When the smoke gets in your lungs: short-term effects of Indonesia's 2015 forest fires on health care use.

BACKGROUND: The forest fires that ravaged parts of Indonesia in 2015 were the most severely polluting of this century but little is known about their effects on health care utilization of the affected population. We estimate their short-term impact on visit rates to primary and hospital care with particular focus on visits for specific smoke-related conditions (respiratory disease, acute respiratory tract infection (ARTI) and common cold). METHOD: We estimate the short-term impact of the 2015 forest fire on visit rates to primary and hospital care by combining satellite data on Aerosol Optical Depth (AOD) with administrative records from Indonesian National Health Insurance Agency (BPJS Kesehatan) from January 2015-April  2016. The 16 months of panel data cover 203 districts in the islands of Sumatra and Kalimantan before, during and after the forest fires. We use the (more efficient) ANCOVA version adaptation of a fixed effects model to compare the trends in healthcare use of affected districts (with AOD value above 0.75) with control districts (AOD value below 0.75). Considering the higher vulnerability of children's lungs, we do this separately for children under 5 and the rest of the population adults (> 5), and for both urban and rural areas, and for both the period during and after the forest fires. RESULTS: We find little effects for adults. For young children we estimate positive effects for care related to respiratory problems in primary health care facilities in urban areas. Hospital care visits in general, on the other hand, are negatively affected in rural areas. We argue that these patterns arise because accessibility of care during fires is more restricted for rural than for urban areas. CONCLUSION: The severity of the fires and the absence of positive impact on health care utilization for adults and children in rural areas indicate large missed opportunities for receiving necessary care. This is particularly worrisome for children, whose lungs are most vulnerable to the effects. Our findings underscore the need to ensure ongoing access to medical services during forest fires and emphasize the necessity of catching up with essential care for children after the fires, particularly in rural areas.

Should the Use of Adaptive Machine Learning Systems in Medicine be Classified as Research?

A novel advantage of the use of machine learning (ML) systems in medicine is their potential to continue learning from new data after implementation in clinical practice. To date, considerations of the ethical questions raised by the design and use of adaptive machine learning systems in medicine have, for the most part, been confined to discussion of the so-called "update problem," which concerns how regulators should approach systems whose performance and parameters continue to change even after they have received regulatory approval. In this paper, we draw attention to a prior ethical question: whether the continuous learning that will occur in such systems after their initial deployment should be classified, and regulated, as medical research? We argue that there is a strong prima facie case that the use of continuous learning in medical ML systems should be categorized, and regulated, as research and that individuals whose treatment involves such systems should be treated as research subjects.

Digital Humans to Combat Loneliness and Social Isolation: Ethics Concerns and Policy Recommendations.

Social isolation and loneliness are growing concerns around the globe that put people at increased risk of disease and early death. One much-touted approach to addressing them is deploying artificially intelligent agents to serve as companions for socially isolated and lonely people. Focusing on digital humans, we consider evidence and ethical arguments for and against this approach. We set forth and defend public health policies that respond to concerns about replacing humans, establishing inferior relationships, algorithmic bias, distributive justice, and data privacy.

Behavioural and environmental risk factors associated with primary schoolchildren's overweight and obesity in urban Indonesia.

OBJECTIVES: To aid the design of nutrition interventions in low- and middle-income countries undergoing a nutrition transition, this study examined behavioural and environmental risk factors associated with childhood overweight and obesity in urban Indonesia. DESIGN: Body height and weight of children were measured to determine BMI-for-age Z-scores and childhood overweight and obesity status. A self-administered parental survey measured socio-economic background, children's diet, physical activity, screen time and parental practices. Logistic and quantile regression models were used to assess the association between risk factors and the BMI-for-age Z-score distribution. SETTING: Public primary schools in Central Jakarta, sampled at random. PARTICIPANTS: Children (n 1674) aged 6-13 years from 18 public primary schools. RESULTS: Among the children, 31·0 % were overweight or obese. The prevalence of obesity was higher in boys (21·0 %) than in girls (12·0 %). Male sex and height (aOR = 1·67; 95 % CI 1·30, 2·14 and aOR = 1·16; 95 % CI 1·14, 1·18, respectively) increased the odds of being overweight or obese, while the odds reduced with every year of age (aOR = 0·43; 95 % CI 0·37, 0·50). Maternal education was positively associated with children's BMI at the median of the Z-score distribution (P = 0·026). Dietary and physical activity risk scores were not associated with children's BMI at any quantile. The obesogenic home food environment score was significantly and positively associated with the BMI-for-age Z-score at the 75th and 90th percentiles (P = 0·022 and 0·023, respectively). CONCLUSIONS: This study illustrated the demographic, behavioural and environmental risk factors for overweight and obesity among primary schoolchildren in a middle-income country. To foster healthy behaviours in primary schoolchildren, parents need to ensure a positive home food environment. Future sex-responsive interventions should involve both parents and children, promote healthy diets and physical activity and improve food environments in homes and schools.

