Mean Arterial Pressure and Neonatal Outcomes in Pregnancies Complicated by Mild Chronic Hypertension.

OBJECTIVE: To estimate the association between mean arterial pressure during pregnancy and neonatal outcomes in participants with chronic hypertension using data from the CHAP (Chronic Hypertension and Pregnancy) trial. METHODS: A secondary analysis of the CHAP trial, an open-label, multicenter randomized trial of antihypertensive treatment in pregnancy, was conducted. The CHAP trial enrolled participants with mild chronic hypertension (blood pressure [BP] 140-159/90-104 mm Hg) and singleton pregnancies less than 23 weeks of gestation, randomizing them to active treatment (maintained on antihypertensive therapy with a goal BP below 140/90 mm Hg) or standard treatment (control; antihypertensives withheld unless BP reached 160 mm Hg systolic BP or higher or 105 mm Hg diastolic BP or higher). We used logistic regression to measure the strength of association between mean arterial pressure (average and highest across study visits) and to select neonatal outcomes. Unadjusted and adjusted odds ratios (per 1-unit increase in millimeters of mercury) of the primary neonatal composite outcome (bronchopulmonary dysplasia, retinopathy of prematurity, necrotizing enterocolitis, or intraventricular hemorrhage grade 3 or 4) and individual secondary outcomes (neonatal intensive care unit admission [NICU], low birth weight [LBW] below 2,500 g, and small for gestational age [SGA]) were calculated. RESULTS: A total of 2,284 participants were included: 1,155 active and 1,129 control. Adjusted models controlling for randomization group demonstrated that increasing average mean arterial pressure per millimeter of mercury was associated with an increase in each neonatal outcome examined except NEC, specifically neonatal composite (adjusted odds ratio [aOR] 1.12, 95% CI, 1.09-1.16), NICU admission (aOR 1.07, 95% CI, 1.06-1.08), LBW (aOR 1.12, 95% CI, 1.11-1.14), SGA below the fifth percentile (aOR 1.03, 95% CI, 1.01-1.06), and SGA below the 10th percentile (aOR 1.02, 95% CI, 1.01-1.04). Models using the highest mean arterial pressure as opposed to average mean arterial pressure also demonstrated consistent associations. CONCLUSION: Increasing mean arterial pressure was positively associated with most adverse neonatal outcomes except NEC. Given that the relationship between mean arterial pressure and adverse pregnancy outcomes may not be consistent at all mean arterial pressure levels, future work should attempt to further elucidate whether there is an absolute threshold or relative change in mean arterial pressure at which fetal benefits are optimized along with maternal benefits. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, NCT02299414.

Psychiatric Diagnoses Are Associated With Postoperative Disparities in Patients Undergoing Major Colorectal Operations.

BACKGROUND: Over 50% of hospitalized patients have comorbid psychiatric diagnoses, resulting in increased risk of morbidity such as longer lengths of stay, worse health-related quality of life, and increased mortality. However, data regarding colorectal surgery postoperative outcomes in patients with psychiatric diagnoses (PD) are limited. METHODS: We queried a single institution's National Surgical Quality Improvement Program from 2013-2019 for major colorectal procedures. Postsurgical outcomes for patients with and without PD were compared. Primary outcomes were prolonged length of stay (pLOS) and 30-day readmission. RESULTS: From a total of 1447 patients, 402 (27.8%) had PD. PD had more smokers (20.9% vs 15%) and higher mean body mass index (29.1 kg/m2 vs 28.2 kg/m2). Bivariate outcomes showed more surgical site infections (SSI) (10.2% vs 6.12%), reoperation (9.45% vs 6.35%), and pLOS (34.8% vs 29.0%) (all P values <.05) in the PD group. On multivariate analysis, PD had higher likelihood of reoperation (OR 1.53, 95% CI: [1.02-2.80]) and SSI (OR 1.82, 95% CI: [1.25-2.66]). DISCUSSION: Psychiatric diagnoses are a risk factor for adverse outcomes after colorectal procedures. Further studies are needed to evaluate the benefit of perioperative mental health support services for these patients.

