Decoding children dental health risks: a machine learning approach to identifying key influencing factors.

Introduction and objectives: This study investigates key factors influencing dental caries risk in children aged 7 and under using machine learning techniques. By addressing dental caries' prevalence, it aims to enhance early identification and preventative strategies for high-risk individuals. Methods: Data from clinical examinations of 356 children were analyzed using Logistic Regression, Decision Trees, and Random Forests models. These models assessed the influence of dietary habits, fluoride exposure, and socio-economic status on caries risk, emphasizing accuracy, precision, recall, F1 score, and AUC metrics. Results: Poor oral hygiene, high sugary diet, and low fluoride exposure were identified as significant caries risk factors. The Random Forest model demonstrated superior performance, illustrating the potential of machine learning in complex health data analysis. Our SHAP analysis identified poor oral hygiene, high sugary diet, and low fluoride exposure as significant caries risk factors. Conclusion: Machine learning effectively identifies and quantifies dental caries risk factors in children. This approach supports targeted interventions and preventive measures, improving pediatric dental health outcomes. Clinical significance: By leveraging machine learning to pinpoint crucial caries risk factors, this research lays the groundwork for data-driven preventive strategies, potentially reducing caries prevalence and promoting better dental health in children.

Nomenclature of the symptoms of head and neck cancer: a systematic scoping review.

Introduction: Evolution of a patient-reported symptom-based risk stratification system to redesign the suspected head and neck cancer (HNC) referral pathway (EVEREST-HN) will use a broad and open approach to the nomenclature and symptomatology. It aims to capture and utilise the patient reported symptoms in a modern way to identify patients' clinical problems more effectively and risk stratify the patient. Method: The review followed the PRISMA checklist for scoping reviews. A search strategy was carried out using Medline, Embase and Web of Science between January 1st 2012 and October 31st 2023. All titles, abstracts and full paper were screened for eligibility, papers were assessed for inclusion using predetermined criteria. Data was extracted pertaining to the aims, type of study, cancer type, numbers of patients included and symptoms, presenting complaints or signs and symptoms. Results: There were 9,331 publications identified in the searches, following title screening 350 abstracts were reviewed for inclusion and 120 were considered for eligibility for the review. 48 publications met the eligibility criteria and were included in the final review. Data from almost 11,000 HNC patients was included. Twenty-one of the publications were from the UK, most were retrospective examination of patient records. Data was extracted and charted according to the anatomical area of the head and neck where the symptoms are subjectively and objectively found, and presented according to lay terms for symptoms, clinical terms for symptoms and the language of objective clinical findings. Discussion: Symptoms of HNC are common presenting complaints, interpreting these along with clinical history, examination and risk factors will inform a clinician's decision to refer as suspected cancer. UK Head and Neck specialists believe a different way of triaging the referrals is needed to assess the clinical risk of an undiagnosed HNC. EVEREST-HN aims to achieve this using the patient history of their symptoms. This review has highlighted issues in terms of what is considered a symptom, a presenting complaint and a clinical finding or sign.

Validation of the International Medical Prevention Registry on Venous Thromboembolism (IMPROVE) risk scores for venous thromboembolism and bleeding in an independent population.

Background: Multiple guidelines recommend assessment of bleeding and venous thromboembolism (VTE) risk in adult medical inpatients to inform prevention strategies. There is no agreed-upon method for VTE and bleeding risk assessment. Objectives: To validate the International Medical Prevention Registry on Venous Thromboembolism (IMPROVE) VTE and bleeding risk scores in an independent population. Methods: In this retrospective study, we calculated the IMPROVE VTE and bleeding risk scores in medical inpatients admitted between 2010 and 2019 at the University of Vermont Medical Center (UVMMC). Patients were followed for in-hospital bleeding events while hospitalized and VTE events while hospitalized and for 3 months after discharge. We assessed calibration of the risk models by comparing the observed incidence of events in the UVMMC and IMPROVE populations across the published risk categories. We also assessed performance of the IMPROVE risk factors after refitting the models in the UVMMC population. Discrimination was assessed using the area under the receiver operating characteristic curve (AUC). Results: VTE occurred in 270 (1.1%) of 23,873 admissions, with 92 (34%) occurring during admission, and bleeding occurred in 712 (4.7%) of 15,240 admissions. When the IMPROVE-VTE risk factors were refitted to the UVMMC data, the AUC was 0.64. When the IMPROVE bleeding risk factors were refitted to the UVMMC data, the AUC was 0.67. The IMPROVE-VTE score tended to overestimate risk at higher scores, and the IMPROVE bleeding score underestimated risk at lower scores and overestimated risk at higher scores. Conclusion: While the refitted IMPROVE VTE and bleeding risk scores had reasonable model fit, the scores were poorly calibrated and did not reliably identify or differentiate patients at risk for VTE and bleeding. Different methods are needed for risk assessment of medical inpatients for VTE and bleeding risk.