Effects of performance-based capitation payment on the use of public primary health care services in Indonesia.

The Indonesian national health insurance agency BPJS Kesehatan, the largest single-payer system in the world, is among the first to combine capitation-based payments with performance-based financing. The Kapitasi Berbasis Komitmen (KBK) scheme for puskesmas (community health centres) was implemented in province capitals between August 2015 and May 2016. Its main goal was to incentivize the substitution of secondary by primary care use. We evaluate its effect on its three incentivized outcomes: the fraction of insured visiting the puskesmas, the fraction of chronically ill with a puskesmas visit and the hospital referral rate for insured with a non-specialistic condition. We use BPJS Kesehatan claims data from 2015 to 2016 from a stratified one percent sample of its members. Comparable control districts were identified using coarsened exact matching. We adopt a Difference-in-Differences (DID) study design and estimate a two-way fixed effects regression model to compare 27 intervention districts to 300 comparable non-capital control districts. We find that KBK payment increased the monthly percentage of enrolees contacting a puskesmas with 0.578 percentage points. This is a sizeable increase of 48 percent compared to the baseline rate of just 1.2% but it still leaves most puskesmas far below the "sufficient" KBK threshold of 15%. For chronically ill patients, a small increase of 1.15 percentage points was estimated, but it leaves the rate even further below the program's "sufficient" threshold of 50%. We find no statistically significant effect on referral rates to hospitals for conditions not requiring specialist care. While we find positive effects of KBK on two out of three outcomes, all estimated effect sizes leave the actual rates far below the program targets. Our findings suggest that the KBK performance-based capitation reform has not been very successful in substituting secondary care use by greater primary care use.

Unplanned readmissions after Impella mechanical circulatory support.

BACKGROUND: Early readmissions significantly impact on patient-wellbeing, burden the health-care system, and are important quality metrics. Data on 30-day readmission following Impella mechanical circulatory support (MCS) are unknown. We aimed to assess the rates, causes and clinical outcomes associated with 30-day unplanned readmissions after Impella mechanical circulatory support (MCS). METHODS: Discharged patients who underwent Impella MCS between 2016 and 2019 in the U.S. Nationwide Readmission Database were analyzed. Incidence, causes, and outcomes associated with 30-day unplanned readmissions were assessed. RESULTS: Of 22,055 patients who received Impella MCS, 2685 (12.2%) experienced 30-day readmissions. Cardiac readmissions accounted for 51.7% compared to 48.3% of non-cardiac readmissions, and most (70%) patients were readmitted back to the index hospital. Heart failure was the leading cause of cardiac readmissions accounting for 25% of them, whereas infections were the most common cause among non-cardiac readmissions. Patients who were readmitted were significantly older (median age 71 versus 68 years), more likely to be female (31% versus 26%) and had a shorter length-of-stay (index hospitalization, median 8 versus 9 days) compared to those who were not readmitted. Factors independently associated with 30-day readmissions were chronic renal (aOR: 1.46, 95% CI: 1.35-1.57), pulmonary (aOR: 1.23, 95% CI: 1.15-1.33), and liver disease (aOR: 1.38, 95% CI: 1.17-1.63), anemia (aOR: 1.35, 95% CI: 1.26-1.46), female sex (aOR: 1.21, 95% CI: 1.12-1.30), index admission on weekends (aOR: 1.23, 95% CI: 1.13-1.34), STEMI diagnosis (aOR: 1.16, 95% CI: 1.02-1.31), major adverse event during index hospitalization (aOR: 1.11, 95% CI: 1.00-1.24), prolonged length-of-stay (median 9 vs. 8 days, P < 0.001), and discharge against medical advice (aOR: 2.06, 95% CI: 1.37-3.09). Significantly higher mortality rates were overserved during readmissions to a hospital different than the MCS implanting hospital (12% versus 5.9%, P < 0.001). CONCLUSION: Thirty-day readmissions after Impella MCS are relatively common and relate to sex, baseline comorbidities, presentation, expected primary payer, discharge destination and initial length of hospital stay. Heart failure was the leading cause of cardiac readmissions, whereas infections were the most common cause among non-cardiac readmissions. Most patients were readmitted to the same hospital as their index admission for MCS. Higher mortality rates were observed when patients were readmitted to a different hospital.