Improving dengue fever predictions in Taiwan based on feature selection and random forests.

BACKGROUND: Dengue fever is a well-studied vector-borne disease in tropical and subtropical areas of the world. Several methods for predicting the occurrence of dengue fever in Taiwan have been proposed. However, to the best of our knowledge, no study has investigated the relationship between air quality indices (AQIs) and dengue fever in Taiwan. RESULTS: This study aimed to develop a dengue fever prediction model in which meteorological factors, a vector index, and AQIs were incorporated into different machine learning algorithms. A total of 805 meteorological records from 2013 to 2015 were collected from government open-source data after preprocessing. In addition to well-known dengue-related factors, we investigated the effects of novel variables, including particulate matter with an aerodynamic diameter < 10 µm (PM10), PM2.5, and an ultraviolet index, for predicting dengue fever occurrence. The collected dataset was randomly divided into an 80% training set and a 20% test set. The experimental results showed that the random forests achieved an area under the receiver operating characteristic curve of 0.9547 for the test set, which was the best compared with the other machine learning algorithms. In addition, the temperature was the most important factor in our variable importance analysis, and it showed a positive effect on dengue fever at < 30 °C but had less of an effect at > 30 °C. The AQIs were not as important as temperature, but one was selected in the process of filtering the variables and showed a certain influence on the final results. CONCLUSIONS: Our study is the first to demonstrate that AQI negatively affects dengue fever occurrence in Taiwan. The proposed prediction model can be used as an early warning system for public health to prevent dengue fever outbreaks.

Placental differences between severe fetal growth restriction and hypertensive disorders of pregnancy requiring early preterm delivery: morphometric analysis of the villous tree supported by artificial intelligence.

BACKGROUND: The great obstetrical syndromes of fetal growth restriction and hypertensive disorders of pregnancy can occur individually or be interrelated. Placental pathologic findings often overlap between these conditions, regardless of whether 1 or both diagnoses are present. Quantification of placental villous structures in each of these settings may identify distinct differences in developmental pathways. OBJECTIVE: This study aimed to determine how the quantity and surface area of placental villi and vessels differ between severe, early-onset fetal growth restriction with absent or reversed umbilical artery Doppler indices and hypertensive disorders of pregnancy or the 2 conditions combined among subjects with disease severity that warrant early preterm delivery. We hypothesized that the trajectories of placental morphogenesis diverge after a common initiating insult of deep defective placentation. Specifically, we postulated that only villi are affected in pregnancy-related hypertension, whereas both villous and vascular structures are proportionally diminished in severe fetal growth restriction with no additional effect when hypertension is concomitantly present. STUDY DESIGN: In this retrospective cohort study, paraffin-embedded placental tissue was obtained from 4 groups, namely (1) patients with severe fetal growth restriction with absent or reversed umbilical artery end-diastolic velocities and hypertensive disorders of pregnancy, (2) patients with severe fetal growth restriction with absent or reversed umbilical artery Doppler indices and no hypertension, (3) gestational age-matched, appropriately grown pregnancies with hypertensive disease, and (4) gestational age-matched, appropriately grown pregnancies without hypertension. Dual immunohistochemistry for cytokeratin-7 (trophoblast) and CD34 (endothelial cells) was performed, followed by artificial intelligence-driven morphometric analyses. The number of villi, total villous area, number of fetoplacental vessels, and total vascular area across villi within a uniform region of interest were quantified. Quantitative analyses of placental structures were modeled using linear regression. RESULTS: Placentas from pregnancies complicated by hypertensive disorders of pregnancy exhibited significantly fewer stem villi (-282 stem villi; 95% confidence interval, -467 to -98; P<.01), a smaller stem villous area (-4.3 mm2; 95% confidence interval, -7.3 to -1.2; P<.01), and fewer stem villous vessels (-4967 stem villous vessels; 95% confidence interval, -8501 to -1433; P<.01) with no difference in the total vascular area. In contrast, placental abnormalities in cases with severe growth restriction were limited to terminal villi with global decreases in the number of villi (-873 terminal villi; 95% confidence interval, -1501 to -246; P<.01), the villous area (-1.5 mm2; 95% confidence interval, -2.7 to -0.4; P<.01), the number of blood vessels (-5165 terminal villous vessels; 95% confidence interval, -8201 to -2128; P<.01), and the vascular area (-0.6 mm2; 95% confidence interval, -1.1 to -0.1; P=.02). The combination of hypertension and growth restriction had no additional effect beyond the individual impact of each state. CONCLUSION: Pregnancies complicated by hypertensive disorders of pregnancy exhibited defects in the stem villi only, whereas placental abnormalities in severely growth restricted pregnancies with absent or reversed umbilical artery end-diastolic velocities were limited to the terminal villi. There were no significant statistical interactions in the combination of growth restriction and hypertension, suggesting that distinct pathophysiological pathways downstream of the initial insult of defective placentation are involved in each entity and do not synergize to lead to more severe pathologic consequences. Delineating mechanisms that underly the divergence in placental development after a common inciting event of defective deep placentation may shed light on new targets for prevention or treatment.