An integrated ergonomic risk assessment framework based on fuzzy logic and IVSF-AHP for optimising ergonomic risks in a mixed-model assembly line.

This study proposes a systematic approach to address ergonomic factors, including physical, environmental and psychosocial aspects, in solving assembly line balancing problems. A three-stage framework is developed, starting with determining weights for ergonomic risk assessment methods using the interval-valued spherical fuzzy analytical hierarchy process. In the second stage, a fuzzy logic model for integrated ergonomic risk assessment is constructed based on these weights, and the integrated ergonomic risk score is determined. In the third stage, a mathematical model is formulated to minimise the cycle time while balancing the ergonomic risk level. A case study conducted in a wire harness factory validated the effectiveness of the proposed approach, showing a 10-11% improvement in line efficiency and a 12-25% enhancement in ergonomic risk balancing performance. These findings underscore the potential benefits of implementing this approach, which can significantly improve occupational safety and overall performance.

This article presents a practical and systematic approach for enhancing ergonomic conditions in assembly lines. The proposed approach aims to balance the ergonomic risk level while minimising the cycle time by considering physical, environmental and psychosocial risk factors. A case study conducted in a wire harness factory demonstrated significant improvements in balancing ergonomic risks, highlighting the real-world applicability of this research.

Assessment of heavy metal contamination in leafy vegetables: implications for public health and regulatory measures.

Heavy metal contamination in leafy vegetables poses significant health risks, highlighting the urgent need for stringent monitoring and intervention measures to ensure food safety and mitigate potential adverse effects on public health. This study investigates the levels of heavy metals, including cadmium (Cd), chromium (Cr), nickel (Ni), lead (Pb), zinc (Zn), and copper (Cu), in locally grown and commercially available leafy vegetables, comparing them to the safety limits established by WHO/FAO. The results revealed that levels of Cd, Cr, Ni, and Pb in the vegetables exceeded WHO/FAO limits, while Zn and Cu remained within permissible bounds. Marketed vegetables exhibited higher metal concentrations than those from nearby farms. For Cu (0.114-0.289 mg/kg) and Zn (0.005-0.574 mg/kg), the daily intake of metals (DIM) was below the dietary intake (DI) and upper limit (UL). Cd's DIM (0.031-0.062 mg/kg) remained below the UL but exceeded the DI. Marketed kale and mint surpassed both DI and UL limits for Ni, while local produce only exceeded the DI. All vegetables had DIM below the DI, except for mint and kale. For Pb, every vegetable exceeded DI limits, with market samples contributing significantly. Cr's DIM ranged from 0.028 to 1.335 mg/kg, for which no set maximum daily intake exists. The health risk index (HRI) values for Zn, Cd, Cu, Ni, and Pb suggested potential health risks associated with leafy greens, while Cr's HRI was below 1. The study underscores the need for stringent monitoring and intervention measures to mitigate the health risks posed by heavy metal contamination in leafy vegetables. These findings suggest that consuming these leafy greens may put consumers at considerable risk for health problems related to Cd, Cu, Ni, Pb, and Zn exposure.

Evaluation of potential human health risks arising from nitrate and fluoride in the groundwater of Aurangabad, Bihar using GIS and chemometric analysis.

