Spatiotemporal analysis of the association between Kawasaki disease incidence and PM2.5 exposure: a nationwide database study in Japan.

BACKGROUND: Kawasaki disease (KD) is an acute vasculitis primarily affecting children. While some studies suggest a link between KD and PM2.5 exposure, findings remain inconsistent. This study aimed to perform spatiotemporal analysis to investigate the impact of monthly and annual exposure to PM2.5 and other air pollutants on the incidence of KD before and after the advent of the COVID-19 pandemic. METHODS: In this retrospective analysis, we used the Japanese administrative claims database to identify the incidence of KD in children under age 5 in 335 secondary medical care areas across Japan before (from July 2014 to December 2019) and during (from January 2020 to December 2021) the COVID-19 pandemic. For each of these periods, we developed hierarchical Bayesian models termed conditional autoregressive (CAR) models that can address the spatiotemporal clustering of KD to investigate the association between the monthly incidence of KD and exposure to PM2.5, NO, NO2 and SO2 over 1-month and 12-month durations. The pollution data were collected from publicly available data provided by the National Institute for Environmental Studies. RESULTS: In the before-pandemic and during-pandemic periods, 55 289 and 14 023 new cases of KD were identified, respectively. The CAR models revealed that only 12-month exposure to PM2.5 was consistently correlated with KD incidence, and each 1 µg/m3 increase in annual PM2.5 exposure corresponded to a 3%-10% rise in KD incidence. Consistent outcomes were observed in the age-stratified sensitivity analysis. CONCLUSIONS: Annual exposure to PM2.5 was robustly linked with the onset of KD. Further research is needed to elucidate the underlying mechanism by which the spatiotemporal distribution of PM2.5 is associated with KD.

Immediate postnatal prediction of death or bronchopulmonary dysplasia among very preterm and very low birth weight infants based on gradient boosting decision trees algorithm: A nationwide database study in Japan.

INTRODUCTION: Bronchopulmonary dysplasia (BPD) poses a substantial global health burden. Individualized treatment strategies based on early prediction of the development of BPD can mitigate preterm birth complications; however, previously suggested predictive models lack early postnatal applicability. We aimed to develop predictive models for BPD and mortality based on immediate postnatal clinical data. METHODS: Clinical information on very preterm and very low birth weight infants born between 2008 and 2018 was extracted from a nationwide Japanese database. The gradient boosting decision trees (GBDT) algorithm was adopted to predict BPD and mortality, using predictors within the first 6 h postpartum. We assessed the temporal validity and evaluated model adequacy using Shapley additive explanations (SHAP) values. RESULTS: We developed three predictive models using data from 39,488, 39,096, and 40,291 infants to predict "death or BPD," "death or severe BPD," and "death before discharge," respectively. These well-calibrated models achieved areas under the receiver operating characteristic curve of 0.828 (95% CI: 0.828-0.828), 0.873 (0.873-0.873), and 0.887 (0.887-0.888), respectively, outperforming the multivariable logistic regression models. SHAP value analysis identified predictors of BPD, including gestational age, size at birth, male sex, and persistent pulmonary hypertension. In SHAP value-based case clustering, the "death or BPD" prediction model stratified infants by gestational age and persistent pulmonary hypertension, whereas the other models for "death or severe BPD" and "death before discharge" commonly formed clusters of low mortality, extreme prematurity, low Apgar scores, and persistent pulmonary hypertension of the newborn. CONCLUSIONS: GBDT models for predicting BPD and mortality, designed for use within 6 h postpartum, demonstrated superior prognostic performance. SHAP value-based clustering, a data-driven approach, formed clusters of clinical relevance. These findings suggest the efficacy of a GBDT algorithm for the early postnatal prediction of BPD.

Geographical distribution of antimicrobial exposure among very preterm and very low birth weight infants: A nationwide database study in Japan.

OBJECTIVES: To examine spatial effects in neonatal care, we conducted a retrospective cohort study to investigate the geographical distribution of antimicrobial exposure among very preterm and very low birth weight infants in Japan. STUDY DESIGN: We utilized a nationwide claims database in Japan to extract prescriptions of injectable antimicrobials for 41,423 very preterm and very low birth weight infants admitted within the first two days of life from April 2010 to March 2021. We identified frequently prescribed antimicrobials, revealed early neonatal exposure and neonatal exposure to each antimicrobial agent by 47 prefectures in Japan, and evaluated their spatial autocorrelation using global and local Moran's I statistics. We then scrutinized regional disparities in antimicrobial drug prescriptions. RESULTS: The top 10 antimicrobials prescribed to very preterm and very low birth weight infants in Japan were ampicillin, amikacin, gentamicin, cefotaxime, fluconazole, ampicillin combination, micafungin, cefmetazole, cefazolin, and vancomycin. We identified northern cold spots for fluconazole exposure and southern hot spots for ampicillin, amikacin, gentamicin, and cefmetazole exposure. Geographical heterogeneity in the selection of antibacterial and antimycotic agents was observed. CONCLUSION: Our study revealed the geographical distribution of antimicrobial exposure among very preterm and very low birth weight infants in Japan, thus disclosing its spatial effects. Further research addressing the spatial effects of neonatal care is needed to understand how drug exposure affects the outcomes of preterm infants.