Prognosticating Fetal Growth Restriction and Small for Gestational Age by Medical History.

This study aimed to develop and externally validate a prognostic prediction model for screening fetal growth restriction (FGR)/small for gestational age (SGA) using medical history. From a nationwide health insurance database (n=1,697,452), we retrospectively selected visits of 12-to-55-year-old females to healthcare providers. This study used machine learning (including deep learning) and 54 medical-history predictors. The best model was a deep-insight visible neural network (DI-VNN). It had area under the curve of receiver operating characteristics (AUROC) 0.742 (95% CI 0.734 to 0.750) and a sensitivity of 49.09% (95% CI 47.60% to 50.58% at with 95% specificity). Our model used medical history for screening FGR/SGA with moderate accuracy by DI-VNN. In future work, we will compare this model with those from systematically-reviewed, previous studies and evaluate if this model's usage impacts patient outcomes.

Assessing Internet Search Models in Predicting Daily New COVID-19 Cases and Deaths in South Korea.

Search data were found to be useful variables for COVID-19 trend prediction. In this study, we aimed to investigate the performance of online search models in state space models (SSMs), linear regression (LR) models, and generalized linear models (GLMs) for South Korean data from January 20, 2020, to July 31, 2021. Principal component analysis (PCA) was run to construct the composite features which were later used in model development. Values of root mean squared error (RMSE), peak day error (PDE), and peak magnitude error (PME) were defined as loss functions. Results showed that integrating search data in the models for short- and long-term prediction resulted in a low level of RMSE values, particularly for SSMs. Findings indicated that type of model used highly impacts the performance of prediction and interpretability of the model. Furthermore, PDE and PME could be beneficial to be included in the evaluation of peaks.

Low- and high-level information analyses of transcriptome connecting endometrial-decidua-placental origin of preeclampsia subtypes: A preliminary study.

BACKGROUND: Existing proposed pathogenesis for preeclampsia (PE) was only applied for early onset subtype and did not consider pre-pregnancy and competing risks. We aimed to decipher PE subtypes by identifying related transcriptome that represents endometrial maturation and histologic chorioamnionitis. METHODS: We utilized eight arrays of mRNA expression for discovery (n=289), and other eight arrays for validation (n=352). Differentially expressed genes (DEGs) were overlapped between those of: (1) healthy samples from endometrium, decidua, and placenta, and placenta samples under histologic chorioamnionitis; and (2) placenta samples for each of the subtypes. They were all possible combinations based on four axes: (1) pregnancy-induced hypertension; (2) placental dysfunction-related diseases (e.g., fetal growth restriction [FGR]); (3) onset; and (4) severity. RESULTS: The DEGs of endometrium at late-secretory phase, but none of decidua, significantly overlapped with those of any subtypes with: (1) early onset (p-values ≤0.008); (2) severe hypertension and proteinuria (p-values ≤0.042); or (3) chronic hypertension and/or severe PE with FGR (p-values ≤0.042). Although sharing the same subtypes whose DEGs with which significantly overlap, the gene regulation was mostly counter-expressed in placenta under chorioamnionitis (n=13/18, 72.22%; odds ratio [OR] upper bounds ≤0.21) but co-expressed in late-secretory endometrium (n=3/9, 66.67%; OR lower bounds ≥1.17). Neither the placental DEGs at first-nor second-trimester under normotensive pregnancy significantly overlapped with those under late-onset, severe PE without FGR. CONCLUSIONS: We identified the transcriptome of endometrial maturation in placental dysfunction that distinguished early- and late-onset PE, and indicated chorioamnionitis as a PE competing risk. This study implied a feasibility to develop and validate the pathogenesis models that include pre-pregnancy and competing risks to decide if it is needed to collect prospective data for PE starting from pre-pregnancy including chorioamnionitis information.

