Correlation of Insulin Resistance With Short-Term Outcome in Nondiabetic Patients With ST-Segment Elevation Myocardial Infarction.

BACKGROUND:  Obviously, hyperglycemia and insulin resistance (IR) are common in patients with acute ST-segment elevation myocardial infarction (STEMI). Additionally, IR is a substantial risk factor for cardiovascular diseases. The study aims to evaluate the association between IR and short-term outcomes of acute STEMI patients without diabetes mellitus in the form of reperfusion success, the occurrence of heart failure, the development of arrhythmias, and mortality. METHOD:  A cross-sectional study was done from August 2021 to December 2021 in two cardiology centers in Al-Sadr Teaching hospital and Basrah Oil hospital in Basrah, Southern Iraq. Sixty-one nondiabetic hospitalized patients with acute STEMI were included in the study. Twenty-five (41%) of them received thrombolytics and 36 (59%) were managed with percutaneous transluminal coronary angioplasty. From each patient, a fasting blood sample was taken for calculation of the Homeostasis Model Assessment for IR (HOMA-IR) and triglyceride glucose index (TyG) index. The patients were evaluated within 1-week for (reperfusion success, echocardiography for calculation of the ejection fraction (EF), arrhythmias, and mortality), and within 4-weeks for mortality. RESULTS:  Within the tertile 3 of the HOMA-IR and TyG index, significant higher 4-week mortality (35% and 30%, respectively). Pearson correlation also showed significant and negative correlations between both HOMA-IR and TyG index values and EF. While reperfusion success, arrhythmias, and 1-week mortality did not correlate significantly with both HOMA-IR and TyG index. CONCLUSION:  IR as defined by HOMA-IR and TyG index was significantly associated with poor outcomes in patients with acute STEMI in the form of EF<55 and 4-week mortality.

Contribution of atmospheric dry deposition to stormwater loads for PAHs and trace metals in a small and highly trafficked urban road catchment.

A deep understanding of pollutant buildup and wash-off is essential for accurate urban stormwater quality modeling and for the development of stormwater management practices, knowing the potential adverse impacts of runoff pollution on receiving waters. In the context of quantifying the contribution of airborne pollutants to the contamination of stormwater runoff and assessing the need of developing an integrated AIR-WATER modeling chain, loads of polycyclic aromatic hydrocarbons (PAHs) and metal trace elements (MTEs) are calculated in atmospheric dry deposits, stormwater runoff, and surface dust stock within a small yet highly trafficked urban road catchment (~ 30,000 vehicles per day) near Paris. Despite the important traffic load and according to the current definition of "atmospheric" source, atmospheric deposition did not account for more than 10% of the PAHs and trace metal loads in stormwater samples for the majority of the events, based on the ratio of deposition to stormwater. This result shows that atmospheric deposition is not a major source of pollutants in stormwater, and thus, linking the air and water compartment in a modeling chain to have more accurate estimates of pollutant loads in stormwater runoff might not be relevant. Comparison of road dust with water samples demonstrates that only the fine fraction of the available stock is eroded during a rainfall event. Even if the atmosphere mostly generates fine particles, the existence of other sources of fine particles to stormwater runoff is highlighted.

Investigation of the wash-off process using an innovative portable rainfall simulator allowing continuous monitoring of flow and turbidity at the urban surface outlet.

Development of appropriate models, based on an in-depth understanding of the wash-off process, is essential to accurately estimating pollutant loads transported by stormwater, thereby minimizing environmental contamination. To this end, we developed an innovative rainfall simulator, which simulated an intense rainfall (120mm/h) and permitted the acquisition of runoff samples as well as the in situ monitoring of continuous flow and turbidity dynamics. Relationships between deposited sediments and total suspended solids in simulated runoff were thus investigated on two different types of surfaces within the Paris region in terms of loads and particle size distribution. Results demonstrate the occurrence of first flush phenomenon on the sidewalks even under constant flow. Results also show that the highest fraction conveyed by runoff consisted of fine (<16µm) and medium-sized (<100µm) particles, whose detachment was more favorable from smooth surfaces than from rougher ones. In terms of stormwater quality modelling, results suggest that the integration of a wash-off fraction based on both particle size and rainfall intensity could be an entrance for a better prediction of stormwater pollution.

Performance assessment of a commonly used "accumulation and wash-off" model from long-term continuous road runoff turbidity measurements.

The suitability of a commonly used accumulation and wash-off model for continuous modelling of urban runoff contamination was evaluated based on 11-month turbidity and flow-rate records from an urban street. Calibration and uncertainty analysis were performed using a Markov Chain Monte-Carlo sampling method for both suspended solids loads (discharge rates) and concentration modelling. Selected models failed at replicating suspended solids concentration over the complete monitoring period. The studied dataset indeed suggests that the accumulation process is rather unpredictable and cannot be satisfactorily represented with usual accumulation models unless short periods are considered. Regarding suspended solid loads modelling, noticeably better performance was achieved, but similar results could as well be obtained with much simpler constant concentration models. Unless providing very accurate estimates of concentrations in runoff, accounting for their temporal variability during rain events may therefore not always be necessary for pollutant loads modelling, as loads are in fact mostly explained by runoff volumes.