The Virtues of Interpretable Medical AI.

Artificial intelligence (AI) systems have demonstrated impressive performance across a variety of clinical tasks. However, notoriously, sometimes these systems are "black boxes." The initial response in the literature was a demand for "explainable AI." However, recently, several authors have suggested that making AI more explainable or "interpretable" is likely to be at the cost of the accuracy of these systems and that prioritizing interpretability in medical AI may constitute a "lethal prejudice." In this paper, we defend the value of interpretability in the context of the use of AI in medicine. Clinicians may prefer interpretable systems over more accurate black boxes, which in turn is sufficient to give designers of AI reason to prefer more interpretable systems in order to ensure that AI is adopted and its benefits realized. Moreover, clinicians may be justified in this preference. Achieving the downstream benefits from AI is critically dependent on how the outputs of these systems are interpreted by physicians and patients. A preference for the use of highly accurate black box AI systems, over less accurate but more interpretable systems, may itself constitute a form of lethal prejudice that may diminish the benefits of AI to-and perhaps even harm-patients.

Alcohol Consumption and Atrial Arrhythmia Recurrence After Atrial Fibrillation Ablation: A Systematic Review and Meta-analysis.

BACKGROUND: Although alcohol consumption is associated with an increased risk of atrial fibrillation (AF), it is unclear whether alcohol is associated with AF recurrences after catheter ablation for AF. We aimed to systematically review the medical literature to assess the impact of alcohol consumption on the recurrence of AF after AF ablation. METHODS: A structured electronic database search of the scientific literature (Medline, Embase, and Central from inceptions to December 2021) was performed for studies reporting rates of AF recurrence after catheter ablation stratified by patients' level of alcohol consumption according to study-specific definitions. Unadjusted study-specific odds ratios (ORs) were meta-analysed with the use of random-effects models. Risk of bias was evaluated by means of the ROBINS-I tool. RESULTS: We identified 9 observational studies which included 5436 patients who underwent catheter ablation for AF. Compared with patients consuming little or no alcohol, patients consuming moderate to high amounts of alcohol had a greater risk of AF recurrence (summary OR 1.45, 95% confidence interval [CI] 1.06-1.99; P = 0.02; I2 = 79%). Results remained robust when we excluded studies with < 100 participants (OR 1.40, 95% CI 1.03-1.9) or abstract-only publications (OR 1.84, 95% CI 1.21-2.8). All included studies were found to be at serious risk of bias, primarily due to confounding. CONCLUSIONS: Increased alcohol consumption is associated with an increased risk of AF recurrence after catheter ablation for AF. Reduction of alcohol consumption may be beneficial in this context.

Diachronic and synchronic variation in the performance of adaptive machine learning systems: the ethical challenges.

