Associations Between Extreme Temperatures and Cardiovascular Cause-Specific Mortality: Results From 27 Countries.

BACKGROUND: Cardiovascular disease is the leading cause of death worldwide. Existing studies on the association between temperatures and cardiovascular deaths have been limited in geographic zones and have generally considered associations with total cardiovascular deaths rather than cause-specific cardiovascular deaths. METHODS: We used unified data collection protocols within the Multi-Country Multi-City Collaborative Network to assemble a database of daily counts of specific cardiovascular causes of death from 567 cities in 27 countries across 5 continents in overlapping periods ranging from 1979 to 2019. City-specific daily ambient temperatures were obtained from weather stations and climate reanalysis models. To investigate cardiovascular mortality associations with extreme hot and cold temperatures, we fit case-crossover models in each city and then used a mixed-effects meta-analytic framework to pool individual city estimates. Extreme temperature percentiles were compared with the minimum mortality temperature in each location. Excess deaths were calculated for a range of extreme temperature days. RESULTS: The analyses included deaths from any cardiovascular cause (32 154 935), ischemic heart disease (11 745 880), stroke (9 351 312), heart failure (3 673 723), and arrhythmia (670 859). At extreme temperature percentiles, heat (99th percentile) and cold (1st percentile) were associated with higher risk of dying from any cardiovascular cause, ischemic heart disease, stroke, and heart failure as compared to the minimum mortality temperature, which is the temperature associated with least mortality. Across a range of extreme temperatures, hot days (above 97.5th percentile) and cold days (below 2.5th percentile) accounted for 2.2 (95% empirical CI [eCI], 2.1-2.3) and 9.1 (95% eCI, 8.9-9.2) excess deaths for every 1000 cardiovascular deaths, respectively. Heart failure was associated with the highest excess deaths proportion from extreme hot and cold days with 2.6 (95% eCI, 2.4-2.8) and 12.8 (95% eCI, 12.2-13.1) for every 1000 heart failure deaths, respectively. CONCLUSIONS: Across a large, multinational sample, exposure to extreme hot and cold temperatures was associated with a greater risk of mortality from multiple common cardiovascular conditions. The intersections between extreme temperatures and cardiovascular health need to be thoroughly characterized in the present day-and especially under a changing climate.

Wearing masks as a protective measure for children against traffic-related air pollution: A comparison of perceptions between school children and their caregivers in Ho Chi Minh City, Vietnam.

BACKGROUND: Traffic-related air pollution (TRAP) problems are unlikely to be solved in the short term, making it imperative to educate children on protective measures to mitigate the negative impact on their health. Children and their caregivers may hold differing views on wearing a face mask as a safeguard against air pollution. While many studies have focused on predicting children's health-protective behaviours against air pollution, few have explored the differences in perceptions between children and their caregivers. OBJECTIVES: To examine this, we conducted a study that compared the health beliefs of two generations and evaluated the factors that influence the use of masks by children to reduce air pollution exposure. METHODS: The study was conducted in 24 secondary schools and involved 8420 children aged 13-14 and their caregivers. We used a Health Belief Model (HBM)-based instrument containing 17-item self-administered health beliefs questionnaires to gather data. The results were analysed using hierarchical logistic regression to determine the probability of children frequently wearing masks to protect against TRAP. RESULTS: Our study showed both children and caregivers recognised that several factors could influence mask-wearing among children: discomfort or difficulty breathing while wearing a mask and forgetting to bring a mask when going outside; perceived threats of the poor quality of air and children's respiratory health problems; and cues to mask use (i.e., seeing most of their friends wearing facemasks and ease of finding masks in local stores). However, only children were significantly concerned with public perception of their appearance while wearing a mask. Females were more likely to wear masks, and caregivers with higher levels of education were more likely to encourage their children to wear masks. Children who commuted to schools by walking, biking, or motorbiking were also more accepting of mask-wearing than those who travelled by car or bus. CONCLUSIONS: Children and their caregivers hold different perceptions of wearing masks to protect against air pollution. Children are more susceptible to social judgements regarding their appearance when wearing a mask.