Uteroplacental insufficiency decreases leptin expression and impairs lung development in growth-restricted newborn rats.

BACKGROUND: The study aimed to analyze the effect of uteroplacental insufficiency (UPI) on leptin expression and lung development of intrauterine growth restriction (IUGR) rats. METHODS: On day 17 of pregnancy, time-dated Sprague-Dawley rats were randomly divided into either an IUGR group or a control group. Uteroplacental insufficiency surgery (IUGR) and sham surgery (control) were conducted. Offspring rats were spontaneously delivered on day 22 of pregnancy. On postnatal days 0 and 7, rats' pups were selected at random from the control and IUGR groups. Blood was withdrawn from the heart to determine leptin levels. The right lung was obtained for leptin and leptin receptor levels, immunohistochemistry, proliferating cell nuclear antigen (PCNA), western blot, and metabolomic analyses. RESULTS: UPI-induced IUGR decreased leptin expression and impaired lung development, causing decreased surface area and volume in offspring. This results in lower body weight, decreased serum leptin levels, lung leptin and leptin receptor levels, alveolar space, PCNA, and increased alveolar wall volume fraction in IUGR offspring rats. The IUGR group found significant relationships between serum leptin, radial alveolar count, von Willebrand Factor, and metabolites. CONCLUSION: Leptin may contribute to UPI-induced lung development during the postnatal period, suggesting supplementation as a potential treatment. IMPACT: The neonatal rats with intrauterine growth restriction (IUGR) caused by uteroplacental insufficiency (UPI) showed decreased leptin expression and impaired lung development. UPI-induced IUGR significantly decreased surface area and volume in lung offspring. This is a novel study that investigates leptin expression and lung development in neonatal rats with IUGR caused by UPI. If our findings translate to IUGR infants, leptin may contribute to UPI-induced lung development during the postnatal period, suggesting supplementation as a potential treatment.

Analysis of the human kidney transcriptome and plasma proteome identifies markers of proximal tubule maladaptation to injury.

Acute kidney injury (AKI) is a major risk factor for long-term adverse outcomes, including chronic kidney disease. In mouse models of AKI, maladaptive repair of the injured proximal tubule (PT) prevents complete tissue recovery. However, evidence for PT maladaptation and its etiological relationship with complications of AKI is lacking in humans. We performed single-nucleus RNA sequencing of 120,985 nuclei in kidneys from 17 participants with AKI and seven healthy controls from the Kidney Precision Medicine Project. Maladaptive PT cells, which exhibited transcriptomic features of dedifferentiation and enrichment in pro-inflammatory and profibrotic pathways, were present in participants with AKI of diverse etiologies. To develop plasma markers of PT maladaptation, we analyzed the plasma proteome in two independent cohorts of patients undergoing cardiac surgery and a cohort of marathon runners, linked it to the transcriptomic signatures associated with maladaptive PT, and identified nine proteins whose genes were specifically up- or down-regulated by maladaptive PT. After cardiac surgery, both cohorts of patients had increased transforming growth factor-ß2 (TGFB2), collagen type XXIII-α1 (COL23A1), and X-linked neuroligin 4 (NLGN4X) and had decreased plasminogen (PLG), ectonucleotide pyrophosphatase/phosphodiesterase 6 (ENPP6), and protein C (PROC). Similar changes were observed in marathon runners with exercise-associated kidney injury. Postoperative changes in these markers were associated with AKI progression in adults after cardiac surgery and post-AKI kidney atrophy in mouse models of ischemia-reperfusion injury and toxic injury. Our results demonstrate the feasibility of a multiomics approach to discovering noninvasive markers and associating PT maladaptation with adverse clinical outcomes.