OBJECTIVES: Machine learning (ML) has the potential to facilitate "continual learning" in medicine, in which an ML system continues to evolve in response to exposure to new data over time, even after being deployed in a clinical setting. In this article, we provide a tutorial on the range of ethical issues raised by the use of such "adaptive" ML systems in medicine that have, thus far, been neglected in the literature. TARGET AUDIENCE: The target audiences for this tutorial are the developers of ML AI systems, healthcare regulators, the broader medical informatics community, and practicing clinicians. SCOPE: Discussions of adaptive ML systems to date have overlooked the distinction between 2 sorts of variance that such systems may exhibit-diachronic evolution (change over time) and synchronic variation (difference between cotemporaneous instantiations of the algorithm at different sites)-and underestimated the significance of the latter. We highlight the challenges that diachronic evolution and synchronic variation present for the quality of patient care, informed consent, and equity, and discuss the complex ethical trade-offs involved in the design of such systems.

Readmissions After Left Atrial Appendage Closure in Patients With Previous Ischemic Stroke or Transient Ischemic Attack.

Background: We examined the frequency and risk factors associated with readmission after left atrial appendage closure (LAAC) in patients with and without previous ischemic stroke and/or transient ischemic attack (TIA). Methods: Hospitalizations for LAAC were identified from the US National Readmission Database, 2016-2018. The primary outcome was the first unplanned readmission after LAAC, with readmission times stratified into those occurring within 0 to 30 days vs within 31 to 180 days. Patients were stratified based on the history of previous stroke and/or TIA. Results: Of 12,901 discharges after LAAC, 28% had previous stroke and/or TIA, and 8.2% had a readmission within 30 days while 18% had a readmission within 31 to 180 days. The rates of in-hospital complications and readmissions at both periods were not significantly different between individuals with vs without previous stroke and/or TIA. Cardiac causes accounted for 28% of readmissions within 30 days and 32% of those within 31 to 180 days, and congestive failure, bleeding, and infections were the most common readmission diagnoses. New stroke and/or TIA accounted for 4% and 6% of the total noncardiac readmissions within 30 days and 31 to 180 days, respectively, and the incidence was higher among those with previous stroke and/or TIA. Female sex and index hospitalization length of stay (LOS) > 1 day were factors independently associated with readmission within 30 days, whereas LOS, diabetes, renal disease, chronic obstructive pulmonary disease, and anemia were among the factors associated with readmissions within 31 to 180 days. Conclusions: Unplanned rehospitalizations were common after LAAC and had similar frequency for patients with vs without previous ischemic stroke and/or TIA. Female sex and index hospitalization LOS > 1 day were among the strongest factors that were independently associated with readmission within 30 days.

Contexte: Nous avons examiné la fréquence et les facteurs de risque des réadmissions consécutives à une fermeture de l'appendice auriculaire gauche (FAOG) chez les patients ayant ou non subi un accident vasculaire cérébral (AVC) ischémique et/ou un accident ischémique transitoire (AIT). Méthodologie: Les hospitalisations pour une FAOG ont été recensées au moyen de la US National Readmission Database (base de données nationale des réadmissions aux États-Unis) pour la période 2016-2018. Le critère d'évaluation principal était la première réadmission non prévue après une FAOG, avec stratification du moment de la réadmission selon que celle-ci était survenue de 0 à 30 jours ou de 31 à 180 jours après l'intervention. Les patients ont été stratifiés en fonction des antécédents d'AVC et/ou d'AIT. Résultats: Parmi les 12 901 patients ayant reçu leur congé de l'hôpital après une FAOG, 28 % avaient des antécédents d'AVC et/ou d'AIT; 8,2 % des patients admissibles ont été réadmis dans les 30 jours et 18 %, entre le 31e et le 180e jour suivant l'intervention. Aucune différence significative n'a été observée entre les patients ayant subi un AVC et/ou un AIT et les patients qui n'en avaient pas subi en ce qui concerne les taux de complications hospitalières et de réadmission durant ces deux périodes. Les causes cardiaques représentaient 28 % des réadmissions dans les 30 jours et 32 % des réadmissions entre le 31e et le 180e jour. L'insuffisance cardiaque congestive, les hémorragies et les infections ont été les causes les plus fréquentes de réadmission. Les nouveaux cas d'AVC et/ou d'AIT ont respectivement été à l'origine de 4 % et de 6 % de l'ensemble des réadmissions de cause non cardiaque dans les 30 jours, et entre le 31e et le 180e jour, et leur fréquence a été plus élevée chez les patients ayant des antécédents d'AVC et/ou d'AIT. Le sexe féminin et une durée d'hospitalisation initiale > 1 jour ont été des facteurs indépendants associés aux réadmissions dans les 30 jours, tandis que la durée de l'hospitalisation, un diabète, une néphropathie, une maladie pulmonaire obstructive chronique et une anémie faisaient partie des facteurs associés aux réadmissions entre le 31e et le 180e jour. Conclusions: Les réhospitalisations non prévues ont été courantes après une FAOG, et leur fréquence a été similaire en présence ou en l'absence d'antécédents d'AVC ischémique et/ou d'AIT. Le sexe féminin et une durée d'hospitalisation initiale > 1 jour ont été les facteurs les plus importants associés aux réadmissions dans les 30 jours.