This study employed the groundwater pollution index to assess the appropriateness of groundwater for human consumption. Additionally, the hazard index was utilized to evaluate the potential non-carcinogenic risks associated with fluoride and nitrate exposure among children, women, and men in the study region. A total of 103 samples were collected from the Aurangabad district of Bihar. The analyzed samples were assessed using several physicochemical parameters. Major cations in the groundwater are Ca2+ > Mg2+ and major anions are HCO3- > Cl- > SO42- > NO3- > F- > PO43-. Around 17% of the collected groundwater samples surpassed the allowable BIS concentration limits for Nitrate, while approximately 11% surpassed the allowed limits for fluoride concentration. Principal component analysis was utilized for its efficacy and efficiency in the analytical procedure. Four principal components were recovered that explained 69.06% of the total variance. The Hazard Quotient (HQ) of nitrate varies between 0.03-1.74, 0.02-1.47, and 0.03-1.99 for females, males, and children, respectively. The HQ of fluoride varies between 0.04-1.59, 0.04-1.34, and 0.05-1.82 for females, males, and children, respectively. The central part of the district was at high risk according to the spatial distribution maps of the total hazard index (THI). Noncarcinogenic risks due to THI are 47%, 37%, and 28% for children, females, and males, respectively. According to the human health risk assessment, children are more prone to getting affected by polluted water than adults. The groundwater pollution index (GPI) value ranges from 0.46 to 2.27 in the study area. Seventy-five percent of the samples fell under minor pollution and only one fell under high pollution. The spatial distribution of GPI in the research area shows that the central region is highly affected, which means that this water is unsuitable for drinking purposes.

Distribution, risk evaluation, and source allocation of cesium and strontium in surface soil in a mining city.

Radioactive nuclides cesium (Cs) and strontium (Sr) possess long half-lives, with 135Cs at approximately 2.3 million years and 87Sr at about 49 billion years. Their persistent accumulation can result in long-lasting radioactive contamination of soil ecosystems. This study employed geo-accumulation index (Igeo), pollution load index (PLI), potential ecological risk index (PEPI), health risk assessment model (HRA), and Monte Carlo simulation to evaluate the pollution and health risks of Cs and Sr in the surface soil of different functional areas in a typical mining city in China. Positive matrix factorization (PMF) model was used to elucidate the potential sources of Cs and Sr and the respective contribution rates of natural and anthropogenic sources. The findings indicate that soils in the mining area exhibited significantly higher levels of Cs and Sr pollution compared to smelting factory area, agricultural area, and urban residential area. Strontium did not pose a potential ecological risk in any studied functional area. The non-carcinogenic health risk of Sr to the human body in the study area was relatively low. Because of the lack of parameters for Cs, the potential ecological and human health risks of Cs was not calculated. The primary source of Cs in the soil was identified as the parent material from which the soil developed, while Sr mainly originated from associated contamination caused by mining activities. This research provides data for the control of Cs and Sr pollution in the surface soil of mining city.

Lead Exposure Estimation Through a Physiologically Based Toxicokinetic Model Using Human Biomonitoring Data and Comparison with Scenario-Based Exposure Assessment: A Case Study in Korean Adults.

Pb toxicity is linked to cardiovascular and nephrotoxicity issues. Exposure to this heavy metal can occur through food and drinking water. Therefore, this study aimed to evaluate Pb exposure and assess health risks in Korean adults using a physiologically based toxicokinetic (PBTK) model. Human blood Pb concentrations were monitored using the Korean National Environmental Health Survey (KoNEHS) Cycle 4. The average Pb exposure in Korean adults was 0.520 µg/kg bw/day. The PBTK results were compared with scenario-based results from the 2021 risk assessment report of five heavy metals, including Pb, conducted by the MFDS. Exposure determined through reverse dosimetry was approximately two times higher than scenario-based exposure (0.264 µg/kg bw/day). The higher exposure levels obtained during PBTK analysis may be attributed to sustained exposure within historically more contaminated living environments and the long half-life of Pb. These findings suggest that the PBTK-based method can quantify aggregated exposure levels in the body over time, potentially serving as a complementary tool to address the constraints of scenario-based assessment methods for integrated risk assessment. Moreover, this model is convenient and cost-effective compared with scenario-based exposure estimation. These findings can facilitate the application of model for tracking continuous national changes in hazardous substance levels.

Prostate cancer risk assessment and avoidance of prostate biopsies using fully automatic deep learning in prostate MRI: comparison to PI-RADS and integration with clinical data in nomograms.

