Standard Risk Assessment Tools Research Articles

Harnessing AI for Early Detection of Cardiovascular Diseases: Insights from Predictive Models Using Patient Data

Cardiovascular diseases (CVDs) continue to be the leading cause of death in the world, taking millions of lives every year. Early detection and treatment of these diseases are critical in preventing deaths and illnesses. Currently, traditional diagnostic methods like routine clinical examinations and other standard risk assessment tools fail to detect CVDs in early on set stages, posing numerous limitations for preventable interventions. This work explores incorporating artificial intelligence (AI) to catalyze early CVD diagnosis using AI models for patient data including electrocardiogram (ECG), wearable-generated metrics, and medical history. The research showcased the ability of AI to predict with high accuracy when CVD would start using machine learning methods such as Random Forest, Support Vector Machines (SVM) and Neural Networks. The powerful AI models were carefully constructed by training and testing them on an extensive dataset that contained measurements of diverse patient characteristics including many other readouts related to cardiovascular risk. Compared to traditional methods, the models outperformed, and Neural Networks had an accuracy of 92% in identifying high-risk patients. A hallmark of this work is that AI identifies subtle patterns and relationships within patient data ones that conventional approaches might not find. These AI-based predictive models might soon become part of the routine clinical evaluation for cardiovascular disease, providing a personalized and early health intervention to empower your cardiovascular care. Timely identification of these high-risk patients could allow for targeted interventions, leading to improved health and reductions in healthcare spending. Despite the promising potential that AI holds in healthcare, it also has brought up issues of data privacy, ethical use and the need for extensive clinical validation. This paper suggests a predictive strategy could be implemented using AI algorithms to lead early detection and management of CVD, which opens an opportunity for individualized care accompanied by big data era. Future studies should focus on improving such models with more diverse and larger datasets as well as overcoming logistical difficulties encountered in integrating AI into clinical workflows.

ImproRisk model, an open access risk assessment tool

Abstract ImproRisk is an open‐access Risk Assessment model, developed in Cyprus, which contributes to the harmonization, standardization and transparency of the Dietary Exposure Assessment methodologies across Europe. It is a simple and transparent tool, built in R, for conducting accurate dietary exposure assessments to chemical substances. Aiming to be established as a standardized Risk Assessment tool at European level, the model has been designed to accept occurrence and consumption data, coded according to the EFSA's food classification and description system version 2 (FoodEx2). ImproRisk users are able to estimate dietary exposure to a chemical substance under study at any level of the EFSA's FoodEx2, considering the FoodEx2 base term and the Process facet (F28). Dietary exposure is estimated at individual level for different population groups and exposure estimates are stratified by different demographic characteristics. ImproRisk is considered as a useful tool both for risk assessors and risk managers, as it facilitates decision making, by providing information regarding the percentage of the population exceeding the relevant health‐based guidance value or reference points for a specific chemical substance.

Root cause analysis and strategies for reducing falls amonginpatients in healthcare facilities: A narrative review.

Root Cause Analysis (RCA) is a systematic process which can be applied to analyze fall incidences in reactive manner to identify contributing factors and propose actions for preventing future falls. To better understand cause of falls and effective interventions for their reduction we conducted a narrative review of RCA and Strategies for Reducing Falls among Inpatients in Healthcare Facilities. In this narrative review, databases including Scopus, ISI Web of Science, Cochrane, and PubMed were searched to obtain the related literature published. Databases were searched from January 2005 until the end of March 2023. The Joanna Briggs Institute (JBI) tool was used for quality assessment of articles. To analyze the data, a five-stage framework analysis method was utilized. Seven articles that fulfilled the inclusion criteria were identified for this study. All of the selected studies were interventional in nature and employed the RCAmethod to ascertain the underlying causes of inpatient falls. The root causes discovered for falls involved patient-related factors (37.5%), environmental factors (25%), organizational and process factors (19.6%), staff and communication factors (17.9%). Strategies to reduce falls involved environmental measures and physical protection (29.4%), identifying, and displaying the causes of risk (23.5%), education and culturalization (21.6%), standard fall risk assessment tool (13.7%), and supervision and monitoring (11.8%). the findings identify the root causes of falls in inpatient units and provide guidance for successful action plan execution. Additionally, it emphasizes the importance of considering the unique characteristics of healthcare organizations and adapting interventions accordingly for effectiveness in different settings.