Association of single nucleotide polymorphisms in the IRF6 gene with nonsyndromic cleft lip with or without cleft palate in Kinh Vietnamese patients.

BACKGROUND: The interferon regulatory factor 6 (IRF6) gene, which causes Van der Woude syndrome, is associated with nonsyndromic cleft lip with or without cleft palate (NSCL/P). Single nucleotide polymorphisms (SNPs) in the IRF6 gene were identified as susceptibility indicators of this defect in several populations. To further evaluate its role in this birth defect, we conducted this study with the aim of identifying allele frequencies, genotype frequencies, and associations of 5 SNPs (rs2235373, rs2235371, rs2235375, rs2013162, and rs2236907) in the IRF6 gene with NSCL/P in Kinh Vietnamese patients. METHODS: A total of 132 patients with NSCL/P and 132 healthy individuals were included in our study group. Direct sequencing was performed to genotype the tag SNPs. Genetic models were used to compare genotype and allele frequencies between the case and control groups. RESULTS: In the recessive model, the genotypes C/C of rs2236907, C/C of rs2013162, G/G of rs2235375, and A/A of rs2235373 were associated with an increased risk of NSCL/P, whereas there was no clear association between rs2235371 and the malformation in any genetic model. When subgroup analysis was performed, we observed a similar risk trend in the cleft lip and palate, cleft palate only and cleft lip only phenotypes. In haplotype analysis, haplotype models of 5 tag SNPs were associated with increased risks of this defect in all phenotypic models (ORGCGCC/CCAA = 23.64, 95% CI 12.28-45.49, p < 0.0001). CONCLUSIONS: These findings point to a considerable contribution of rs2236907, rs2013162, rs2235373, and rs2235375 to the NSCL/P defect in Kinh Vietnamese individuals.

Burden of asthma-like symptoms and a lack of recognition of asthma in Vietnamese children.

OBJECTIVE: Lack of recognition of asthma in childhood results in unmet asthma treatment needs and leads to the risk of sub-optimal respiratory health. The present study assessed the prevalence of asthmatic under-recognition in middle school children in Vietnam. METHODS: We conducted a school-based survey among 15,112 Vietnamese children. Most of them are aged from 13 to 14. Schools and students were recruited using multi-stage sampling. Respiratory symptoms were collected via self-report using a standardized tool from the International Study of Asthma and Allergies in Childhood. Under-recognition of asthma was defined as a presence of at least one asthma-like symptom but a negative response to having ever asthma. Associations were investigated using logistic regression. RESULTS: Prevalence of asthma-like symptoms was 27.3% and prevalence of physician-diagnosed asthma was 8.5%. Over 80% of symptomatic children were not diagnosed with asthma. Under-recognition of asthma was found more in girls (adjusted odds ratio; aOR = 1.75; 95%CI: 1.54 to 1.98). CONCLUSIONS: Asthma is significantly under-recognized in Vietnamese middle-school children. Urgent action is required to improve the recognition of asthma in Vietnam.

Fine particulate matter and daily hospitalizations for mental and behavioral disorders: A time-series study in Ho Chi Minh City, Vietnam.

Various adverse health outcomes caused by particulate matter (PM) exposure has been documented, while the evidence for the adverse effects of PM exposure on mental and behavioral disorders (MBDs) is limited. To date, few epidemiological studies, especially in developing countries, have focused on these adverse effects. In the past decade, air pollution sources in Vietnam have noticeably increased, resulting to the elevated concentrations of ambient air pollutants particularly fine PM or PM with an aerodynamic diameter ≤2.5 µm (PM2.5). Hence, investigating the short-term association between PM2.5 and MBDs is worthwhile. In this study, a quasi-Poisson time-series regression analysis was used to investigate the association between PM2.5 exposure and daily hospitalizations for MBDs to the Ho Chi Minh City Mental Health Hospital during 2017-2020. A natural cubic spline smooth function for time was used to screen out long-term and seasonality trends. Stratified analyses were also performed by sex, age, and season. During study period, 9,986 hospitalizations for MBDs were recorded and included in the analysis. Results suggested that a 10 µg/m3 daily increase in PM2.5 concentration was associated with a statistically significant 2.96% (95% confidence interval: 0.23%-5.76%) increase in hospitalizations for MBDs. The effects of PM2.5 exposure on hospital admissions were more pronounced in female patients and the middle-age group (35-59 years). This finding could increase awareness regarding prevention and minimization of MBDs on the public.