OBJECTIVES: Risk calculators (RCs) improve patient selection for prostate biopsy with clinical/demographic information, recently with prostate MRI using the prostate imaging reporting and data system (PI-RADS). Fully-automated deep learning (DL) analyzes MRI data independently, and has been shown to be on par with clinical radiologists, but has yet to be incorporated into RCs. The goal of this study is to re-assess the diagnostic quality of RCs, the impact of replacing PI-RADS with DL predictions, and potential performance gains by adding DL besides PI-RADS. MATERIAL AND METHODS: One thousand six hundred twenty-seven consecutive examinations from 2014 to 2021 were included in this retrospective single-center study, including 517 exams withheld for RC testing. Board-certified radiologists assessed PI-RADS during clinical routine, then systematic and MRI/Ultrasound-fusion biopsies provided histopathological ground truth for significant prostate cancer (sPC). nnUNet-based DL ensembles were trained on biparametric MRI predicting the presence of sPC lesions (UNet-probability) and a PI-RADS-analogous five-point scale (UNet-Likert). Previously published RCs were validated as is; with PI-RADS substituted by UNet-Likert (UNet-Likert-substituted RC); and with both UNet-probability and PI-RADS (UNet-probability-extended RC). Together with a newly fitted RC using clinical data, PI-RADS and UNet-probability, existing RCs were compared by receiver-operating characteristics, calibration, and decision-curve analysis. RESULTS: Diagnostic performance remained stable for UNet-Likert-substituted RCs. DL contained complementary diagnostic information to PI-RADS. The newly-fitted RC spared 49% [252/517] of biopsies while maintaining the negative predictive value (94%), compared to PI-RADS ≥ 4 cut-off which spared 37% [190/517] (p < 0.001). CONCLUSIONS: Incorporating DL as an independent diagnostic marker for RCs can improve patient stratification before biopsy, as there is complementary information in DL features and clinical PI-RADS assessment. CLINICAL RELEVANCE STATEMENT: For patients with positive prostate screening results, a comprehensive diagnostic workup, including prostate MRI, DL analysis, and individual classification using nomograms can identify patients with minimal prostate cancer risk, as they benefit less from the more invasive biopsy procedure. KEY POINTS: The current MRI-based nomograms result in many negative prostate biopsies. The addition of DL to nomograms with clinical data and PI-RADS improves patient stratification before biopsy. Fully automatic DL can be substituted for PI-RADS without sacrificing the quality of nomogram predictions. Prostate nomograms show cancer detection ability comparable to previous validation studies while being suitable for the addition of DL analysis.

Two Decades of Air Pollution Health Risk Assessment: Insights From the Use of WHO's AirQ and AirQ+ Tools.

Objectives: We evaluated studies that used the World Health Organization's (WHO) AirQ and AirQ+ tools for air pollution (AP) health risk assessment (HRA) and provided best practice suggestions for future assessments. Methods: We performed a comprehensive review of studies using WHO's AirQ and AirQ+ tools, searching several databases for relevant articles, reports, and theses from inception to Dec 31, 2022. Results: We identified 286 studies that met our criteria. The studies were conducted in 69 countries, with most (57%) in Iran, followed by Italy and India (∼8% each). We found that many studies inadequately report air pollution exposure data, its quality, and validity. The decisions concerning the analysed population size, health outcomes of interest, baseline incidence, concentration-response functions, relative risk values, and counterfactual values are often not justified, sufficiently. Many studies lack an uncertainty assessment. Conclusion: Our review found a number of common shortcomings in the published assessments. We suggest better practices and urge future studies to focus on the quality of input data, its reporting, and associated uncertainties.

Risk assessment of small organoarsenic species in food.