Interpretable machine learning predicts postpartum hemorrhage with severe maternal morbidity in a lower-risk laboring obstetric population

BackgroundEarly identification of patients at increased risk for postpartum hemorrhage (PPH) associated with severe maternal morbidity (SMM) is critical for preparation and preventative intervention. However, prediction is challenging in patients without obvious risk factors for postpartum hemorrhage with severe maternal morbidity. Current tools for hemorrhage risk assessment use lists of risk factors rather than predictive models. ObjectiveTo develop, validate (internally and externally), and compare a machine learning model for predicting PPH associated with SMM against a standard hemorrhage risk assessment tool in a lower risk laboring obstetric population. Study DesignThis retrospective cross-sectional study included clinical data from singleton, term births (>=37 weeks’ gestation) at 19 US hospitals (2016–2021) using data from 58,023 births at 11 hospitals to train a generalized additive model (GAM) and 27,743 births at 8 held-out hospitals to externally validate the model. The outcome of interest was PPH with severe maternal morbidity (blood transfusion, hysterectomy, vascular embolization, intrauterine balloon tamponade, uterine artery ligation suture, uterine compression suture, or admission to intensive care). Cesarean birth without a trial of vaginal birth and patients with a history of cesarean were excluded. We compared the model performance to that of the California Maternal Quality Care Collaborative (CMQCC) Obstetric Hemorrhage Risk Factor Assessment Screen. ResultsThe GAM predicted PPH with an area under the receiver-operating characteristic curve (AUROC) of 0.67 (95% CI 0.64–0.68) on external validation, significantly outperforming the CMQCC risk screen AUROC of 0.52 (95% CI 0.50–0.53). Additionally, the GAM had better sensitivity of 36.9% (95% CI 33.01–41.02) than the CMQCC screen sensitivity of 20.30% (95% CI 17.40–22.52) at the CMQCC screen positive rate of 16.8%. The GAM identified in-vitro fertilization as a risk factor (adjusted OR 1.5; 95% CI 1.2–1.8) and nulliparous births as the highest PPH risk factor (adjusted OR 1.5; 95% CI 1.4–1.6). ConclusionOur model identified almost twice as many cases of PPH as the CMQCC rules-based approach for the same screen positive rate and identified in-vitro fertilization and first-time births as risk factors for PPH. Adopting predictive models over traditional screens can enhance PPH prediction.

Renal function in pediatric urologic surgical patients: Insight from the National Surgical Quality Improvement Program—Pediatric cohort

Abstract Background Renal protection is a frequent indication for urological surgery in pediatric patients; however, preoperative assessment is not routinely performed. We assessed the rates of preoperative renal function testing and stratified outcomes after major pediatric urological surgery. Pediatric urology patients, specifically high-risk patients undergoing genitourinary surgeries, are likely to have an underdiagnosis of renal dysfunction after surgery. Materials and methods Cases were identified from the 2012 to 2019 National Surgical Quality Improvement Program—Pediatric database. Patients who underwent major urological surgery on an inpatient basis were included in this study. Abnormal renal function was defined as a creatinine (Cr) level of ≥0.5 mg/dL (younger than 2 years) and a glomerular filtration rate of <90 mL/min (2 years or older). Glomerular filtration rate was calculated using the bedside Schwartz equation (2 years or older): estimated glomerular filtration rate = 0.413 × (height/Cr). Results A total of 17,315 patients were included, of whom 3792 (21.9%) had documented Cr values. Based on the defined criteria, abnormal renal function was found in 7.3% of infants (younger than 2 years), 33.6% of children (2–9 years), and 52.5% of adolescents (10–18 years). Patients with abnormal preoperative renal function values were significantly (p < 0.001) more likely to experience readmission (10.2% vs. 5.8%), reoperation (3.7% vs. 1.6%), surgical organ/space infection (0.9% vs. 0.4%), transfusion (1.5% vs. 0.6%), renal insufficiency (1.6% vs. 0.4%), or urinary tract infection (5.1% vs. 3.6%). Conclusions In this pediatric population, 21.9% of the patients had documented preoperative Cr values before major urological surgery. Patients with documented abnormal preoperative renal function tests experienced higher complication rates. These patients have higher rates of progressive renal insufficiency and acute renal failure than those with normal renal function. The introduction of a standardized and unbiased risk assessment tool has the potential to offer patients benefits by pinpointing individuals with a heightened risk of complications. Further investigation is necessary to enhance the precise categorization of at-risk patients.