The Virtues of Interpretable Medical Artificial Intelligence.

Artificial intelligence (AI) systems have demonstrated impressive performance across a variety of clinical tasks. However, notoriously, sometimes these systems are "black boxes." The initial response in the literature was a demand for "explainable AI." However, recently, several authors have suggested that making AI more explainable or "interpretable" is likely to be at the cost of the accuracy of these systems and that prioritizing interpretability in medical AI may constitute a "lethal prejudice." In this article, we defend the value of interpretability in the context of the use of AI in medicine. Clinicians may prefer interpretable systems over more accurate black boxes, which in turn is sufficient to give designers of AI reason to prefer more interpretable systems in order to ensure that AI is adopted and its benefits realized. Moreover, clinicians may be justified in this preference. Achieving the downstream benefits from AI is critically dependent on how the outputs of these systems are interpreted by physicians and patients. A preference for the use of highly accurate black box AI systems, over less accurate but more interpretable systems, may itself constitute a form of lethal prejudice that may diminish the benefits of AI to-and perhaps even harm-patients.

Ethical implementation of mitochondrial donation in Australia.

Australia has recently legalised mitochondrial donation. However, key ethical and legal issues still need to be addressed. This paper maps the relevant issues and offers some suggestions for how they ought to be resolved.

Human Germline Genome Editing: On the Nature of Our Reasons to Genome Edit.

Ever since the publication of Derek Parfit's Reasons and Persons, bioethicists have tended to distinguish between two different ways in which reproductive technologies may have implications for the welfare of future persons. Some interventions harm or benefit particular individuals: they are "person affecting." Other interventions determine which individual, of a number of possible individuals, comes into existence: they are "identity affecting" and raise the famous "non-identity problem." For the past several decades, bioethical debate has, for the most part, proceeded on the assumption that direct genetic modification of human embryos would be person affecting. In this paper, I argue that that genome editing is highly unlikely to be person affecting for the foreseeable future and, as a result, will neither benefit nor harm edited individuals.

Outcomes of Elderly Patients Undergoing Left Atrial Appendage Closure.

Background Elderly patients have a higher burden of comorbidities that influence clinical outcomes. We aimed to compare in-hospital outcomes in patients ≥80 years old to younger patients, and to determine the factors associated with increased risk of major adverse events (MAE) after left atrial appendage closure. Methods and Results The National Inpatient Sample was used to identify discharges after left atrial appendage closure between October 2015 and December 2018. The primary outcome was in-hospital MAE defined as the composite of postprocedural bleeding, vascular and cardiac complications, acute kidney injury, stroke, and death. A total of 6779 hospitalizations were identified, of which, 2371 (35%) were ≥80 years old and 4408 (65%) were <80 years old. Patients ≥80 years old experienced a higher rate of MAE compared with those aged <80 years old (6.0% versus 4.6%, P=0.01), and this difference was driven by a numerically higher rate of cardiac complications (2.4% versus 1.8%, P=0.09) and death (0.3% versus 0.1%, P=0.05) among individuals ≥80 years old. In patients ≥80 years old, higher odds of in-hospital MAE were observed in women (1.61-fold), and those with preprocedural congestive heart failure (≈2-fold), diabetes (≈1.5-fold), renal disease (≈2.6-fold), anemia (≈2.7-fold), and dementia (≈5-fold). In patients <80 years old, a higher risk of in-hospital MAE was encountered among women (≈1.4-fold) and those with diabetes (≈1.3-fold), renal disease (≈2.6-fold), anemia (≈2-fold), and dyslipidemia (≈1.2-fold). Conclusions Patients ≥80 years old had higher rates of in-hospital MAE compared with patients aged <80 years old. Female sex and the presence of heart failure, diabetes, renal disease, and anemia were factors associated with in-hospital MAE among both groups.