Hospital-based prostate cancer screening in vietnamese men with lower urinary tract symptoms: a classification and regression tree model.

BACKGROUND: Prostate cancer (PCa) is a common disease in men over 65 years of age, and should be detected early, while reducing unnecessary biopsies. This study aims to construct a classification and regression tree (CART) model (i.e., risk stratification algorithm) using multivariable approach to select Vietnamese men with lower urinary tract symptoms (LUTS) for PCa biopsy. METHODS: We conducted a case-control study on 260 men aged ≥ 50 years who visited MEDIC Medical Center, Vietnam in 2017-2018 with self-reported LUTS. The case group included patients with a positive biopsy and the control group included patients with a negative biopsy diagnosis of PCa. Bayesian Model Averaging (BMA) was used for selecting the most parsimonious prediction model. Then the CART with 5-fold cross-validation was constructed for selecting men who can benefit from PCa biopsy in steps by steps and intuitive way. RESULTS: BMA suggested five potential prediction models, in which the most parsimonious model including PSA, I-PSS, and age. CART advised the following cut-off points in the marked screening sequence: 18 < PSA < 33.5 ng/mL, I-PSS ≥ 19, and age ≥ 71. Patients with PSA ≥ 33.5 ng/mL have a PCa risk was 91.2%; patients with PSA < 18 ng/mL and I-PSS < 19 have a PCa risk was 7.1%. Patient with 18 ≤ PSA < 33.5ng/mL and I-PSS < 19 have a PCa risk is 70% if age ≥ 71; and is 16% if age < 71. In overall, CART reached high predictive value with AUC = 0.915. Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of CART at the 20% diagnosis probability threshold were 91.5%, 86.2%, 86.9%, 91.2%, and 88.9% respectively; at 80% diagnosis probability threshold were 79.2%, 92.3%, 91.2%, 81.6%, and 85.8% respectively. CONCLUSION: CART combining PSA, I-PSS, and age has practical use in hospital-based PCa screening in Vietnamese men with lower urinary tract symptoms.

Impact of temperature on hospital admission for acute lower respiratory infection (ALRI) among pre-school children in Ho Chi Minh City, Vietnam.

Changes in ambient temperature have been reported as an important risk factor for respiratory diseases among pre-school children. However, there have been few studies so far on the effects of temperature on children respiratory health in developing countries including Vietnam. This study examined the impact of short-term changes in ambient temperature on hospital admissions for acute lower respiratory infection (ALRI) among children aged less than 5 years old in Ho Chi Minh City (HCMC), Vietnam. Data on daily hospital admissions from 2013 to 2017 were collected from two large paediatric hospitals of the city. Daily meteorological data of the same period were also collected. Time series analysis was performed to evaluate the association between risk of hospitalisations and temperatures categorised by seasons, age, and causes. We found that a 1 °C increase in maximum temperature was associated with 4.2 and 3.4% increase in hospital admission for ALRI among children 3-5 years old during the dry season and the rainy season, respectively. Surprisingly, in the rainy season, a rise of 1°C diurnal temperature range (DTR) was significantly associated with a decrease from 2.0 to 2.5% risk of hospitalisation for ALRI among children <3 years old. These findings suggested that although high temperature is a risk factor for hospital admissions among children in general, other modifiable factors such as age, exposure time, air conditioning usage, wearing protective clothing, socioeconomic status, and behaviour may influence the overall effect of high temperature on hospital admissions of children <5 years old in HCMC. The findings of this study have provided evidence for building public health policies aimed at preventing and minimizing the adverse health effects of temperature on children in HCMC.

Quantifying excess deaths related to heatwaves under climate change scenarios: A multicountry time series modelling study.