Standard Risk Assessment Tools Fall Short to Assess Risk in Transplant Patients

Standard Risk Assessment Tools Fall Short to Assess Risk in Transplant Patients

Abstract A022: Assessing, understanding, and addressing social determinants of cancer health disparities through patient navigation among rural Arkansans

Abstract The Winthrop P. Rockefeller Cancer Institute at the University of Arkansas for Medical Sciences (UAMS), Office of Community Outreach and Engagement has developed a Cancer Patient Navigation Program dedicated to improving cancer care for everyone in Arkansas. The team includes nurse navigators and community health workers that help bridge the gap between cancer patients, and financial resources in the community, and health care providers. The Cancer Patient Navigation Program emphasizes patient empowerment through prevention, screening, and treatment for rural and underserved populations across the state. The aim of the program is to help eliminate barriers to health care by providing resources for cancer treatment to rural and underserved populations across Arkansas. Navigators and community health works are located throughout every geographic region of Arkansas and are representative of the diversity in the communities they serve. Navigators and community health workers use the Protocol for Responding to and Assessing Patients’ Assets, Risks, and Experiences (PRAPARE®) to identify cancer patients’ barriers to care. PRAPARE® is a standardized patient risk assessment tool consisting of a set of national core measures as well as a process for addressing the social drivers at both the patient and population levels. Since May 2022, the Cancer Patient Navigation program has assessed and addressed the needs of 350 cancer patients. The data collected by navigators and community health workers has improved care coordination services, increased collaborations with local community partners with similar goals, and provided a unique opportunity for UAMS to better understand challenges of cancer patients and provide more appropriate services and care that is needed on a community level. The PRAPRE data has allowed the Office of Community Outreach and Engagement to understand the number of social determinants risks as well as the most common social determinant risks in our patient population. The risk tally score established a baseline to determine who might be more “at risk” by both geographic location and cancer diagnosis. To date, the data collected has been analyzed to track referrals and interventions. The data will further be used to ensure community-engagement priorities and resources are integrated into all Winthrop P. Rockefeller Cancer Institute research cores and clinical enterprises. Addressing the adverse social drivers of health will ultimately allow UAMS to improve patient well-being, facilitate access to prevention, screening, and treatment. Citation Format: Valandra L. German. Assessing, understanding, and addressing social determinants of cancer health disparities through patient navigation among rural Arkansans [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr A022.

Tissue Perfusion and the Braden Scale as Predictors of Pressure Injury Risk in the Intensive Care Unit Patient

Purpose: The national rate of pressure injury (PI) in the intensive care unit (ICU) 2016-2018 was 5.97%, while at one hospital in Honolulu, Hawaii it averaged 13%. The Braden scale is the gold standard PI risk assessment tool. Researchers have reported the Braden scale has limited value in the ICU setting and consider tissue perfusion to be the better indicator. The aim was to determine if tissue perfusion, as measured by noninvasive transcutaneous tissue oxygen levels, was a predictor of PI risk development.Methods: Electronic medical records of 161 patients admitted from January 1, 2017 to June 30, 2019 were retrospectively reviewed. Patients’ characteristics were summarized using descriptive statistics. Bivariate associations with the development of PI were examined using Fisher’s exact test for the categorical variables, and Wilcoxon rank-sum test for the continuous variables. A multivariable logistic model was fitted for the development of PI with adjustments for potential confounders.Results: Of 161 patients, 125 met the inclusion criteria. Length of stay, Acute Physiology and Chronic Health Evaluation II score, use of vasopressors, and the Braden score were statistically significant predictors of PI risk development; tissue perfusion was not significant.Conclusion: ICU patients have a higher mortality and severity of illness. The Braden score guides implementation of PI preventative measures. The relationship between tissue perfusion and PI development may warrant further research. A broader clinical picture to incorporate the Braden scale and other risk factors in PI development such as Acute Physiology and Chronic Health Evaluation II score and use of vasopressors should be considered.