Development of mortality prediction models for infants with isolated, left-sided congenital diaphragmatic hernia before and after birth.

BACKGROUND: Mortality prediction of congenital diaphragmatic hernia (CDH) is essential for developing treatment strategies, including fetal therapy. Several researchers have reported prognostic factors for this rare but life-threatening condition; however, the optimal combination of prognostic factors remains to be elucidated. OBJECTIVES: This study aimed to develop the most discriminative prenatal and postnatal models to predict the mortality of infants with an isolated left-sided CDH. METHODS: This multi-institutional retrospective cohort study included infants with CDH born at 15 tertiary hospitals of the Japanese CDH Study Group between 2011 and 2016. We developed multivariable logistic models with every possible combination of predictors and identified models with the highest cross-validated area under the receiver operating characteristic curve (AUC) for prenatal and postnatal predictions. RESULTS: Among 302 eligible infants, 44 died before discharge. The prenatal mortality prediction model was based on the observed/expected lung area to head circumference ratio (O/E LHR), liver herniation, and stomach herniation (AUC, 0.830). The postnatal mortality prediction model was based on O/E LHR, liver herniation, and the lowest oxygenation index (AUC, 0.944). CONCLUSION: Our models can facilitate the prenatal and postnatal mortality prediction of infants with isolated left-sided CDH.

Computational Pipeline for Glomerular Segmentation and Association of the Quantified Regions with Prognosis of Kidney Function in IgA Nephropathy.

The histopathological findings of the glomeruli from whole slide images (WSIs) of a renal biopsy play an important role in diagnosing and grading kidney disease. This study aimed to develop an automated computational pipeline to detect glomeruli and to segment the histopathological regions inside of the glomerulus in a WSI. In order to assess the significance of this pipeline, we conducted a multivariate regression analysis to determine whether the quantified regions were associated with the prognosis of kidney function in 46 cases of immunoglobulin A nephropathy (IgAN). The developed pipelines showed a mean intersection over union (IoU) of 0.670 and 0.693 for five classes (i.e., background, Bowman's space, glomerular tuft, crescentic, and sclerotic regions) against the WSI of its facility, and 0.678 and 0.609 against the WSI of the external facility. The multivariate analysis revealed that the predicted sclerotic regions, even those that were predicted by the external model, had a significant negative impact on the slope of the estimated glomerular filtration rate after biopsy. This is the first study to demonstrate that the quantified sclerotic regions that are predicted by an automated computational pipeline for the segmentation of the histopathological glomerular components on WSIs impact the prognosis of kidney function in patients with IgAN.

Neonatal systemic juvenile Xanthogranuloma with Hydrops diagnosed by Purpura skin biopsy: a case report and literature review.

BACKGROUND: Systemic juvenile xanthogranuloma is a very rare disease typically presents as skin lesions with yellow papules or nodules and is sometimes fatal. We report a case of congenital neonatal systemic juvenile xanthogranuloma with atypical skin appearance that made the diagnosis difficult. CASE PRESENTATION: A preterm Japanese female neonate with prenatally diagnosed fetal hydrops in-utero was born with purpuric lesions involving the trunk and face. Since birth, she had hypoxemic respiratory failure, splenomegaly, anemia, thrombocytopenia, coagulopathy, and was transfusion dependent for red blood cells, fresh frozen plasma, and platelets. Multiple cystic lesions in her liver, part of them with vascular, were detected by ultrasound. A liver biopsy was inconclusive. A skin lesion on her face similar to purpura gradually changed to a firm and solid enlarged non-yellow nodule. Technically, the typical finding on skin biopsy would have been histiocytic infiltration (without Touton Giant cells) and immunohistochemistry results which then would be consistent with a diagnosis of systemic juvenile xanthogranuloma, and chemotherapy improved her general condition. CONCLUSIONS: This case report shows that skin biopsies are necessary to detect neonatal systemic juvenile xanthogranuloma when there are organ symptoms and skin eruption, even if the skin lesion does not have a typical appearance of yellow papules or nodules.