Symptom-based scoring technique by machine learning to predict COVID-19: a validation study.

BACKGROUND: Coronavirus disease 2019 (COVID-19) surges, such as that which occurred when omicron variants emerged, may overwhelm healthcare systems. To function properly, such systems should balance detection and workloads by improving referrals using simple yet precise and sensitive diagnostic predictions. A symptom-based scoring system was developed using machine learning for the general population, but no validation has occurred in healthcare settings. We aimed to validate a COVID-19 scoring system using self-reported symptoms, including loss of smell and taste as major indicators. METHODS: A cross-sectional study was conducted to evaluate medical records of patients admitted to Dr. Sardjito Hospital, Yogyakarta, Indonesia, from March 2020 to December 2021. Outcomes were defined by a reverse-transcription polymerase chain reaction (RT-PCR). We compared the symptom-based scoring system, as the index test, with antigen tests, antibody tests, and clinical judgements by primary care physicians. To validate use of the index test to improve referral, we evaluated positive predictive value (PPV) and sensitivity. RESULTS: After clinical judgement with a PPV of 61% (n = 327/530, 95% confidence interval [CI]: 60% to 62%), confirmation with the index test resulted in the highest PPV of 85% (n = 30/35, 95% CI: 83% to 87%) but the lowest sensitivity (n = 30/180, 17%, 95% CI: 15% to 19%). If this confirmation was defined by either positive predictive scoring or antigen tests, the PPV was 92% (n = 55/60, 95% CI: 90% to 94%). Meanwhile, the sensitivity was 88% (n = 55/62, 95% CI: 87% to 89%), which was higher than that when using only antigen tests (n = 29/41, 71%, 95% CI: 69% to 73%). CONCLUSIONS: The symptom-based COVID-19 predictive score was validated in healthcare settings for its precision and sensitivity. However, an impact study is needed to confirm if this can balance detection and workload for the next COVID-19 surge.

Angiogenic Function of Human Placental Endothelial Cells in Severe Fetal Growth Restriction Is Not Rescued by Individual Extracellular Matrix Proteins.

Severe fetal growth restriction (FGR) is characterized by increased placental vascular resistance resulting from aberrant angiogenesis. Interactions between endothelial cells (ECs) and the extracellular matrix (ECM) are critical to the complex process of angiogenesis. We have previously found that placental stromal abnormalities contribute to impaired angiogenesis in severe FGR. The objective of this research is to better characterize the effect of individual ECM proteins on placental angiogenic properties in the setting of severe FGR. ECs were isolated from human placentae, either control or affected by severe FGR, and subjected to a series of experiments to interrogate the role of ECM proteins on adhesion, proliferation, migration, and apoptosis. We found impaired proliferation and migration of growth-restricted ECs. Although individual substrates did not substantially impact migratory capacity, collagens I, III, and IV partially mitigated proliferative defects seen in FGR ECs. Differences in adhesion and apoptosis between control and FGR ECs were not evident. Our findings demonstrate that placental angiogenic defects that characterize severe FGR cannot be explained by a singular ECM protein, but rather, the placental stroma as a whole. Further investigation of the effects of stromal composition, architecture, stiffness, growth factor sequestration, and capacity for remodeling is essential to better understand the role of ECM in impaired angiogenesis in severe FGR.

Perinatal Outcomes Associated With Management of Stage 1 Hypertension.