The European Commission asked EFSA for a risk assessment on small organoarsenic species in food. For monomethylarsonic acid MMA(V), decreased body weight resulting from diarrhoea in rats was identified as the critical endpoint and a BMDL10 of 18.2 mg MMA(V)/kg body weight (bw) per day (equivalent to 9.7 mg As/kg bw per day) was calculated as a reference point (RP). For dimethylarsinic acid DMA(V), increased incidence in urinary bladder tumours in rats was identified as the critical endpoint. A BMDL10 of 1.1 mg DMA(V)/kg bw per day (equivalent to 0.6 mg As/kg bw per day) was calculated as an RP. For other small organoarsenic species, the toxicological data are insufficient to identify critical effects and RPs, and they could not be included in the risk assessment. For both MMA(V) and DMA(V), the toxicological database is incomplete and a margin of exposure (MOE) approach was applied for risk characterisation. The highest chronic dietary exposure to DMA(V) was estimated in 'Toddlers', with rice and fish meat as the main contributors across population groups. For MMA(V), the highest chronic dietary exposures were estimated for high consumers of fish meat and processed/preserved fish in 'Infants' and 'Elderly' age class, respectively. For MMA(V), an MOE of ≥ 500 was identified not to raise a health concern. For MMA(V), all MOEs were well above 500 for average and high consumers and thus do not raise a health concern. For DMA(V), an MOE of 10,000 was identified as of low health concern as it is genotoxic and carcinogenic, although the mechanisms of genotoxicity and its role in carcinogenicity of DMA(V) are not fully elucidated. For DMA(V), MOEs were below 10,000 in many cases across dietary surveys and age groups, in particular for some 95th percentile exposures. The Panel considers that this would raise a health concern.

Shift in emergency department utilization by frequent attendees with sickle cell disease during the COVID-19 pandemic: A multicentre cohort study.

While the coronavirus disease-2019 (COVID-19) might have increased acute episodes in people living with sickle cell disease (SCD), it may also have changed their reliance on emergency department (ED) services. We assessed the impact of the COVID-19 pandemic and lockdowns on ED visits in adult SCD people followed in five French reference centres, with a special focus on 'high users' (≥10 visits in 2019). We analysed the rate of ED visits from 1 January 2015 to 31 December 2021, using a self-controlled case series. Among 1530 people (17 829 ED visits), we observed a significant reduction in ED visits during and after lockdowns, but the effect vanished over time. Compared to pre-pandemic, incidence rate ratios for ED visits were 0.59 [95% CI 0.52-0.67] for the first lockdown, 0.66 [95% CI 0.58-0.75] for the second and 0.85 [95% CI 0.73-0.99] for the third. High users (4% of people but 33.7% of visits) mainly drove the reductions after the first lockdown. COVID-19 lockdowns were associated with reduced ED visits. While most people returned to their baseline utilization by April 2021, high users had a lasting decrease in ED visits. Understanding the factors driving the drop in ED utilization among high users might inform clinical practice and health policy.

Treatment drop-in in a contemporary cohort used to derive cardiovascular risk prediction equations.

BACKGROUND: No routinely recommended cardiovascular disease (CVD) risk prediction equations have adjusted for CVD preventive medications initiated during follow-up (treatment drop-in) in their derivation cohorts. This will lead to underestimation of risk when equations are applied in clinical practice if treatment drop-in is common. We aimed to quantify the treatment drop-in in a large contemporary national cohort to determine whether equations are likely to require adjustment. METHODS: Eight de-identified individual-level national health administrative datasets in Aotearoa New Zealand were linked to establish a cohort of almost all New Zealanders without CVD and aged 30-74 years in 2006. Individuals dispensing blood-pressure-lowering and/or lipid-lowering medications between 1 July 2006 and 31 December 2006 (baseline dispensing), and in each 6-month period during 12 years' follow-up to 31 December 2018 (follow-up dispensing), were identified. Person-years of treatment drop-in were determined. RESULTS: A total of 1 399 348 (80%) out of the 1 746 695 individuals in the cohort were not dispensed CVD medications at baseline. Blood-pressure-lowering and/or lipid-lowering treatment drop-in accounted for 14% of follow-up time in the group untreated at baseline and increased significantly with increasing predicted baseline 5-year CVD risk (12%, 31%, 34% and 37% in <5%, 5-9%, 10-14% and ≥15% risk groups, respectively) and with increasing age (8% in 30-44 year-olds to 30% in 60-74 year-olds). CONCLUSIONS: CVD preventive treatment drop-in accounted for approximately one-third of follow-up time among participants typically eligible for preventive treatment (≥5% 5-year predicted risk). Equations derived from cohorts with long-term follow-up that do not adjust for treatment drop-in effect will underestimate CVD risk in higher risk individuals and lead to undertreatment. Future CVD risk prediction studies need to address this potential flaw.