BACKGROUND: Heatwaves are a critical public health problem. There will be an increase in the frequency and severity of heatwaves under changing climate. However, evidence about the impacts of climate change on heatwave-related mortality at a global scale is limited. METHODS AND FINDINGS: We collected historical daily time series of mean temperature and mortality for all causes or nonexternal causes, in periods ranging from January 1, 1984, to December 31, 2015, in 412 communities within 20 countries/regions. We estimated heatwave-mortality associations through a two-stage time series design. Current and future daily mean temperature series were projected under four scenarios of greenhouse gas emissions from 1971-2099, with five general circulation models. We projected excess mortality in relation to heatwaves in the future under each scenario of greenhouse gas emissions, with two assumptions for adaptation (no adaptation and hypothetical adaptation) and three scenarios of population change (high variant, median variant, and low variant). Results show that, if there is no adaptation, heatwave-related excess mortality is expected to increase the most in tropical and subtropical countries/regions (close to the equator), while European countries and the United States will have smaller percent increases in heatwave-related excess mortality. The higher the population variant and the greenhouse gas emissions, the higher the increase of heatwave-related excess mortality in the future. The changes in 2031-2080 compared with 1971-2020 range from approximately 2,000% in Colombia to 150% in Moldova under the highest emission scenario and high-variant population scenario, without any adaptation. If we considered hypothetical adaptation to future climate, under high-variant population scenario and all scenarios of greenhouse gas emissions, the heatwave-related excess mortality is expected to still increase across all the countries/regions except Moldova and Japan. However, the increase would be much smaller than the no adaptation scenario. The simple assumptions with respect to adaptation as follows: no adaptation and hypothetical adaptation results in some uncertainties of projections. CONCLUSIONS: This study provides a comprehensive characterisation of future heatwave-related excess mortality across various regions and under alternative scenarios of greenhouse gas emissions, different assumptions of adaptation, and different scenarios of population change. The projections can help decision makers in planning adaptation and mitigation strategies for climate change.

Prediction Model for Antimalarial Activities of Hemozoin Inhibitors by Using Physicochemical Properties.

The rapid spread of strains of malaria parasites that are resistant to several drugs has threatened global malaria control. Hence, the aim of this study was to predict the antimalarial activity of chemical compounds that possess anti-hemozoin-formation activity as a new means of antimalarial drug discovery. After the initial in vitro anti-hemozoin-formation high-throughput screening (HTS) of 9,600 compounds, a total of 224 hit compounds were identified as hemozoin inhibitors. These 224 compounds were tested for in vitro erythrocytic antimalarial activity at 10 µM by using chloroquine-mefloquine-sensitive Plasmodium falciparum strain 3D7A. Two independent experiments were conducted. The physicochemical properties of the active compounds were extracted from the ChemSpider and SciFinder databases. We analyzed the extracted data by using Bayesian model averaging (BMA). Our findings revealed that lower numbers of S atoms; lower distribution coefficient (log D) values at pH 3, 4, and 5; and higher predicted distribution coefficient (ACD log D) values at pH 7.4 had significant associations with antimalarial activity among compounds that possess anti-hemozoin-formation activity. The BMA model revealed an accuracy of 91.23%. We report new prediction models containing physicochemical properties that shed light on effective chemical groups for synthetic antimalarial compounds and help with in silico screening for novel antimalarial drugs.

Green Space and Deaths Attributable to the Urban Heat Island Effect in Ho Chi Minh City.

OBJECTIVES: To quantify heat-related deaths in Ho Chi Minh City, Vietnam, caused by the urban heat island (UHI) and explore factors that may alleviate the impact of UHIs. METHODS: We estimated district-specific meteorological conditions from 2010 to 2013 using the dynamic downscaling model and calculated the attributable fraction and number of mortalities resulting from the total, extreme, and mild heat in each district. The difference in attributable fraction of total heat between the central and outer districts was classified as the attributable fraction resulting from the UHI. The association among attributable fraction, attributable number with a green space, population density, and budget revenue of each district was then explored. RESULTS: The temperature-mortality relationship between the central and outer areas was almost identical. The attributable fraction resulting from the UHI was 0.42%, which was contributed by the difference in temperature distribution between the 2 areas. Every 1-square-kilometer increase in green space per 1000 people can prevent 7.4 deaths caused by heat. CONCLUSIONS: Green space can alleviate the impacts of UHIs, although future studies conducting a heath economic evaluation of tree planting are warranted.