OBJECTIVE: To evaluate the association between maternal blood pressure (BP) below 130/80 mm Hg compared with 130-139/80-89 mm Hg and pregnancy outcomes. METHODS: We conducted a planned secondary analysis of CHAP (Chronic Hypertension and Pregnancy), an open label, multicenter, randomized controlled trial. Participants with mean BP below 140/90 mm Hg were grouped as below 130/80 mm Hg compared with 130-139/80-89 mm Hg by averaging postrandomization clinic BP throughout pregnancy. The primary composite outcome was preeclampsia with severe features, indicated preterm birth before 35 weeks of gestation, placental abruption, or fetal or neonatal death. The secondary outcome was small for gestational age (SGA). RESULTS: Of 2,408 patients in CHAP, 2,096 met study criteria; 1,328 had mean BP 130-139/80-89 mm Hg and 768 had mean BP below 130/80 mm Hg. Participants with mean BP below 130/80 mm Hg were more likely to be older, on antihypertensive medication, in the active treatment arm, and to have lower BP at enrollment. Mean clinic BP below 130/80 mm Hg was associated with lower frequency of the primary outcome (16.0% vs 35.8%, adjusted relative risk 0.45; 95% CI 0.38-0.54) as well as lower risk of severe preeclampsia and indicated birth before 35 weeks of gestation. There was no association with SGA. CONCLUSION: In pregnant patients with mild chronic hypertension, mean BP below 130/80 mm Hg was associated with improved pregnancy outcomes without increased risk of SGA. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov , NCT02299414.

Scaling the EVERREST of severe, early-onset fetal growth restriction.

Severe, early-onset fetal growth restriction is a leading cause of medically indicated preterm birth and substantially increases the risk for perinatal death or disability. No treatments exist to improve fetal growth or safely prolong pregnancy. Furthermore, wide-ranging phenotypes limit the accurate prediction of pregnancy outcome. In this issue of the JCI, Spencer and colleagues combine a discovery-science approach with ultrasound parameters to identify the most discriminative models for predicting either the primary outcome of fetal or neonatal death, or a secondary outcome of death or delivery at 28 weeks of gestation or earlier. Their findings can better individualize patient counseling but, just as compellingly, provide the capacity to identify those pregnancies that are at such considerable risk as to justify enrollment in paradigm-shifting interventional trials that are in the pipeline.

Breastfeeding initiation and duration among people with mild chronic hypertension: a secondary analysis of the Chronic Hypertension and Pregnancy trial.

BACKGROUND: Increased duration of breastfeeding improves maternal cardiovascular health and may be especially beneficial in high-risk populations, such as those with chronic hypertension. Others have shown that individuals with hypertension are less likely to breastfeed, and there has been limited research aimed at supporting breastfeeding goals in this population. The impact of perinatal blood pressure control on breastfeeding outcomes among people with chronic hypertension is unknown. OBJECTIVE: This study aimed to evaluate whether breastfeeding initiation and short-term duration assessed at the postpartum clinic visit differed according to perinatal blood pressure treatment strategy (targeting blood pressure <140/90 mm Hg vs reserving antihypertensive treatment for blood pressure ≥160/105 mm Hg). STUDY DESIGN: We performed a secondary analysis of the Chronic Hypertension and Pregnancy trial. This was an open-label, multicenter, randomized trial where pregnant participants with mild chronic hypertension were randomized to receive antihypertensive medications with goal blood pressure <140/90 mm Hg (active treatment) or deferred treatment until blood pressure ≥160/105 mm Hg (control). The primary outcome was initiation and duration of breastfeeding, assessed at the postpartum clinic visit. We performed bivariate analyses and log-binomial and cumulative logit regression models, adjusting models for variables that were unbalanced in bivariate analyses. We performed additional analyses to explore the relationship between breastfeeding duration and blood pressure measurements at the postpartum visit. RESULTS: Of the 2408 participants from the Chronic Hypertension and Pregnancy trial, 1444 (60%) attended the postpartum study visit and provided breastfeeding information. Participants in the active treatment group had different body mass index class distribution and earlier gestational age at enrollment, and (by design) were more often discharged on antihypertensives. Breastfeeding outcomes did not differ significantly by treatment group. In the active and control treatment groups, 563 (77.5%) and 561 (78.1%) initiated breastfeeding, and mean durations of breastfeeding were 6.5±2.3 and 6.3±2.1 weeks, respectively. The probability of ever breastfeeding (adjusted relative risk, 0.99; 95% confidence interval, 0.93-1.05), current breastfeeding at postpartum visit (adjusted relative risk, 1.01; 95% confidence interval, 0.94-1.10), and weeks of breastfeeding (adjusted odds ratio, 0.87; 95% confidence interval, 0.68-1.12) did not differ by treatment group. Increased duration (≥2 vs <2 weeks) of breastfeeding was associated with slightly lower blood pressure measurements at the postpartum visit, but these differences were not significant in adjusted models. CONCLUSION: In a secondary analysis of the cohort of Chronic Hypertension and Pregnancy trial participants who attended the postpartum study visit and provided breastfeeding information (60% of original trial participants), breastfeeding outcomes did not differ significantly by treatment group. This suggests that maintaining goal blood pressure <140/90 mm Hg throughout the perinatal period is associated with neither harm nor benefit for short-term breastfeeding goals. Further study is needed to understand long-term breastfeeding outcomes among individuals with chronic hypertension and how to support this population in achieving their breastfeeding goals.

