations inform target site occupancy. These mechanistic data are integrated by quantitative and systems pharmacology modeling to maximize bacterial killing and minimize resistance in in vitro and mouse infection models. This translational approach holds promise to identify antibiotic combination dosing strategies for patients with serious infections.

First Penicillin-Binding Protein Occupancy Patterns for 15 ß-Lactams and ß-Lactamase Inhibitors in Mycobacterium abscessus.

Mycobacterium abscessus causes serious infections that often require over 18 months of antibiotic combination therapy. There is no standard regimen for the treatment of M. abscessus infections, and the multitude of combinations that have been used clinically have had low success rates and high rates of toxicities. With ß-lactam antibiotics being safe, double ß-lactam and ß-lactam/ß-lactamase inhibitor combinations are of interest for improving the treatment of M. abscessus infections and minimizing toxicity. However, a mechanistic approach for building these combinations is lacking since little is known about which penicillin-binding protein (PBP) target receptors are inactivated by different ß-lactams in M. abscessus We determined the preferred PBP targets of 13 ß-lactams and 2 ß-lactamase inhibitors in two M. abscessus strains and identified PBP sequences by proteomics. The Bocillin FL binding assay was used to determine the ß-lactam concentrations that half-maximally inhibited Bocillin binding (50% inhibitory concentrations [IC50s]). Principal component analysis identified four clusters of PBP occupancy patterns. Carbapenems inactivated all PBPs at low concentrations (0.016 to 0.5 mg/liter) (cluster 1). Cephalosporins (cluster 2) inactivated PonA2, PonA1, and PbpA at low (0.031 to 1 mg/liter) (ceftriaxone and cefotaxime) or intermediate (0.35 to 16 mg/liter) (ceftazidime and cefoxitin) concentrations. Sulbactam, aztreonam, carumonam, mecillinam, and avibactam (cluster 3) inactivated the same PBPs as cephalosporins but required higher concentrations. Other penicillins (cluster 4) specifically targeted PbpA at 2 to 16 mg/liter. Carbapenems, ceftriaxone, and cefotaxime were the most promising ß-lactams since they inactivated most or all PBPs at clinically relevant concentrations. These first PBP occupancy patterns in M. abscessus provide a mechanistic foundation for selecting and optimizing safe and effective combination therapies with ß-lactams.

Achieving a Quintuple Aim for Telehealth in Pediatrics.

Pediatric practice increasingly involves providing care for children with medical complexity. Telehealth offers a strategy for providers and health care systems to improve care for these patients and their families. However, lack of awareness related to the unintended negative consequences of telehealth on vulnerable populations--coupled with failure to intentional design best practices for telehealth initiatives--implies that these novel technologies may worsen health disparities in the long run. This article reviews the positive and negative implications of telehealth. In addition, to achieve optimal implementation of telehealth, it discusses 10 considerations to promote optimal care of children using these technologies.

Impact of Social Needs Navigation on Utilization Among High Utilizers in a Large Integrated Health System: a Quasi-experimental Study.

BACKGROUND: Programs addressing social determinants of health for high-utilizing patients are gaining interest among health systems as an avenue to promote health and decrease utilization. OBJECTIVE: To evaluate impacts of a social needs screening and navigation program for adult predicted high utilizers on total medical visit utilization. DESIGN: A prospective, quasi-experimental study using an intent-to-treat propensity-weighted difference-in-differences approach. Stratified analyses assessed intervention effects among three low-socioeconomic status sub-samples: patients in low-income areas, in low-education areas, and with Medicaid insurance. PARTICIPANTS: Predicted high utilizers-patients predicted to be in the highest 1% for total utilization in a large integrated health system. INTERVENTION: A telephonic social needs screening and navigation program. MAIN MEASURES: Primary difference-in-difference analyses compared total visit count utilization, including outpatient, emergency department (ED), and inpatient utilization, between the intervention and control groups at both in-network and out-of-network facilities. Prevalence of social needs among sample patients and their connection rates to social needs resources are also described. KEY RESULTS: The study included 34,225 patients (7107 intervention, 27,118 control). Most (53%) patients screened reported social needs, but only a minority (10%) of those with a need were able to connect with resources to address these needs. Primary analysis found total utilization visits decreased 2.2% (95% CI - 4.5%, 0.1%; p = 0.058) in the intervention group. Stratified analyses showed decreases in total utilization for all low-socioeconomic status subgroups receiving the intervention compared with controls: - 7.0% (95% CI - 11.9%, - 1.9%; p = 0.008) in the low-income area group, - 11.5% (- 17.6%, 5.0%; p < 0.001) in the low-education area group, and - 12.1% (- 18.1%, - 5.6%; p < 0.001) in the Medicaid group. CONCLUSIONS: Social needs navigation programs for high-utilizing patients may have modest effects on utilization for the population overall. However, significant decreases in utilization were found among low-socioeconomic status patients more likely to experience social needs.