A comparison of different methods for calculating overall risk scores from risk factors ascertained in a computerized obstetric information system

Summary Objective: Identification of risk factors for bleeding and prospective evaluation of two bleeding risk scores in the treatment of acute venous thromboembolism. Design: Secondary analysis of a prospective, randomized, assessor-blind, multicenter clinical trial. Setting: One university and 2 regional teaching hospitals. Patients: 188 patients treated with heparin or danaparoid for acute venous thromboembolism. Measurements: The presenting clinical features, the doses of the drugs, and the anticoagulant responses were analyzed using univariate and multivariate logistic regression analysis in order to evaluate prognostic factors for bleeding. In addition, the recently developed Utrecht bleeding risk score and Landefeld bleeding risk index were evaluated prospectively. Results: Major bleeding occurred in 4 patients (2.1%) and minor bleeding in 101 patients (53.7%). For all (major and minor combined) bleeding, body surface area ≤2 m2 (odds ratio 2.3, 95% Cl 1.2-4.4; p = 0.01), and malignancy (odds ratio 2.4, 95% Cl 1.1-4.9; p = 0.02) were confirmed to be independent risk factors. An increased treatment-related risk of bleeding was observed in patients treated with high doses of heparin, independent of the concomitant activated partial thromboplastin time ratios. Both bleeding risk scores had low diagnostic value for bleeding in this sample of mainly minor bleeders. Conclusions: A small body surface area and malignancy were associated with a higher frequency of bleeding. The bleeding risk scores merely offer the clinician a general estimation of the risk of bleeding. In patients with a small body surface area or in patients with malignancy, it may be of interest to study whether limited dose reduction of the anticoagulant drug may cause less bleeding without affecting efficacy.

Download Full-text

The development of information interaction as a key element of state risk management and health protection

Sanitarnyj vrač (Sanitary Inspector) ◽

10.33920/med-08-2003-08 ◽

2020 ◽

pp. 68-76

Author(s):

S. Voronkova

Keyword(s):

Risk Factors ◽

Health Promotion ◽

Information System ◽

Information Interaction ◽

New Information ◽

Wide Range ◽

Working Age ◽

The Russian Federation ◽

Working Age Population ◽

Types Of Information

The article discusses ways to obtain information about risk factors and the health status of the population. The article describes a new information system «labor Medicine», which allows to organize the collection of a wide range of data for further analysis and application in the activities of various Executive authorities, public organizations, foundations, legal entities and citizens. It is proposed to improve this system by expanding the types of information collected, creating a passport for health promotion organizations, as well as integration with systems that are being implemented in the Russian Federation for managing the health of the working-age population in the context of state policy in the field of Informatization.

Download Full-text

Predicting COVID-19 mortality with electronic medical records

npj Digital Medicine ◽

10.1038/s41746-021-00383-x ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Hossein Estiri ◽

Zachary H. Strasser ◽

Jeffy G. Klann ◽

Pourandokht Naseri ◽

Kavishwar B. Wagholikar ◽

...

Keyword(s):

Risk Factors ◽

Medical Information ◽

Age Groups ◽

Prognostic Models ◽

Smoking History ◽

Risk Scores ◽

Gradient Boosting ◽

Chronic Obstructive ◽

Clinical Expertise ◽

History Of

AbstractThis study aims to predict death after COVID-19 using only the past medical information routinely collected in electronic health records (EHRs) and to understand the differences in risk factors across age groups. Combining computational methods and clinical expertise, we curated clusters that represent 46 clinical conditions as potential risk factors for death after a COVID-19 infection. We trained age-stratified generalized linear models (GLMs) with component-wise gradient boosting to predict the probability of death based on what we know from the patients before they contracted the virus. Despite only relying on previously documented demographics and comorbidities, our models demonstrated similar performance to other prognostic models that require an assortment of symptoms, laboratory values, and images at the time of diagnosis or during the course of the illness. In general, we found age as the most important predictor of mortality in COVID-19 patients. A history of pneumonia, which is rarely asked in typical epidemiology studies, was one of the most important risk factors for predicting COVID-19 mortality. A history of diabetes with complications and cancer (breast and prostate) were notable risk factors for patients between the ages of 45 and 65 years. In patients aged 65–85 years, diseases that affect the pulmonary system, including interstitial lung disease, chronic obstructive pulmonary disease, lung cancer, and a smoking history, were important for predicting mortality. The ability to compute precise individual-level risk scores exclusively based on the EHR is crucial for effectively allocating and distributing resources, such as prioritizing vaccination among the general population.