Comprehensive evaluation of nitrogen contamination in water ecosystems of the Miyun reservoir watershed, northern China: distribution, source apportionment and risk assessment.

Miyun Reservoir plays a vital role as a source of drinking water for Beijing, however it grapples with nitrogen contamination issues that have been poorly understood in terms of their distribution, source, and associated health risks. This study addresses this knowledge gap by employing data on nitrate nitrogen (NO3--N), chloride (Cl-), dual isotopic compositions of NO3- (δ15N-NO3- and δ18O-NO3-) data in water ecosystems, systematically exploring the distribution, source and health risk of nitrogen contaminants in Miyun reservoir watersheds. The results showed that over the past 30 years, surface water runoff has exhibited a notable decrease and periodic fluctuations due to the combined influence of climate and anthropogenic activities, while the total nitrogen (TN) concentration in aquatic ecosystems presented an annual fluctuating upward trend. The TN concentration in the wet season was predominantly elevated because a large amount of nitrogen contaminants migrated into water ecosystems through heavy rainfall or river erosion. The concentration of NO3--N, the main contaminant of the water ecosystems, showed distinct variations across different watersheds, followed as rivers over the Miyun reservoir. Moreover, NO3--N levels gradually increased from upstream to downstream in different basins. NO3--N in surface water was mainly derived from the mixture of agricultural ammonia fertilizer and sewage and manure, with a minority of samples potentially undergoing denitrification. Comparatively, the main sources of NO3--N in groundwater were soil N and sewage and manure, while the denitrification process was inactive. The carcinogenic risks caused by NO3--N in groundwater were deemed either nonexistent or minimal, while the focus should predominantly be on potential non-carcinogenic risks, particularly for infants and children. Therefore, it is crucial to perform proactive measures aimed at safeguarding water ecosystems, guided by an understanding of the distribution, sources, and associated risks of nitrogen contamination.

Identifying the genetic mechanism of medium-low temperature fluoride-enriched geothermal groundwater by the self-organizing map and evaluating health risk in the Wugongshan area, southeast China.

Fluoride-enriched groundwater is a serious threat for groundwater supply around the world. The medium-low temperature fluoride-enriched geothermal groundwater resource is widely distributed in the circum-Wugongshan area. And the fluoride concentration of all geothermal samples exceeds the WHO permissible limit of 1.5 mg/L. The Self-Organizing Map method, hydrochemical and isotopic analysis are used to decipher the driving factors and genetic mechanism of fluoride-enriched geothermal groundwater. A total of 19 samples collected from the circum-Wugongshan geothermal belt are divided into four clusters by the self-organizing map. Cluster I, Cluster II, Cluster III, and Cluster IV represent the geothermal groundwater with the different degree of fluoride concentration pollution, the different hydrochemical type, and the physicochemical characteristic. The high F- concentration geothermal groundwater is characterized by HCO3-Na with alkalinity environment. The δD and δ18O values indicate that the geothermal groundwater origins from the atmospheric precipitation with the recharge elevation of 1000-2100 m. The dissolution of fluoride-bearing minerals is the main source of fluoride ions in geothermal water. Moreover, groundwater fluoride enrichment is also facilitated by water-rock interaction, cation exchange and alkaline environment. Additionally, the health risk assessment result reveals that the fluorine-enriched geothermal groundwater in the western part of Wugongshan area poses a more serious threat to human health than that of eastern part. The fluoride health risks of geothermal groundwater for different group show differentiation, 100% for children, 94.74% for adult females, and 68.42% for adult males, respectively. Compared with adult females and adult males, children faced the greatest health risks. The results of this study provide scientific evaluation for the utilization of geothermal groundwater and the protection of human health around the Wugongshan area.

Mapping and assessment of groundwater pollution risks in the main aquifer of the Mostaganem plateau (Northwest Algeria): utilizing the novel vulnerability index and decision tree model.