Association between dengue severity and plasma levels of dengue-specific IgE and chymase.

There is no definitive predictor of dengue severity, and this has led to a very large number of unnecessary hospitalizations worldwide. Although mast cell mediators are believed to a play role in dengue severity, the lack of precise kinetic data demands further research on early predictors. We enrolled 111 patients with confirmed dengue and 85 with "other febrile illness" (OFI) in a hospital-based prospective study in Vietnam. Dengue patients were classified as level 1, 2, or 3 based on the clinical intervention received. Blood samples were collected from each patient every day (pre- and post-defervescence) and after discharge. Plasma chymase, total IgE, and dengue-specific IgE were measured. Dengue-specific IgE levels showed an increasing trend during the course of illness and remained high even at post-discharge, although no significant difference was observed among severity levels. Total IgE showed no such trend. The specific IgE/total IgE ratio (S/T ratio) remained constantly higher in level 3 patients compared to other levels, with a significant difference at some time points. The S/T ratio of acute phase samples (before defervescence) tended to increase with increasing severity (level 1 < 2 < 3), and was significantly higher in level 3 patients than in level 1 and OFI patients. As an early predictor of severity allowing level 3 patients to be distinguished from other dengue patients, the S/T ratio achieved a sensitivity of 75% and specificity of 68%. We describe the kinetic profiles of IgEs, their ratio, and chymase levels at different severity levels. The S/T ratio was found to be associated with dengue severity, suggesting that it could potentially be used as an early predictor of severity.

High-Throughput Screening and Prediction Model Building for Novel Hemozoin Inhibitors Using Physicochemical Properties.

It is essential to continue the search for novel antimalarial drugs due to the current spread of resistance against artemisinin by Plasmodium falciparum parasites. In this study, we developed in silico models to predict hemozoin inhibitors as a potential first-step screening for novel antimalarials. An in vitro colorimetric high-throughput screening assay of hemozoin formation was used to identify hemozoin inhibitors from 9,600 structurally diverse compounds. The physicochemical properties of positive hits and randomly selected compounds were extracted from the ChemSpider database; they were used for developing prediction models to predict hemozoin inhibitors using two different approaches, i.e., traditional multivariate logistic regression and Bayesian model averaging. Our results showed that a total of 224 positive-hit compounds exhibited the ability to inhibit hemozoin formation, with 50% inhibitory concentrations (IC50s) ranging from 3.1 µM to 199.5 µM. The best model according to traditional multivariate logistic regression included the three variables octanol-water partition coefficient, number of hydrogen bond donors, and number of atoms of hydrogen, while the best model according to Bayesian model averaging included the three variables octanol-water partition coefficient, number of hydrogen bond donors, and index of refraction. Both models had a good discriminatory power, with area under the curve values of 0.736 and 0.781 for the traditional multivariate model and Bayesian model averaging, respectively. In conclusion, the prediction models can be a new, useful, and cost-effective approach for the first screen of hemozoin inhibition-based antimalarial drug discovery.

Association of BAK1 single nucleotide polymorphism with a risk for dengue hemorrhagic fever.

BACKGROUND: Dengue hemorrhagic fever (DHF) is a severe life-threatening form of dengue infection. Low platelet count is one of the characteristic clinical manifestations in patients with severe dengue. However, little is known about genetic factors in the host that cause low platelet count in patients with dengue. METHODS: A previous genome-wide association study of hematological and biochemical traits identified single nucleotide polymorphisms (SNPs) associated with low platelet count in healthy subjects. To examine the possible association of these SNPs with DHF, 918 Thai patients with dengue [509 patients with DHF and 409 with dengue fever (DF)] were genotyped for five SNPs: rs5745568 in BAK1, rs6141 in THPO, rs6065 in GP1BA, rs739496 in SH2B3, and rs385893 in RCL1. In addition, rs4804803 in CD209, that has been reported to be associated with dengue infection, was also genotyped to examine if rs4804803 affects the association detected in this study. RESULTS: The allele frequencies of each SNP were compared between the DHF and DF groups. Among the five SNPs, the G allele of rs5745568 in BAK1 was significantly associated with a risk for DHF [P = 0.006 and crude odd ratio (95 % confidence interval) = 1.32 (1.09-1.60)]. The association of this allele with DHF was also significant in a logistic regression analysis adjusted for age, sex, hospital (i.e., geographic region), immune status (i.e., primary or secondary infection), and virus serotype [P = 0.016 and adjusted odd ratio (95 % confidence interval) = 1.29 (1.05-1.58)]. The result was not influenced by rs4804803 [P = 0.0167 and adjusted OR (95 % CI) = 1.29 (1.05-1.58)]. No other SNPs including rs4804803 showed significant association. CONCLUSIONS: The low-level constitutive production of platelets caused by the G allele of rs5745568 seems to increase the risk of bleeding in dengue infection. Our results suggest that BCL-2 homologous antagonist/killer (BAK) protein, encoded by BAK1, plays a crucial role in the pathogenesis of DHF.