Constructing a Learning Curve to Discuss the Medical Treatments and the Effect of Vaccination of COVID-19.

Acknowledging the extreme risk COVID-19 poses to humans, this paper attempted to analyze and compare case fatality rates, identify the existence of learning curves for COVID-19 medical treatments, and examine the impact of vaccination on fatality rate reduction. Confirmed cases and deaths were extracted from the "Daily Situation Report" provided by the World Health Organization. The results showed that low registration and low viral test rates resulted in low fatality rates, and the learning curve was significant for all countries except China. Treatment for COVID-19 can be improved through repeated experience. Vaccinations in the U.K. and U.S.A. are highly effective in reducing fatality rates, but not in other countries. The positive impact of vaccines may be attributed to higher vaccination rates. In addition to China, this study identified the existence of learning curves for the medical treatment of COVID-19 that can explain the effect of vaccination rates on fatalities.

Mechanistic insights into the development of severe fetal growth restriction.

Fetal growth restriction (FGR), which most commonly results from suboptimal placental function, substantially increases risks for adverse perinatal and long-term outcomes. The only "treatment" that exists is delivery, which averts stillbirth but does not improve outcomes in survivors. Furthermore, the potential long-term consequences of FGR to the fetus, including cardiometabolic disorders, predispose these individuals to developing FGR in their future pregnancies. This creates a multi-generational cascade of adverse effects stemming from a single dysfunctional placenta, and understanding the mechanisms underlying placental-mediated FGR is critically important if we are to improve outcomes and overall health. The mechanisms behind FGR remain unknown. However, placental insufficiency derived from maldevelopment of the placental vascular systems is the most common etiology. To highlight important mechanistic interactions within the placenta, we focus on placental vascular development in the setting of FGR. We delve into fetoplacental angiogenesis, a robust and ongoing process in normal pregnancies that is impaired in severe FGR. We review cellular models of FGR, with special attention to fetoplacental angiogenesis, and we highlight novel integrin-extracellular matrix interactions that regulate placental angiogenesis in severe FGR. In total, this review focuses on key developmental processes, with specific focus on the human placenta, an underexplored area of research.

XGBoost-Based Simple Three-Item Model Accurately Predicts Outcomes of Acute Ischemic Stroke.