Nationwide Trends in Hospitalizations with Heart Failure Preserved Ejection Fraction and Subsequent Cardiovascular Outcomes in Elderly Patients with Leukemia [2016-2019]

Background: Leukemia and the therapeutic treatments for leukemia are both associated with cardiovascular side effects. Heart failure is one of the most identified side effects related to cancer or cancer-related therapies. Evidence suggests a higher risk of HFrEF (heart failure with reduced ejection fraction) and its consequences, there is limited data on the trends of HFpEF admissions in Leukemia patients. In this study, we are using a nationally representative population to study the trends in HFpEF-related admissions and outcomes in elderly Leukemia patients. Methods: A retrospective analysis was conducted using the National Inpatient Sample from the 2016-2019 dataset. Elderly patients older than 65 years with leukemia were selected and the trends of HFpEF were studied over these 4 years. In this study, we used both univariable and multivariable regression analysis to adjust the odds ratio and compared and followed the trends over 4 years. Co-primary outcomes were major adverse cardiac and cerebrovascular events [MACCE - all-cause mortality, acute myocardial infarction (AMI), acute ischemic stroke (AIS), and cardiac arrest] in HFpEF patients among the leukemia cohort. Results: There was a significantly higher prevalence and increasing trends of HFpEF admissions in cohort with leukemia vs non-leukemia between 2016 to 2019 (from 11.6% to 14.4% in leukemia vs. from 10.3% to 13.0%, p trend <0.001). A total of 66,345 admissions with HFpEF in leukemia patients were studied over a period of 4 years, with a median age of 81 [Table 1]. The majority of the patients studied were whites (87%), Medicare patients (93.6%), and urban teaching locations (66.5%). The baseline characteristics trends were matched in all the cohorts and significant comorbidities observed over a period of 2016-2019 were hypertension (75.8% and 70.2%), diabetes (35.8% and 38.7%), hyperlipidemia (46% and 52.1%), prior MI (9.5% and 9.9%), prior PCI (8.3% and 9.7%), prior CABG (10.8% and 9.5%%), alcohol use (0.9% and 1.4%), drug use (0.3% and 0.9%), chronic pulmonary disease (35.5% and 37.9%), obesity (14.5% and 18.1%), prior chemotherapy (4.4.% and 5.1%), prior radiotherapy (1.9% and 2.7%), and CKD (44.6% and 47.8%). On following the trends from 2016 to 2019 we established that Leukemia patients with HFpEF had no significant improvement in in-hospital outcomes of MACCE including all-cause mortality, myocardial Ischemia, acute ischemic stroke, and cardiac arrest between 2016 and 2019 when potential confounders were adjusted. The univariate and multivariable-adjusted odds ratios for all-cause mortality, AMI, cardiac arrest, AIS, and MACCE were 0.97 and 1.04, 1.16 and 1.21, 0.99 and 1.00, 1.49 and 1.49, and 1.06 and 1.12, respectively when compared for Leukemia-HFpEF cohort of 2019 vs. 2016 (p>0.05). Median hospital stay and cost were stable during the study duration without any significantly increasing or decreasing trends. Conclusion: There were significantly increasing trends in hospitalizations with HFpEF in elderly leukemia patients without any substantial improvement in acute cardiovascular events between 2016 and 2019. It has been established that cardiovascular outcomes are closely associated with leukemia and related chemotherapy, there is no standardized risk stratification or assessment tool to assess the management of MACEE in Leukemia patients. Furthermore, prospective studies are required to better understand and address the association of leukemia-related treatments and their impact on HFpEF risk and MACCE in the long term.