Water plays a pivotal role in socio-economic development in Algeria. However, the overexploitations of groundwater resources, water scarcity, and the proliferation of pollution sources (including industrial and urban effluents, untreated landfills, and chemical fertilizers, etc.) have resulted in substantial groundwater contamination. Preserving water irrigation quality has thus become a primary priority, capturing the attention of both scientists and local authorities. The current study introduces an innovative method to mapping contamination risks, integrating vulnerability assessments, land use patterns (as a sources of pollution), and groundwater overexploitation (represented by the waterhole density) through the implementation of a decision tree model. The resulting risk map illustrates the probability of contamination occurrence in the substantial aquifer on the plateau of Mostaganem. An agricultural region characterized by the intensive nutrients and pesticides use, the significant presence of septic tanks, widespread illegal dumping, and a technical landfill not compliant with environmental standards. The critical situation in the region is exacerbated by excessive groundwater pumping surpassing the aquifer's natural replenishment capacity (with 115 boreholes and 6345 operational wells), especially in a semi-arid climate featuring limited water resources and frequent drought. Vulnerability was evaluated using the DRFTID method, a derivative of the DRASTIC model, considering parameters such as depth to groundwater, recharge, fracture density, slope, nature of the unsaturated zone, and the drainage density. All these parameters are combined with analyses of inter-parameter relationship effects. The results show a spatial distribution into three risk levels (low, medium, and high), with 31.5% designated as high risk, and 56% as medium risk. The validation of this mapping relies on the assessment of physicochemical analyses in samples collected between 2010 and 2020. The results indicate elevated groundwater contamination levels in samples. Chloride exceeded acceptable levels by 100%, nitrate by 71%, calcium by 50%, and sodium by 42%. These elevated concentrations impact electrical conductivity, resulting in highly mineralized water attributed to anthropogenic agricultural pollution and septic tank discharges. High-risk zones align with areas exhibiting elevated nitrate and chloride concentrations. This model, deemed satisfactory, significantly enhances the sustainable management of water resources and irrigated land across various areas. In the long term, it would be beneficial to refine "vulnerability and risk" models by integrating detailed data on land use, groundwater exploitation, and hydrogeological and hydrochemical characteristics. This approach could improve vulnerability accuracy and pollution risk maps, particularly through detailed local data availability. It is also crucial that public authorities support these initiatives by adapting them to local geographical and climatic specificities on a regional and national scale. Finally, these studies have the potential to foster sustainable development at different geographical levels.

Drug-related emergency department visits: external validation of an assessment tool in a general emergency department population.

BACKGROUND: The process of identifying drug-related hospitalisations is subjective and time-consuming. Assessment tool for identifying hospital admissions related to medications (AT-HARM10) was developed to simplify and objectify this process. AT-HARM10 has not previously been externally validated, thus the predictive precision of the tool is uncertain. AIM: To externally validate AT-HARM10 in adult patients admitted to the emergency department (ED). METHOD: This retrospective cross-sectional study investigated 402 patients admitted to the ED, Diakonhjemmet Hospital, Oslo, Norway. A trained 5th-year pharmacy student used AT-HARM10 to assess all patients and to classify their ED visits as possibly or unlikely drug-related. Assessment of the same patients by an interdisciplinary expert panel acted as the gold standard. The external validation was conducted by comparing AT-HARM10 classifications with the gold standard. RESULTS: According to AT-HARM10 assessments, 169 (42%) patients had a possible drug-related ED visit. Calculated sensitivity and specificity values were 95% and 71%, respectively. Further, positive and negative predictive values were 46% and 98%, respectively. Adverse effects/over-treatment and suboptimal treatment were the issues most frequently overestimated by AT-HARM10 compared with the gold standard. CONCLUSION: AT-HARM10 identifies drug-related ED visits with high sensitivity. However, the low positive predictive value indicates that further review of ED visits classified as possible drug-related by AT-HARM10 is necessary. AT-HARM10 can serve as a useful first-step screening that efficiently identifies unlikely drug-related ED visits, thus only a smaller proportion of the patients need to be reviewed by an interdisciplinary expert panel.

Are pharmaceutical residues in crops a threat to human health?

