Risk Prediction of Fatal Suicide in Ilam Province, Iran

Abstract. Akbari M, Rafinejad J, Hanafi-Bojd AA, Aivazi AA, Biglarian A, Sheikhi S, Shavali Z, Akbarzadeh K. 2020. Human myiasis survey in Ilam Province, Southwest of Iran. Nusantara Bioscience 12: 143-147. Myiasis is the infestation of live human and vertebrate animals with dipterous larvae, which at least for a period. Ilam Province of Iran is one of the most important animal husbandry areas, especially nomadic, in Iran. The objective of this study was to identify the prevalence of myiasis in shepherds in Ilam Province. A cross-sectional study was conducted among the shepherds in Ilam Province, western Iran. Out of the 11 counties in Ilam Province, 6 were randomly chosen from three different climates for this study. A questionnaire was used by a trained interviewer to obtain the information from subjects. The disease has been seen in spring, summer, and autumn seasons. About 94.1% of people have been infested at least once. Pharyngeal myiasis had the highest prevalence with 58.3%. Itchy, painful throat, sneeze, cough, and headache were common symptoms. About 85.1% of people described the symptoms of the disease as severe and very severe. About 75.4% stated that the duration of the disease was more than 5 days. According to the results of the study, it was found that the prevalence of myiasis among shepherds in the Ilam Province is high and it is necessary to take appropriate measures to control the disease and increase health literacy.

Ilam tunnels inspection, maintenance, and rehabilitation: A case study

SummaryIn 1995, a peste des petits ruminants (PPR) outbreak was diagnosed in Ilam province in Iran near the border with Iraq both serologically and virologically. As then, despite all control measures, PPR has been identified in the whole country and has led to costs of at least US$1.5 million to the Iranian owners of sheep and goats.

IntroductionLeeches, a hermaphroditic, blood-sucking parasite arerarely reported in humans and animals as a cause of manyproblems. They vary in color, length and shape, and may beblack, brightly colored, or mottled. The leeches mainlyinhabit in ponds, lakes, and streams. The Limnatis niloticaspecies is a blood-sucking parasite that lives in stagnantwater in ponds and lakes. The strong jaws and muscularsuckers at the anterior and posterior ends of L. nilotica arethe main sign for detection. This species is commonlyfound existing in Southern Europe, North Africa, and theMiddle East including Iran (Bahmani et al. 2006). Theseleeches live in hosts and can cause anemia and may act asvectors of animal pathogens. The main symptoms includehaemoptysis, snoring, dyspnea, cough, dysphagia, andbleeding from the vagina (Bani Ismail et al. 2007;Estambale et al. 1992; Grosser and Pesic 2006; Yaghmaee2000). Hirudiniasis is not common in animal and human,but sporadic reports of leech infestations in humans andanimals are available from the Middle East and adjoiningcountries. In some reports in human beings, leeches as aforeign body and parasite in the respiratory tract havebeen reported, and in animals, leeches infesting the nasalcavity were reported in one camel in Iraq (Al-Ani andAl-Shareefi1995; Cheikh-Rouhou et al. 2000). In this study,a 3-year-old pregnant cow referred to a private clinic in theDehloran suburbs in Iran with acute respiratory distress andinappetite.Case reportA 3-year-old pregnant cow referred to a private clinic in theDehloran suburbs in Iran with acute respiratory distress andinappetite. The history of the case revealed that the mainfeed of the cow had been hay and grazing in pasture, andfor drinking water, a stream and sump were used 48 hprevious to the time of referral; the cow displayed severediscomfort, with little appetite, abnormal breathing, andrespiratory sounds. The case had no background of anydisorder. Examination of the case showed increasingrespiratory rates, bleeding from the mouth, and reluctanceto walk.The temperature, heart rate, and respiratory rate wereincreased slowly. Rectal examination manifested noabnormal signs and the fetus palpated and was alive.The mouth of the cow was fully opened, and the mouthcavity was fully explored. One leech was found attachedto the right-side cheek and tongue (Fig. 1). The leecheswere removed by using forceps carefully without theprescription of any drugs, and after examination, thespecies of leech was identified asL. nilotica.Thestrongjaws and muscular suckers at the anterior and posteriorends, the dark-green color surface with rows of greenspots on the dorsal surface, and yellowish-orange anddark-green bands on either side with a 100-mm lengthwere the main signs for detection of L. nilotica species.Investigations revealed that the animal used to drink waterfrom a nearby pond that had rainwater. The owner of thepresent case was educated not to allow the other animalsto drink water from the infested pond.

Investigating the effect of ambient temperature, sound type, and noise level on the heart rate of the elderly.