Standard Risk Assessment Tools Fall Short to Assess Risk in Transplant Patients

Introduction: The HCT-CI (Hematopoietic Cell Transplantation-specific Comorbidity Index) predicts survival after HCT in patients with hematologic malignancies. HCT-CI ≥3 is associated with higher Non-Relapse Mortality (NRM) and lower overall survival in both allogeneic (allo) and autologous (auto)-HCT patients. The Disease Risk Index (DRI) Assessment Tool is a validated tool to categorize patients undergoing allo- transplant into risk categories based on disease status. It was developed to predict overall survival per disease status. This study was done to understand reasons for increased mortality in transplant patients at our center in 2021 compared to 2020 by comparing HCT-CI and DRI of transplant patients between the two years. Methods: The study was approved by our institution's IRB. A retrospective chart analysis of adult patients who underwent auto- or allo-HCT at Henry Ford Hospital in the years 2020 and 2021 was conducted. Relevant patient demographics, comorbidities, disease characteristics, and transplant-related data were collected. HCT-CI scores were calculated on all patients using the online calculator (https://www.mdcalc.com/calc/3980/hematopoietic-cell-transplantation-specific-comorbidity-index-hct-ci). Patients were also risk stratified based on the DRI Assessment Tool (https://cibmtr.org/CIBMTR/Resources/Research-Tools-Calculators/Disease-Risk-Index-DRI-Assignment-Tool). Data was reviewed and collected by investigators and compiled in a confidential platform. Results: A total of 166 patient records between 2020 and 2021 were reviewed. In 2020, 46 patients underwent auto-HCT and 28 underwent allo-HCT. In 2021, 58 patients underwent auto-HCT and 34 patients underwent allo-HCT. The one-year post transplant survival rates for patients are elucidated in Table 1. The median HCT-CI scores amongst the patients who underwent transplant was 3 in 2020 and 4 in 2021(refer Table 2). When assessing the Disease Risk Index, overall, more patients with higher disease risk were transplanted in 2021 compared to 2020 (refer Table 3). 16 patients (12 in 2021 and 4 in 2020) underwent transplant for diseases that are not included in the DRI assessment tool. Of these, 8 patients in 2021 underwent allo-HCT. These included aplastic anemia (AA), inherited bone marrow failure syndromes (BMF), solid tumors, primary CNS lymphomas, mycosis fungoides and hemophagocytic lymphohistiocytosis (HLH). Conclusion: The HCT-CI and the DRI are both tools used in transplant centers to risk stratify patients pre-transplant. The use of both tools can give a good sense of post-transplant outcomes, combining both individual patient characteristics as well as diseases specific variations. These data are also important for monitoring outcomes at transplant centers. In this study, patients who had an HCT-CI >/3 were similar in both years. The DRI however could not be ascertained in 16 patients, as these diseases are not currently included in the DRI. This makes outcome prediction for these particular patients suboptimal especially if they do not have as many comorbidities but still higher risk diseases. Furthermore, this precludes effective outcome monitoring in and amongst transplant centers. The combination of both the HCT-CI and the DRI would perform better if the DRI tool is revised to become more comprehensive or by creating a DRI that is specific for non-malignant disorders like AA, HLA and BMF. We intend to propose this to CIBMTR for further consideration.

Injury hazard assessment in schools: Findings from a pilot study in Karachi, Pakistan

IntroductionInjuries are a major public health concern and one of the leading causes of death and disability worldwide. Childhood injuries contribute to a major proportion of this burden. ObjectiveTo identify injury hazards within school premises and playgrounds in Karachi, Pakistan. MethodsThis observational cross-sectional study took place in 107 public and private schools of Karachi, Pakistan using a self-structured standard injury risk assessment tool. This tool was developed after an extensive literature review, expert consultation, and field visits to a few local schools. Data related to school demographics, administrative data and injury hazards within the school boundaries were collected in schools offering education from nursery to secondary grades (through 10th grade, matriculation). Descriptive analysis were calculated. ResultsOut of 107 schools, only 12 were recording school-related injuries. A quarter (25%) of schools had some type of disaster drill exercises and built-in fire exits. Fire alarms were placed in 10 schools (9%), all of which were private. In 16 schools (15%), students had access to rooftop doors. There were multiple injury hazards in the school playgrounds. More than half of the schools had hazardous playground surfaces, such as slippery, concrete and uneven ground. Over 80% of schools were not supervising the children during playtime and did not have a separate play area for children under 6 years old. In 38 schools (22%), there were multiple injury hazards in the play rides, such as broken equipment, rusted parts, and sharp edges. Moreover, nine schools (7%) had loose nuts, bolts, edges, belts, steps, or rails in their play rides. Inside, almost a quarter (24%, n = 76) of schools did not have proper insulation of electric wires. Protruded metal nails, which could be high risk for prick and cut injuries, were observed in 20% of the observed furniture. ConclusionIn conclusion, there are multiple injury hazards in the private and public schools of Karachi, Pakistan.