A replication study confirms the association of GWAS-identified SNPs at MICB and PLCE1 in Thai patients with dengue shock syndrome.

BACKGROUND: Dengue shock syndrome (DSS), a severe life-threatening form of dengue infection, mostly occurs in children. A recent genome wide association study (GWAS) identified two SNPs, rs3132468 of major histocompatibility complex class I polypeptide-related sequence B (MICB) and rs3765524 of phospholipase C, epsilon 1 (PLCE1), associated with DSS in Vietnamese children. In this study, to examine whether an identical association is found in a different population, the association of these two SNPs with DSS was assessed in Thai children with dengue. METHODS: The rs3132468 and rs3765524 SNPs were genotyped in 917 Thai children with dengue: 76 patients with DSS and 841 patients with non-DSS. The allele frequencies were compared between DSS and non-DSS groups by one-sided Fisher's exact test. The association of rs3132468 and rs3765524 with the mRNA expression levels of MICB and PLCE1 were assessed in EBV-transformed lymphoblastoid cell lines. RESULTS: The reported DSS-risk alleles were significantly associated with DSS in Thai patients with dengue (one-sided P = 0.0213 and odds ratio [OR] = 1.58 for rs3132468-C and one-sided P = 0.0252 and OR = 1.49 for rs3765524-C). The rs3132468-C allele showed a significant association with lower mRNA level of MICB (P = 0.0267), whereas the rs3765524-C allele did not. These results imply that the MICB molecule may play an important role in the prevention of DSS in dengue infection. CONCLUSIONS: Together with previous association studies, we conclude that rs3132468-C at MICB and rs3765524-C at PLCE1 confer risk of DSS in Southeast Asians.

Leveraging Climate Data for Dengue Forecasting in Ba Ria Vung Tau Province, Vietnam: An Advanced Machine Learning Approach.

Dengue fever is a persistent public health issue in tropical regions, including Vietnam, where climate variability plays a crucial role in disease transmission dynamics. This study focuses on developing climate-based machine learning models to forecast dengue outbreaks in Ba Ria Vung Tau (BRVT) province, Vietnam, using meteorological data from 2003 to 2022. We utilized four predictive models-Negative Binomial Regression (NBR), Seasonal AutoRegressive Integrated Moving Average with Exogenous Regressors (SARIMAX), Extreme Gradient Boosting (XGBoost) v2.0.3, and long short-term memory (LSTM)-to predict weekly dengue incidence. Key climate variables, including temperature, humidity, precipitation, and wind speed, were integrated into these models, with lagged variables included to capture delayed climatic effects on dengue transmission. The NBR model demonstrated the best performance in terms of predictive accuracy, achieving the lowest Mean Absolute Error (MAE), compared to other models. The inclusion of lagged climate variables significantly enhanced the model's ability to predict dengue cases. Although effective in capturing seasonal trends, SARIMAX and LSTM models struggled with overfitting and failed to accurately predict short-term outbreaks. XGBoost exhibited moderate predictive power but was sensitive to overfitting, particularly without fine-tuning. Our findings confirm that climate-based machine learning models, particularly the NBR model, offer valuable tools for forecasting dengue outbreaks in BRVT. However, improving the models' ability to predict short-term peaks remains a challenge. The integration of meteorological data into early warning systems is crucial for public health authorities to plan timely and effective interventions. This research contributes to the growing body of literature on climate-based disease forecasting and underscores the need for further model refinement to address the complexities of dengue transmission in highly endemic regions.