New score for predicting major bleeding in patients with atrial fibrillation using direct oral anticoagulants

BackgroundThe incidence of Acute Kidney Injury (AKI) continues to increase in the UK, with associated mortality rates remaining significant. Approximately one fifth of hospital admissions are associated with AKI and approximately a third of patients with AKI in hospital develop AKI during their time in hospital. A fifth of these cases are considered avoidable. Early risk detection remains key to decreasing AKI in hospitals, where sub-optimal care was noted for half of patients who developed AKI.MethodsElectronic anonymised data for adults admitted into the Royal Cornwall Hospitals Trust (RCHT) between 18th March and 31st December 2015 was trimmed to that collected within the first 24 h of hospitalisation. These datasets were split according to three separate time periods: data used for training the Takagi-Sugeno Fuzzy Logic Systems (FLS) and the multivariable logistic regression (MLR) models; data used for testing; and data from a later patient spell used for validation.Three fuzzy logic models and three MLR models were developed to link characteristics of patients diagnosed with a maximum stage AKI within 7 days of admission: the first models to identify any AKI Stage (FLS I, MLR I), the second for patterns of AKI Stage 2 or 3 (FLS II, MLR II), and the third to identify AKI Stage 3 (FLS III, MLR III). Model accuracy is expressed by area under the curve (AUC).ResultsAccuracy for each model during internal validation was: FLS I and MLR I (AUC 0.70, 95% CI: 0.64–0.77); FLS II (AUC 0.77, 95% CI: 0.69–0.85) and MLR II (AUC 0.74, 95% CI: 0.65–0.83); FLS III and MLR III (AUC 0.95, 95% CI: 0.92–0.98).ConclusionsFLS II and FLS III (and the respective MLR models) can identify with a high level of accuracy patients at high risk of developing AKI in hospital. These two models cannot be properly assessed against prior studies as this is the first attempt at quantifying the risk of developing specific Stages of AKI for a broad cohort of both medical and surgical inpatients. FLS I and MLR I performance is comparable to other existing models.

Background: Simple surgical and clinical risk scores are useful in mortality prediction. Aims: The study's aim was to validate three scores in real-world registry of percutaneous coronary intervention (PCI) for the left main coronary artery (LMCA). Methods: All data were obtained from the BIA-LM Registry. Discrimination and calibration of EuroSCORE II, ACEF, CHA2DS2-VASc, and CHA2DS2-VA were assessed with receiver operating characteristic (ROC) curves analysis and Hosmer-Lemeshow (HL) test. Results: The final cohort included 851 patients, median age was 71, and 156 patients had history of previous coronary artery bypass grafting (CABG). Median EuroSCORE II, ACEF, CHA2DS2-VASc, and CHA2DS2-VA were 3.1% (IQR 5.4%), 1.56 (IQR 0.9), 4 (IQR 2), and 4 (IQR 2), respectively. In the short- (30 days) and long-term (mean 4.1 years), there were 27 and 318 deaths. In short-term, EuroSCORE II showed the best discrimination in the overall population and subgroup with unprotected LMCA [area under the curve (AUC) 0.804, 95% CI 0.717-0.890 and AUC 0.826, 95% CI 0.737-0.913, respectively, p < 0.001 for comparisons with other models), with the best cut-off value at 7.1%. In long-term observation, EuroSCORE II and ACEF showed good predictive value (overall population: AUC 0.716, 95% CI 0.680-0.750 and AUC 0.725, 95% CI 0.690-760, respectively). In short- and long-term observation, EuroSCORE II and ACEF showed poor calibration (HL test p < 0.05) as compared to CHA2DS2-VASc (HL test p = 0.40 and 0.18). Conclusions: EuroSCORE II showed good mortality prediction in short-term observation; however, its predicted risk should be interpreted with caution due to poor calibration. ACEF and EuroSCORE II may be useful in long-term mortality prediction.