Decision‐making for pediatric cervical spine imaging after blunt trauma: Investigating team dynamics in the emergency department

AbstractObjectiveCervical spine imaging decision‐making for pediatric traumas is complex and multidisciplinary. Implementing a risk assessment tool has the potential to reduce variation in these decisions and unnecessary radiation exposure for pediatric patients. We sought to determine how emergency department–trauma team dynamics may affect implementation of such a tool.MethodsWe interviewed (pediatric and general emergency physicians, trauma surgeons, neurosurgeons, orthopedic surgeons and ED nurses at 21 hospitals to ascertain how team dynamics affect the pediatric cervical spine imaging decision‐making process. Data were coded following a framework‐driven deductive coding process and thematic analysis was used.ResultsForty‐eight physicians, advanced practice providers, and nurses from 21 hospitals (inclusive of three US regions, trauma levels I–III, and serving towns/cities of various population sizes) were interviewed. Overall, emergency physicians and trauma surgeons indicate being generally responsible for pediatric cervical spine imaging decisions. Conflict often occurs between these specialties due to differential weighting of concerns for missing an injury versus avoiding radiation exposure. Participants described a lack of trust and unclear roles regarding ownership for the final imaging decision. Nurses commonly described low psychological safety that prohibits them from participating in the decision‐making process.ConclusionsImplementation of a standardized risk assessment tool for cervical spine trauma imaging decisions must consider perspectives of both emergency medicine and trauma. Policies to define appropriate use of standardized tools within this team environment should be developed.

Cardiovascular disease risk assessment using a deep-learning-based retinal biomarker: a comparison with existing risk scores.

This study aims to evaluate the ability of a deep-learning-based cardiovascular disease (CVD) retinal biomarker, Reti-CVD, to identify individuals with intermediate- and high-risk for CVD. We defined the intermediate- and high-risk groups according to Pooled Cohort Equation (PCE), QRISK3, and modified Framingham Risk Score (FRS). Reti-CVD's prediction was compared to the number of individuals identified as intermediate- and high-risk according to standard CVD risk assessment tools, and sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated to assess the results. In the UK Biobank, among 48 260 participants, 20 643 (42.8%) and 7192 (14.9%) were classified into the intermediate- and high-risk groups according to PCE, and QRISK3, respectively. In the Singapore Epidemiology of Eye Diseases study, among 6810 participants, 3799 (55.8%) were classified as intermediate- and high-risk group according to modified FRS. Reti-CVD identified PCE-based intermediate- and high-risk groups with a sensitivity, specificity, PPV, and NPV of 82.7%, 87.6%, 86.5%, and 84.0%, respectively. Reti-CVD identified QRISK3-based intermediate- and high-risk groups with a sensitivity, specificity, PPV, and NPV of 82.6%, 85.5%, 49.9%, and 96.6%, respectively. Reti-CVD identified intermediate- and high-risk groups according to the modified FRS with a sensitivity, specificity, PPV, and NPV of 82.1%, 80.6%, 76.4%, and 85.5%, respectively. The retinal photograph biomarker (Reti-CVD) was able to identify individuals with intermediate and high-risk for CVD, in accordance with existing risk assessment tools.