Validation of the global limb anatomical staging system in Vietnamese patients treated for chronic limb-threatening ischemia.

BACKGROUND: Chronic limb-threatening ischemia (CLTI) is the most severe clinical form of peripheral artery disease (PAD), accounting for approximately 11%, and is strongly associated with the incidence of amputation, cardiovascular events, and mortality. The Global Vascular Guideline (GVG) proposed a new Global Anatomic Staging System (GLASS) for evaluating the anatomic complexity of arterial lesions. However, more research is required to evaluate outcomes after endovascular intervention in CLTI patients using the GLASS. OBJECTIVE: Our study aimed to describe clinical characteristics, arterial lesions, and endovascular interventions according to three grades of GLASS in the Vietnamese population. We evaluated the technical success, mortality rate, and probability to preserve the limb according to the GLASS. METHODS: All patients were diagnosed with CLTI and underwent infrainguinal endovascular intervention at the Department of Thoracic and Vascular Surgery, University Medical Center, Ho Chi Minh City from June 2020 to June 2022. All patients were evaluated before intervention and follow-up at 6 and 12 months after intervention. Patients were divided into three groups according to the GLASS, thereby comparing the technical success, mortality, and amputation rates. This retrospective study describes a series of cases. RESULTS: The study sample evaluated 82 lower limbs of 82 patients, in which GLASS class I, II, and III lesions accounted for 36.6%, 43.9%, and 19.5% of the patients, respectively. The rates of technical success in the groups gradually decreased according to the complexity of the lesions (90%, 86.11%, and 56.25% for GLASS I, II, and III, respectively; p = 0.012). Notably, limb-based patency (LBP) at 12 months was significantly lower in the GLASS III group than in the GLASS I and II groups (22.22% vs 88.89% and 67.74%, respectively; p = 0.001). The amputation rates at 12 months in GLASS groups I, II, and III were 13.3%, 22.2%, and 50%, respectively (p = 0.021), while the mortality rates at 12 months were 0%, 8.33%, and 25%, respectively (p = 0.015). CONCLUSION: In patients with CLTI of higher GLASS stages, the rates of technical success were lower and the amputation and mortality rates were higher.

Indoor air pollution is associated with respiratory symptoms in children in urban Vietnam.

Exposure to indoor air pollution (IAP) is a leading environmental risk for respiratory diseases. We investigated the relationship between respiratory symptoms and polluting indoor activities such as smoking, cooking and contact with pets among children in Ho Chi Minh City (HCMC), Vietnam. A cross-sectional survey applied a multistage sampling method in 24 randomly selected secondary schools across the city. Approximately 15,000 students completed self-administrated questionnaires on risk factors and respiratory health outcomes within the preceding 12 months. Data were analyzed using a multivariable logistic regression model with robust standard errors. Wheeze was the most common respiratory symptom (39.5 %) reported, followed by sneezing and runny nose (28.3 %). A small percentage of students self-reported asthma (8.6 %). Approximately 56 % of participants lived with family members who smoked. A positive association between exposure to indoor secondhand smoke and respiratory symptoms was observed, with adjusted odds ratios (aOR) of 1.41 (95 % CI: 1.25-1.60, p < 0.001) for wheezing and 1.64 (95 % CI: 1.43-1.87, p < 0.001) for sneezing and runny nose, respectively. Using an open stove fuelled by coal, wood, or kerosene for cooking was associated with wheeze (aOR: 1.36, CI 95 %: 1.10-1.68, p = 0.01) and sneezing and runny nose (aOR: 1.36, CI 95 %: 1.09-1.69, p = 0.01). In the present study, IAP was associated with adverse health outcomes, as evidenced by an increase in respiratory symptoms reported within the previous 12 months.

Organophosphate Pesticide Exposure: Effect on Farmers' Sperm Quality in the Mekong Delta, Vietnam.