Racial, ethnic and socioeconomic disparities in patients undergoing transcatheter mitral edge-to-edge repair.

BACKGROUND: Transcatheter mitral edge-to-edge repair (TEER) is an increasingly common procedure performed on patients with severe mitral regurgitation. This study assessed the impact of race/ethnicity and socioeconomic status on in-hospital complications after TEER. METHODS: Cohort-based observational study using the National Inpatient Sample between October 2013 and December 2018. The population was stratified into 4 groups based on race/ethnicity and quartiles of neighborhood income levels. The primary outcome was in-hospital complications, defined as the composite of death, bleeding, cardiac and vascular complications, acute kidney injury, and ischemic stroke. RESULTS: 3795 hospitalizations for TEER were identified. Patients of Black and Hispanic race/ethnicity comprised 7.4% and 6.4%, respectively. We estimated that White patients received TEER with a frequency of 38.0/100,000, compared to 29.7/100,000 for Blacks and 30.5/100,000 for Hispanics. In-hospital complications occurred in 20.2% of patients and no differences were found between racial/ethnic groups (P = 0.06). After multilevel modelling, Black and Hispanic patients had similar rate of overall in-hospital complications (OR: 0.84, CI:0.67-1.05 and OR: 0.84, CI:0.66-1.07, respectively) as compared to White patients, however, higher rates of death were observed in Black patients. Individuals living in income quartile-1 had worse in-hospital outcomes as compared to quartile-4 (OR: 1.19, CI:0.99-1.42). CONCLUSION: In this study assessing racial/ethnic disparities in TEER outcomes, aged-adjusted race/ethnicity minorities were less underrepresented as compared to other structural heart interventions. Black patients experienced a higher rate of in-hospital death, but similar overall rate of post-procedural adverse events as compared to White patients. Lower income levels appear to negatively impact on in-hospital outcomes. BRIEF SUMMARY: This study appraises race/ethnic and socioeconomical disparities in access and outcomes following transcatheter mitral edge-to-edge repair. Racial minority groups were less underrepresented as compared to other structural heart interventions. While Black patients experienced a higher rate of in-hospital death, they experienced similar overall rate of post-procedural complications compared to White patients. Lower income levels also appeared to negatively impact on outcomes.

Snacks, nudges and asymmetric peer influence: Evidence from food choice experiments with children in Indonesia.

Many children in low- and middle-income countries are growing up during a rapid nutrition transition. Experimental evidence on food choice in developing countries is scarce, while it is unclear to what extent evidence from high-income countries can be generalized. Children participated in a snack choice experiment. We expose some children to emoji labels encouraging healthy snacks, while others observe healthy or unhealthy snacking by peers. While emoji labels moderately promote healthy snacking, the adverse effect of observing a peer eating the unhealthy snack is very large. The effect associated with observing a healthy peer is insignificant. Additionally, cross-randomized blocks of children watched a nutrition video to study the interaction of information provision and nudging. The video independently improves healthy choices but does not aid the emoji nudge and cannot counter the strong negative peer effect. We compare our findings to studies conducted in developed countries and discuss policy implications.

Economic Consequences of Ill-Health in Rural Ethiopia.

We use three years of household panel data to analyze the effects of ill-health on household economic outcomes in rural Ethiopia. We examine the immediate effects of various ill-health measures on health expenditure and labor supply, the subsequent coping responses, and finally the effect on income and consumption. We find evidence of substantial economic risk in terms of increased health expenditure and reduced agricultural productivity. Households are able to smooth consumption by resorting to intra-household labor substitution, borrowing and depleting assets. However, maintaining current consumption through borrowing and depletion of assets is unlikely to be sustainable and displays the need for health financing reforms and safety nets that reduce the financial consequences of ill-health.