Type2 Diabetes Risk Assessment in Health Care workers at Rashid Hospital – Dubai: A Cross-Sectional Study

Type 2 diabetes is a common and costly chronic disease in general as well as in the working population and its prevalence is increasing at an alarming rate. There are approximately 3000 healthcare professionals working in Rashid Hospital in different specialties. Objective: This study aimed to determine the prevalence of Type2 Diabetes risk among health care workers at Rashid Hospital. In addition, to find out the risk factors associated with type2 diabetes risk status and to identify the efficacy of lifestyle health promotion intended to improve health risk factors such as weight, body mass index (BMI), physical activity, and lifestyle that may lead to type2 diabetes, affecting the health of healthcare workers and their work performance. Methodology: A cross sectional study carried out at Rashid hospital under Dubai Health Authority. A convenience sample was selected by using Open Epi software from the projected population size of 3000, confidence level of 95%, marginal error 5% and the z- score 1.96%. Data collected by using a standardized diabetes risk assessment tool (FINDRISC tool, Finnish Diabetes Risk Score) for a period of one year. The subjects involved are 50% nursing staff, 30% doctors and 20% other health care workers. The inclusion criteria were staff in Rashid Hospital, both sex, age above 18 years and all nationalities. The exclusion criteria were pregnant women, people with known diabetes, age below 18 and above 65years. The data coding, entry and analysis done by SPSS 22 software version. Results: The study revealed that 45.1% of the participants were at low diabetes risk, 35.3% were at slightly elevated risk, 12.2% at moderate risk, 6.9% at high risk, and 0.5% at very high risk. Age, body mass index, waist circumference, daily physical activity, daily consumption of fruits, berries or vegetables, history in intake of antihypertensive medications, history of high blood glucose during illness or pregnancy and family history of diabetes had a great impact. Up on analysis Nurses are at high risk of contracting the disease shortly if you consider the combined value of high risk and very high-risk category (9.5%) as opposed to Doctors (1.8% +0.9%=2.6%) and other health care staff (4.5+1.5=6%). Conclusion: The modifiable factors like body weight, physical activities and food habit can decrease the risk of developing type 2 diabetes among Rashid Hospital healthcare professionals. Health promotion and education can decrease the diabetes risk and occupational health facility can support the follow up.

Red Blood Cell Distribution Width and Pediatric Community-Acquired Pneumonia Disease Severity.

No standardized risk assessment tool exists for community-acquired pneumonia (CAP) in children. This study aims to investigate the association between red blood cell distribution width (RDW) and pediatric CAP. Data prospectively collected by the Etiology of Pneumonia in the Community study (2010-2012) was used. Study population was pediatric patients admitted to tertiary care hospitals in Nashville and Memphis, Tennessee with clinically and radiographically confirmed CAP. The earliest measured RDW value on admission was used, in quintiles and also as a continuous variable. Outcomes analyzed were: severe CAP (requiring ICU, mechanical ventilation, vasopressor support, or death) or moderate CAP (hospital admission only). Analysis used multivariable logistic regression and restricted cubic splines modeling. In 1459 eligible children, the median age was 29 months (interquartile range: 12-73), median RDW was 13.3% (interquartile range: 12.5-14.3), and 289 patients (19.8%) developed severe disease. In comparison with the lowest RDW quintile (Q1), the adjusted odds ratio (95% CI) for severe CAP in subsequent quintiles were, Q2: 1.20 (0.72-1.99); Q3: 1.28 (0.76-2.14); Q4: 1.69 (1.01-2.82); Q5: 1.25 (0.73-2.13). Consistently, RDW restricted cubic splines demonstrated an independent, nonlinear, positive association with CAP severity (P = .027), with rapid increases in the risk of severe CAP with RDW values up to 15%. Higher presenting RDW was associated with an increased risk of severe CAP in hospitalized children. Widely available and inexpensive, RDW can serve as an objective data point to help with clinical assessments.

Supplier risk assessment strategy

Abstract The aim of the study is to create an effective and standard risk assessment tool that provides the company with support and security in purchasing of new products. The goal was to create a tool that complements and standardizes risk assessment forms and shows rapid results. Using the procurement risk management system, the risk associated with a given product can be determined easily and in a short time. In the process, critical areas where hazards may occur can be clearly identified and the risk can be minimized if properly managed.

Validation of the YLS/CMI on an Australian Juvenile Offending Population.