OBJECTIVES: Using pesticides in the An Giang province is widespread. However, studies on the health effect of organophosphate pesticide have not been updated within the past 12 years. This study aimed to assess exposure to organophosphate pesticides and their effects on sperm quality among farmers in the An Giang Province, Mekong Delta, Vietnam. METHODS: During the winter - spring crop season of December 2021 to February 2022, a cross-sectional study was conducted on farmers aged 18 to 60 years-old based on seven communes' health checkup programs. The pesticide spray group included farmers who had sprayed pesticides in the previous week and had a history of working in agriculture for more than 2 years. The control group was defined as those who lived in the same community, had not worked in agriculture, and had never sprayed pesticides. Demographic characteristics and blood, urine, and semen samples were collected and analyzed. RESULTS: Data for 184 eligible participants were analyzed, including 116 farmers in the pesticide spray group and 68 non-farmers in the control group. Pesticide spray contributed to a decrease in the sperm quality index of 6.253 units (95% CI, 4.472-8.749). Increasing each pseudocholinesterase (PChE) unit (kIU/L) was associated with an increase of 1.181 units in the sperm quality index (95% CI, 0.757-0.947). CONCLUSIONS: Preventive methods for organophosphate pesticide exposure, such as administrative controls, engineering controls, substitution, and personal protective equipment should be applied to control health risks. In the An Giang setting, personal protective equipment is feasible, but most types of equipment are not used. The immediate priority is to determine the cause of personal protective equipment not being used and to find solutions to encourage people to use them.

Temperature-mortality associations by age and cause: a multi-country multi-city study.

Background: Heterogeneity in temperature-mortality relationships across locations may partly result from differences in the demographic structure of populations and their cause-specific vulnerabilities. Here we conduct the largest epidemiological study to date on the association between ambient temperature and mortality by age and cause using data from 532 cities in 33 countries. Methods: We collected daily temperature and mortality data from each country. Mortality data was provided as daily death counts within age groups from all, cardiovascular, respiratory, or noncardiorespiratory causes. We first fit quasi-Poisson regression models to estimate location-specific associations for each age-by-cause group. For each cause, we then pooled location-specific results in a dose-response multivariate meta-regression model that enabled us to estimate overall temperature-mortality curves at any age. The age analysis was limited to adults. Results: We observed high temperature effects on mortality from both cardiovascular and respiratory causes compared to noncardiorespiratory causes, with the highest cold-related risks from cardiovascular causes and the highest heat-related risks from respiratory causes. Risks generally increased with age, a pattern most consistent for cold and for nonrespiratory causes. For every cause group, risks at both temperature extremes were strongest at the oldest age (age 85 years). Excess mortality fractions were highest for cold at the oldest ages. Conclusions: There is a differential pattern of risk associated with heat and cold by cause and age; cardiorespiratory causes show stronger effects than noncardiorespiratory causes, and older adults have higher risks than younger adults.

Development of an Artificial Intelligence-Based Breast Cancer Detection Model by Combining Mammograms and Medical Health Records.

BACKGROUND: Artificial intelligence (AI)-based computational models that analyze breast cancer have been developed for decades. The present study was implemented to investigate the accuracy and efficiency of combined mammography images and clinical records for breast cancer detection using machine learning and deep learning classifiers. METHODS: This study was verified using 731 images from 357 women who underwent at least one mammogram and had clinical records for at least six months before mammography. The model was trained on mammograms and clinical variables to discriminate benign and malignant lesions. Multiple pre-trained deep CNN models to detect cancer in mammograms, including X-ception, VGG16, ResNet-v2, ResNet50, and CNN3 were employed. Machine learning models were constructed using k-nearest neighbor (KNN), support vector machine (SVM), random forest (RF), Artificial Neural Network (ANN), and gradient boosting machine (GBM) in the clinical dataset. RESULTS: The detection performance obtained an accuracy of 84.5% with a specificity of 78.1% at a sensitivity of 89.7% and an AUC of 0.88. When trained on mammography image data alone, the result achieved a slightly lower score than the combined model (accuracy, 72.5% vs. 84.5%, respectively). CONCLUSIONS: A breast cancer-detection model combining machine learning and deep learning models was performed in this study with a satisfactory result, and this model has potential clinical applications.