An all-inclusive and accurate prediction of outcomes for patients with acute ischemic stroke (AIS) is crucial for clinical decision-making. This study developed extreme gradient boosting (XGBoost)-based models using three simple factors-age, fasting glucose, and National Institutes of Health Stroke Scale (NIHSS) scores-to predict the three-month functional outcomes after AIS. We retrieved the medical records of 1848 patients diagnosed with AIS and managed at a single medical center between 2016 and 2020. We developed and validated the predictions and ranked the importance of each variable. The XGBoost model achieved notable performance, with an area under the curve of 0.8595. As predicted by the model, the patients with initial NIHSS score > 5, aged over 64 years, and fasting blood glucose > 86 mg/dL were associated with unfavorable prognoses. For patients receiving endovascular therapy, fasting glucose was the most important predictor. The NIHSS score at admission was the most significant predictor for those who received other treatments. Our proposed XGBoost model showed a reliable predictive power of AIS outcomes using readily available and simple predictors and also demonstrated the validity of the model for application in patients receiving different AIS treatments, providing clinical evidence for future optimization of AIS treatment strategies.

Human-guided deep learning with ante-hoc explainability by convolutional network from non-image data for pregnancy prognostication.

BACKGROUND AND OBJECTIVE: Deep learning is applied in medicine mostly due to its state-of-the-art performance for diagnostic imaging. Supervisory authorities also require the model to be explainable, but most explain the model after development (post hoc) instead of incorporating explanation into the design (ante hoc). This study aimed to demonstrate a human-guided deep learning with ante-hoc explainability by convolutional network from non-image data to develop, validate, and deploy a prognostic prediction model for PROM and an estimator of time of delivery using a nationwide health insurance database. METHODS: To guide modeling, we constructed and verified association diagrams respectively from literatures and electronic health records. Non-image data were transformed into meaningful images utilizing predictor-to-predictor similarities, harnessing the power of convolutional neural network mostly used for diagnostic imaging. The network architecture was also inferred from the similarities. RESULTS: This resulted the best model for prelabor rupture of membranes (n=883, 376) with the area under curves 0.73 (95% CI 0.72 to 0.75) and 0.70 (95% CI 0.69 to 0.71) respectively by internal and external validations, and outperformed previous models found by systematic review. It was explainable by knowledge-based diagrams and model representation. CONCLUSIONS: This allows prognostication with actionable insights for preventive medicine.

Questionnaire-free machine-learning method to predict depressive symptoms among community-dwelling older adults.

The 15-item Geriatric Depression Scale (GDS-15) is widely used to screen for depressive symptoms among older populations. This study aimed to develop and validate a questionnaire-free, machine-learning model as an alternative triage test for the GDS-15 among community-dwelling older adults. The best models were the random forest (RF) and deep-insight visible neural network by internal validation, but both performances were undifferentiated by external validation. The AUROC of the RF model was 0.619 (95% CI 0.610 to 0.627) for the external validation set with a non-local ethnic group. Our triage test can allow healthcare professionals to preliminarily screen for depressive symptoms in older adults without using a questionnaire. If the model shows positive results, then the GDS-15 can be used for follow-up measures. This preliminary screening will save a lot of time and energy for healthcare providers and older adults, especially those persons who are illiterate.

Effects of the Government Response and Community Mobility on the COVID-19 Pandemic in Southeast Asia.

Preventive policies and mobility restrictions are believed to work for inhibiting the growth rate of COVID-19 cases; however, their effects have rarely been assessed and quantified in Southeast Asia. We aimed to examine the effects of the government responses and community mobility on the COVID-19 pandemic in Southeast Asian countries. The study extracted data from Coronavirus Government Response Tracker, COVID-19 Community Mobility Report, and Our World in Data between 1 March and 31 December 2020. The government responses were measured by containment, health, and economic support index. The community mobility took data on movement trends at six locations. Partial least square structural equation modeling was used for bi-monthly analyses in each country. Results show that the community mobility generally followed government responses, especially the containment index. The path coefficients of government responses to community mobility ranged from -0.785 to -0.976 in March to April and -0.670 to -0.932 in May to June. The path coefficients of community mobility to the COVID-19 cases ranged from -0.058 to -0.937 in March to April and from -0.059 to -0.640 in September to October. It suggests that the first few months since the mobility restriction implemented is the optimal time to control the pandemic.