BackgroundIt is unclear whether increased vancomycin area under the curve (AUC) contributes to acute kidney injury (AKI) risk.MethodsThis retrospective cohort study was undertaken to determine whether vancomycin AUC > 550 is associated with a higher rate of AKI than an AUC < 550. Patients treated with vancomycin for at least 4 days at the St. Louis VA from 1/1/2016–9/31/2018 were included. The primary outcome was AKI (defined as an increase in serum creatinine by 0.3 mg/dL or 50% from baseline). Secondary outcomes included length of stay, readmission, or mortality in 30 days, AKI rate with concurrent antibiotics, and AKI rate with comorbidities. The AUC was calculated as daily dose (in mg) divided by vancomycin clearance. The variables of age ≥ 70, vancomycin AUC ≥ 550, creatinine clearance (CrCl) < 50 mL/minute, concomitant antibiotic administration, vancomycin treatment ≤ 7 days, and the presence of comorbidities were included in a bivariate analysis. Variables with a P-value of <0.2 were included in a multivariate logistic regression model.ResultsTwo hundred patients were included in the analysis; 100 patients with an AUC ≥ 550, and 100 with an AUC < 500. Only mean vancomycin dose (1722.50 mg vs. 2361.25 mg; P < 0.05), mean AUC (465.88 vs. 696.45; P < 0.05), and peak SCr (1.22 mg/dL vs. 1.48 mg/dL; P = 0.015) were significantly different between groups; AUC < 550 vs. AUC ≥ 550, respectively. Acute kidney injury occurred in 22% (44/200) of all patients; 42% (42/100) with a calculated AUC ≥ 550 developed AKI compared with 2% (2/100) of patients with an AUC < 550 (P < 0.05). The secondary outcomes of concomitant nephrotoxic agents, length of stay, readmission at 30 days, and 30-day mortality were not significantly different between groups. Only age ≥ 70, vancomycin AUC ≥ 550, CrCl < 50 mL/minute, concomitant piperacillin–tazobactam administration, and the presence of comorbidities were included in the multivariate regression. Age ≥ 70, CrCl < 50 mL/minute, and AUC ≥ 550 [OR 49.5 (95% CI 10.1 – 242.3; P < 0.05)] were found to be independently associated with risk for developing AKI.ConclusionPatients with a calculated vancomycin AUC ≥ 550 were found to have a significantly higher rate of AKI compared with those with an AUC < 550.DisclosuresAll authors: No reported disclosures.

Background: Pulmonary congestion is a key manifestation of decompensated heart failure (HF) and contributes to adverse outcomes, especially in patients with permanent atrial fibrillation (AF). However, practical tools enabling bedside, repeatable, and real-time assessment of pulmonary congestion remain limited. To create and internally validate a non-invasive predictive model for pulmonary congestion in patients with HF and permanent AF utilizing hemodynamic, echocardiographic, and clinical parameters. Methods: This retrospective study included 66 patients with HF and permanent AF, classified into pulmonary congestion and non-congestion groups based on standardized chest radiography criteria. Cardiography (ICG) parameters, echocardiographic indices, and laboratory markers were evaluated. A multivariable logistic regression model was developed using a backward elimination approach guided by the Akaike Information Criterion (AIC). Model performance was evaluated using the area under the curve (AUC), calibration, and decision curve analysis, with internal validation conducted through bootstrap resampling. Model interpretability was further assessed by comparing AUCs of individual predictors and examining risk stratification based on model-derived scores. Results: The final model identified independent associations of pulmonary congestion with left ventricular ejection fraction (LVEF) (OR = 0.934, 95% CI = 0.879–0.992), E/e′ ratio (OR = 1.229, 95% CI = 1.029–1.467), and thoracic fluid conductivity (TFC) (OR = 1.237, 95% CI = 1.070–1.431). The model showed strong discriminative ability (AUC = 0.865, 95% CI = 0.773–0.956), satisfactory calibration (Hosmer-Lemeshow test, p &gt; 0.05), and clinical utility. Internal validation using 500 bootstrap resamples confirmed these results, with robust discrimination (corrected AUC = 0.853, 95% CI = 0.763–0.942), consistent calibration, and maintained net clinical benefit. Model interpretability analysis confirmed its added discriminative value over individual predictors and supported its utility in stratifying pulmonary congestion risk. Conclusions: The proposed model provides a practical, non-invasive approach for identifying pulmonary congestion in patients with HF and AF. It may facilitate early bedside detection and support dynamic clinical decision-making.