Adolescent Nutrition-Developing a Research Agenda for the Second Window of Opportunity in Indonesia.

BACKGROUND: Recently, adolescence has been identified as a second window of opportunity for the correction of nutritional inadequacies. However, there is a lack of knowledge on evidence-based integrated nutrition strategies for adolescents in Indonesia. OBJECTIVE: To provide a research agenda and the prioritization of research actions to tackle outstanding knowledge gaps on adolescent nutrition in Indonesia. METHODS: A preliminary set of research topics was listed based on a desk study of the academic literature and policy documents. Second, a stakeholder meeting was held to further identify and discuss research topics related to adolescent nutrition in Indonesia. Third, an online survey was conducted in which respondents were asked to indicate priority research themes for the next 3 to 5 years and to rank a total of 23 research questions. RESULTS: Most (52%) of the respondents who returned the survey (n = 27) prioritize research on implementation and program evaluation, while 30% prefer descriptive and explanatory research, and 19% place priority with intervention and discovery research. However, when we followed up with specific topics for each of these broad research areas, a more nuanced picture emerged, with intervention and discovery research taking a more prominent standing. CONCLUSIONS: In order to support the design, implementation, and effectiveness of integrated nutrition programs for Indonesian adolescents, in-depth studies should question the best intervention strategies, modes of delivery, and long-term outcomes, while nationwide and disaggregated data should investigate associations and trends over time and identify vulnerable groups.

Sex Differences in Outcomes Following Left Atrial Appendage Closure.

OBJECTIVE: To evaluate the effects of female sex on in-hospital outcomes and to provide estimates for sex-specific prediction models of adverse outcomes following left atrial appendage closure (LAAC). PATIENTS AND METHODS: Cohort-based observational study querying the National Inpatient Sample database between October 1, 2015, and December 31, 2017. Demographics, baseline characteristics, and comorbidities were assessed with the Charlson Comorbidity Index (CCI), Elixhauser Comorbidity Index score (ECS), and CHA2DS2-VASc score. The primary outcome was in-hospital major adverse events (MAEs) defined as the composite of bleeding, vascular, cardiac complications, post-procedural stroke, and acute kidney injury. The associations of the CCI, ECS, and CHA2DS2-VASc score with in-hospital MAE were examined using logistic regression models for women and men, respectively. RESULTS: A total of 3294 hospitalizations were identified, of which 1313 (40%) involved women and 1981 (60%) involved men. Women were older (76.3±7.7 vs 75.2±8.4 years, P<.001), had a higher CHA2DS2-VASc score (4.9±1.4 vs 3.9±1.4, P<.001) but showed lower CCI and ECS compared with men (2.1±1.9 vs 2.3±1.9, P=.01; and 9.3±5.9 vs 9.9±5.7, P=.002, respectively). The primary composite outcome occurred in 4.6% of patients and was higher in women compared with men (women 5.6% vs men 4.0%, P=.04), and this was mainly driven by the occurrence of cardiac complications (2.4% vs 1.2%, P=.01). In women, older age, higher median income, and higher CCI (adjusted odds ratio [aOR], 1.32; 95% confidence interval [CI], 1.21 to 1.44; P<.001), ECS (aOR, 1.04; 95% CI, 1.02 to 1.07; P=.002), and CHA2DS2-VASc score (aOR, 1.24; 95% CI, 1.10 to 1.39; P<.001) were associated with increased risk of in-hospital MAE. In men, non-White race/ethnicity, lower median income, and higher ECS (aOR, 1.06; 95% CI, 1.04 to 1.09; P<.001) were associated with increased risk of in-hospital MAE. CONCLUSION: Women had higher rates of in-hospital adverse events following LAAC than men did. Women with older age and higher median income, CCI, ECS, and CHA2DS2-VASc scores were associated with in-hospital adverse events, whereas men with non-White race/ethnicity, lower median income, and higher ECS were more likely to experience adverse events. Further research is warranted to identify sex-specific, racial/ethnic, and socioeconomic pathways during the patient selection process to minimize complications in patients undergoing LAAC.