There is a wealth of research that shows juvenile justice systems that utilize structured and validated assessment tools, such as the YLS/CMI, are far more effective at reducing rates of recidivism than those who do not. In line with this research, the Department of Justice (DoJ) in Western Australia adopted the YLS/CMI as the standard risk assessment tool for evaluating the criminogenic risk and needs of youth entering the justice system. While there is evidence supporting the utility of the YLS/CMI in predicting recidivism, there is little research demonstrating its effectiveness in Australian juvenile populations and no such research in a West Australian population. There is also a lack of research on the utility of the tool with young Indigenous offenders, which is particularly concerning given the significant overrepresentation of Indigenous people in the Australian criminal justice system. Our study was the first to examine the reliability and predictive validity of the YLS/CMI on a sample of West Australian juvenile offenders. In this paper, we present the results of two analyses. The first examines the properties of the YLS/CMI in a cohort of 4,653 juvenile offenders in Western Australia, including factor structure, internal consistency, and differences between male and female youth and between Indigenous and non-Indigenous youth. Consistent with our hypotheses, the tool demonstrated excellent internal consistency (α = .91) and cross-validation analyses identified significant differences between groups on total YLS scores and risk domains. The second analysis examines the predictive validity of the YLS/CMI in a subsample of 921 youth with a minimum follow-up period of 2 years. The overall recidivism rate was 74.8% and there were differences in scores and recidivism rates for Indigenous compared to non-Indigenous youth, although the predictive accuracies in terms of AUC were similar (c. = 0.65 and 0.66, respectively).

Optimizing Community Supervision Practices with the Elo-rating System: A Proof-of-Concept

Record numbers of offenders are being released to community supervision. This poses a challenge to agencies and officers in charge of providing supervision because there are far more clients in need of supervision than officers can reasonably attend to. This challenge represents an opportunity for criminologists to work with agencies to find innovative ways to allocate their limited resources. Standardized risk assessments are the most commonly used tool for determining which clients receive the most resources (e.g., officer attention). But risk assessment is a static instrument that is incapable of making cross-client predictions. We offer a novel, dynamic approach by integrating the Elo-rating system into the risk assessment paradigm. Our study is meant to present a potential innovative solution and to demonstrate that it may have merit when applied in practice. We test our idea against data from the Pathways to Desistance Study and show that the Elo-rating system is a flexible tool that can be used to adjust to changes in risk more rapidly than standard risk assessment tools. We also show that the Elo-rating system, when combined with risk assessment, can increase the accuracy of prospective predictions of recidivism risk. We discuss how Elo-rating system could be used by community supervision agencies seeking to optimize decision-making.

COVID-19 RISK ASSESSMENT AMONG THE SUSCEPTIBLE INDIVIDUALS IN CHENNAI: A CASE CONTROL STUDY

BACKGROUND The 21st century is facing a long series of scourge from SARS (2003), H1N1 (2009), MERS (2012), and Ebola (2014) to Zika virus (2015). H1N1 spread by a novel inuenza virus in the year 2009, was the rst pandemic of the century, which luckily turned out to be not as severe as expected. In contrast COVID-19 pandemic is characterized by a very rapid spread and high fatality. The best way to prevent and slow down the transmission is to be well informed about its causes and spreads. Risk awareness thus prevent and slow-down the transmission of COVID-19. OBJECTIVES Ÿ To measure the risk of association between parameters of health, exposure, behaviour, social policy and COVID-19 infection Ÿ To evaluate the knowledge gaps on COVID-19 safety measures among the public METHODS A case control study was conducted among 100 cases and 200 controls. A standard Risk assessment tool was used to assess the risk factors for COVID-19 infection through telephonic interview after obtaining a verbal informed consent. RESULTS The odds of getting COVID-19 infection is 4.5 times higher with increase in age. The study also shows a positive and strong correlation between age group and total risk, co-morbidities and total risk among both cases and control groups. On the other hand, gender and behaviour showed a negative and negligible correlation among controls and positive but negligible correlation among the cases. CONCLUSION The risk of getting COVID – 19 disease increases with Age, underlying medical conditions, smoking, hand washing, mask wearing behavior, compliance with social distancing and place of residence. Although the government has laid preventive strategies, the results show unsatisfactory compliance towards social policies. Hence stringent laws should be implemented to scrutinize the population to follow these preventive measures.

Advancing racial justice in patient care encounters—yes, we can!

Advancing racial justice in patient care encounters—yes, we can!