The EuroSCORE in Western Denmark: A Population-Based Study

The histological grading plays an essential role in the treatment decision of lung cancer. Detected tumors are usually biopsied to confirm histologic grade. How to use MRI extracted radiomics features for accurately grading lung cancer is still challenging. To examine the diagnostic utility of multiparametric MRI radiomics and clinical factors for grading non-small-cell lung cancer (NSCLC). Retrospective. A total of 148 patients (25.7% female) with postoperative pathologically confirmed NSCLC and divided into the training cohort (N=110) and the validation cohort (N=38). A 1.5 T; single-shot turbo spin-echo (TSE), T2-weighted imaging (T2WI), and integrated shimming-echo planar imaging (ISHIM-EPI) diffusion-weighted imaging (DWI). A total of 2775 radiomics features were extracted from carcinomatous regions of interest on T2WI, DWI, and the apparent diffusion coefficient (ADC) maps. The five optimal features were selected by using the Student' s t-test, the least absolute shrinkage and selection operator (LASSO) and stepwise regression. The Radscore combined with clinical factors, which selected by univariate and multivariate analyses, to develop a radiomics-clinical nomogram. Its performance was evaluated in the training cohort and the validation cohort. The potential clinical usefulness was analyzed by the receiver operating characteristic curve (ROC), area under the curve (AUC), and the Hosmer-Lemeshow test. Student's t-test, univariate analyses, multivariate analyses, LASSO, ROC, AUC, and the Hosmer-Lemeshow test. P < 0.05 was considered statistically significant. Favorable discrimination performance was obtained for five optimal features (out of the 2775 features), using the training cohorts (AUC 0.761) and validation cohorts (AUC 0.753). In addition, the radiomics-clinical nomogram significantly improved the ability to identify histological grades in the training cohort (AUC 0.814) and the validation cohort (AUC 0.767). The radiomics-clinical nomogram based on multiparametric MRI might have the potential to distinguish the histological grade of NSCLC. 3 TECHNICAL EFFICACY: Stage 2.

204. The ALFA score predicts 30-day mortality after elective anterior lumbar interbody fusion

Background Recent studies have discussed the application of wrist circumference as an easy-to-use predictor of general and abdominal obesity. The aim of the current study is to evaluate the association of wrist circumference with generalized and abdominal obesity and to determine its sex- and age-specific optimal cutoff points in association with generalized and abdominal obesity in a national sample of pediatric population. Methods This nationwide survey was conducted among 14,880 students, aged 6-18 years, selected through a multistage, random cluster sampling method from rural and urban areas of 30 provinces in Iran from 2011 to 2012. Anthropometric indices (weight, height, wrist circumference, waist circumference [WC], hip circumference [HC]) were measured by standard protocols using calibrated instruments. Body mass index (BMI) and waist-to-height ratio (WHtR) were calculated. By considering the area under the curve (AUC) of the receiver operator characteristic (ROC) curves, we evaluated the association of wrist circumference with obesity indices and determined its sex- and age-specific optimal cutoff points in association with obesity. AUC: 0.5, AUC: 0.5-0.65 and AUC: 0.65-1.0 were interpreted as equal to chance, moderately and highly accurate tests, respectively. Results Overall, 13,486 children and adolescents with a mean age of 12.47±3.36 years completed the study (participation rate of 90.6%). In both genders, wrist circumference had a significant correlation with anthropometric measures including weight, height, BMI, WC, HC and WHtR. In all age groups and both genders, wrist circumference performed relatively well in classifying individuals into overweight (AUC: 0.67-0.75, p<0.001), generalized obesity (AUC: 0.81-0.85, p<0.001) and abdominal obesity (AUC: 0.82-0.87, p<0.001). Conclusions Wrist circumference is suggested to be a useful index for assessing excess weight in the pediatric age group. Its easy measurement without the need of calculation ratios might make it as a routine measurement in daily clinical practice and in large epidemiological studies.

Gully erosion is a key issue in natural resource management that often has severe environmental, economic, and social consequences. The objective of the present study is to assess the capability of weights-of-evidence (WofE) and frequency ratio (FR) models for spatial prediction of gully erosion susceptibility and characterizing susceptibility conditions at Chavar region, Ilam province, Iran. At first, a gully erosion inventory map is prepared, using multiple field surveys. In total, of the 63 gullies which have been identified, 44 (70 %) cases are randomly algorithm selected to build gully susceptibility models, while the remaining 19 (30 %) cases are used to validate the models. The effectiveness of gully erosion susceptibility assessment via GIS-based models depends on appropriate selection of the conditioning factors which play an important role in gully erosion. Learning vector quantization (LVQ), one of the supervised neural network methods, is employed in order to estimate variable importance. In this research, the selected conditioning factors are: lithology, land use, distance from river, soil texture, slope degree, slope aspect, plan curvature, topographic wetness index, drainage density, and altitude. Finally, validation of the gully dataset which has not been utilized during the spatial modeling process is applied to validate the gully susceptibility maps. The receiver operating characteristic curves for each gully susceptibility map (i.e., produced by WofE and FR) are drawn, and the areas under the curves (AUC) are calculated. The results show that the gully erosion susceptibility map produced by the frequency ratio model (AUC = 78.11 %) functions well in prediction compared with the WofE model (AUC = 70.07 %). Furthermore, LVQ results reveal that distance from river, drainage density, and land use are the most effective factors.