The application of biosolids, manure, and slurry onto agricultural soils and the growing use of treated wastewater in agriculture result in the introduction of human and veterinary pharmaceuticals to the environment. Once in the soil environment, pharmaceuticals may be taken up by crops, resulting in consequent human exposure to pharmaceutical residues. The potential side effects of pharmaceuticals administered in human medicine are widely documented; however, far less is known regarding the risks that arise from incidental dietary exposure. The aim of this study was to evaluate human exposure to pharmaceutical residues in crops and assess the associated risk to health for a range of pharmaceuticals frequently detected in soils. Estimated concentrations of carbamazepine, oxytetracycline, sulfamethoxazole, trimethoprim, and tetracycline in soil were used in conjunction with plant uptake and crop consumption data to estimate daily exposures to each compound. Exposure concentrations were compared to Acceptable Daily Intakes (ADIs) to determine the level of risk. Generally, exposure concentrations were lower than ADIs. The exceptions were carbamazepine, and trimethoprim and sulfamethoxazole under conservative, worst-case scenarios, where a potential risk to human health was predicted. Future research therefore needs to prioritize investigation into the health effects following exposure to these compounds from consumption of contaminated crops.

Assessment of Lifetime Risk for Cardiovascular Disease: Time to Move Forward.

Over the past decades, there has been a notable increase in the risk of Cardiovascular Disease (CVD), even among younger individuals. Policymakers and the health community have revised CVD prevention programs to include younger people in order to take these new circumstances into account. A variety of CVD risk assessment tools have been developed in the past years with the aim of identifying potential CVD candidates at the population level; however, they can hardly discriminate against younger individuals at high risk of CVD.Therefore, in addition to the traditional 10-year CVD risk assessment, lifetime CVD risk assessment has recently been recommended by the American Heart Association/American College of Cardiology and the European Society of Cardiology prevention guidelines, particularly for young individuals. Methodologically, the benefits of these lifetime prediction models are the incorporation of left truncation observed in survival curves and the risk of competing events which are not considered equivalent in the common survival analysis. Thus, lifetime risk data are easily understandable and can be utilized as a risk communication tool for Public Health surveillance. However, given the peculiarities behind these estimates, structural harmonization should be conducted in order to create a sex-, race-specific tool that is sensitive to accurately identifying individuals who are at high risk of CVD. In this review manuscript, we present the most commonly used lifetime CVD risk tools, elucidate several methodological and critical points, their limitations, and the rationale behind their integration into everyday clinical practice.

Spatio-temporal distribution and source contributions of the ambient pollutants in Lucknow city, India.

Clean air is imperative to the survival of all life forms on the planet. However, recent times have witnessed enormous escalation in urban pollution levels. It is therefore, incumbent upon us to decipher measures to deal with it. In perspective, the present study was carried out to assess PM10 and PM2.5 loading, metallic constituents, gaseous pollutants, source contributions, health impact and noise level of nine-locations, grouped as residential, commercial, and industrial in Lucknow city for 2019-21. Mean concentrations during pre-monsoon for PM10, PM2.5, SO2 and NO2 were: 138.2 ± 35.2, 69.1 ± 13.6, 8.5 ± 3.3 and 32.3 ± 7.4 µg/m3, respectively, whereas post-monsoon concentrations were 143.0 ± 33.3, 74.6 ± 14.5, 12.5 ± 2.1, and 35.5 ± 6.3 µg/m3, respectively. Exceedance percentage of pre-monsoon PM10 over National Ambient Air Quality Standards (NAAQS) was 38.2% while that for post-monsoon was 43.0%; whereas corresponding values for PM2.5 were 15.2% and 24.3%. Post-monsoon season showed higher particulate loading owing to wintertime inversion and high humidity conditions. Order of elements associated with PM2.5 is Co < Cd < Cr < Ni < V < Be < Mo < Mn < Ti < Cu < Pb < Se < Sr < Li < B < As < Ba < Mg < Al < Zn < Ca < Fe < K < Na and that with PM10 is Co < Cd < Ni < Cr < V < Ti < Be < Mo < Cu < Pb < Se < Sr < Li < B < As < Mn < Ba < Mg < Al < Fe < Zn < K < Na < Ca. WHO AIRQ + ascertained 1654, 144 and 1100 attributable cases per 0.1 million of population to PM10 exposure in 2019-21. Source apportionment was carried out using USEPA-PMF and resolved 6 sources with highest percent contributions including road dust re-entrainment, biomass burning and vehicular emission. It is observed that residents of Lucknow city regularly face exposure to particulate pollutants and associated constituents making it imperative to develop pollution abetment strategies.