Download Full-text

Prenatal Sociodemographic Factors Predicting Maltreatment of Children up to 3 Years Old: A Prospective Cohort Study Using Administrative Data in Japan

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18052505 ◽

2021 ◽

Vol 18 (5) ◽

pp. 2505

Author(s):

Aya Isumi ◽

Kunihiko Takahashi ◽

Takeo Fujiwara

Keyword(s):

Risk Factors ◽

Cohort Study ◽

Child Maltreatment ◽

Survey Data ◽

Prospective Cohort Study ◽

Prospective Cohort ◽

Characteristic Curve ◽

Risk Scores ◽

Prenatal Risk ◽

Prenatal Risk Factors

Identifying risk factors from pregnancy is essential for preventing child maltreatment. However, few studies have explored prenatal risk factors assessed at pregnancy registration. This study aimed to identify prenatal risk factors for child maltreatment during the first three years of life using population-level survey data from pregnancy notification forms. This prospective cohort study targeted all mothers and their infants enrolled for a 3- to 4-month-old health check between October 2013 and February 2014 in five municipalities in Aichi Prefecture, Japan, and followed them until the child turned 3 years old. Administrative records of registration with Regional Councils for Children Requiring Care (RCCRC), which is suggestive of child maltreatment cases, were linked with survey data from pregnancy notification forms registered at municipalities (n = 893). Exact logistic regression was used for analysis. A total of 11 children (1.2%) were registered with RCCRC by 3 years of age. Unmarried marital status, history of artificial abortion, and smoking during pregnancy were significantly associated with child maltreatment. Prenatal risk scores calculated as the sum of these prenatal risk factors, ranging from 0 to 7, showed high predictive power (area under receiver operating characteristic curve 0.805; 95% confidence interval (CI), 0.660–0.950) at a cut-off score of 2 (sensitivity = 72.7%, specificity = 83.2%). These findings suggest that variables from pregnancy notification forms may be predictors of the risk for child maltreatment by the age of three.

Download Full-text

Body Mass Index, Multi-Morbidity, and COVID-19 Risk Factors as Predictors of Severe COVID-19 Outcomes

Journal of Primary Care & Community Health ◽

10.1177/21501327211018559 ◽

2021 ◽

Vol 12 ◽

pp. 215013272110185

Author(s):

Sanjeev Nanda ◽

Audry S. Chacin Suarez ◽

Loren Toussaint ◽

Ann Vincent ◽

Karen M. Fischer ◽

...

Keyword(s):

Risk Factors ◽

Body Mass Index ◽

Hospital Admission ◽

Body Mass ◽

Risk Score ◽

The Body ◽

Risk Scores ◽

Nasopharyngeal Swab ◽

Morbidity Score ◽

The Impact

Purpose The purpose of the present study was to investigate body mass index, multi-morbidity, and COVID-19 Risk Score as predictors of severe COVID-19 outcomes. Patients Patients from this study are from a well-characterized patient cohort collected at Mayo Clinic between January 1, 2020 and May 23, 2020; with confirmed COVID-19 diagnosis defined as a positive result on reverse-transcriptase-polymerase-chain-reaction (RT-PCR) assays from nasopharyngeal swab specimens. Measures Demographic and clinical data were extracted from the electronic medical record. The data included: date of birth, gender, ethnicity, race, marital status, medications (active COVID-19 agents), weight and height (from which the Body Mass Index (BMI) was calculated, history of smoking, and comorbid conditions to calculate the Charlson Comorbidity Index (CCI) and the U.S Department of Health and Human Services (DHHS) multi-morbidity score. An additional COVID-19 Risk Score was also included. Outcomes included hospital admission, ICU admission, and death. Results Cox proportional hazards models were used to determine the impact on mortality or hospital admission. Age, sex, and race (white/Latino, white/non-Latino, other, did not disclose) were adjusted for in the model. Patients with higher COVID-19 Risk Scores had a significantly higher likelihood of being at least admitted to the hospital (HR = 1.80; 95% CI = 1.30, 2.50; P < .001), or experiencing death or inpatient admission (includes ICU admissions) (HR = 1.20; 95% CI = 1.02, 1.42; P = .028). Age was the only statistically significant demographic predictor, but obesity was not a significant predictor of any of the outcomes. Conclusion Age and COVID-19 Risk Scores were significant predictors of severe COVID-19 outcomes. Further work should examine the properties of the COVID-19 Risk Factors Scale.

Download Full-text

Has the time come to integrate genetic risk scores into clinical practice?

European Heart Journal ◽

10.1093/ehjci/ehaa946.3761 ◽

2020 ◽

Vol 41 (Supplement_2) ◽

Author(s):

F.V Moniz Mendonca ◽

M.I Mendonca ◽

A Pereira ◽

J Monteiro ◽

J Sousa ◽

...

Keyword(s):

Risk Factors ◽

Clinical Practice ◽

Genetic Variants ◽

Genetic Risk ◽

Odds Ratio ◽

Risk Scores ◽

Cumulative Number ◽

Genetic Risk Scores ◽

Risk Alleles ◽

Cad Risk

Abstract Background The risk for Coronary Artery Disease (CAD) is determined by both genetic and environmental factors, as well as by the interaction between them. It is estimated that genetic factors could account for 40% to 55% of the existing variability among the population (inheritability). Therefore, some authors have advised that it is time we integrated genetic risk scores into clinical practice. Aim The aim of this study was to evaluate the magnitude of the association between an additive genetic risk score (aGRS) and CAD based on the cumulative number of risk alleles in these variants, and to estimate whether their use is valuable in clinical practice. Methods A case-control study was performed in a Portuguese population. We enrolled 3120 participants, of whom 1687 were CAD patients and 1433 were normal controls. Controls were paired to cases with respect to gender and age. 33 genetic variants known to be associated with CAD were selected, and an aGRS was calculated for each individual. The aGRS was further subdivided into deciles groups, in order to estimate the CAD risk in each decile, defined by the number of risk alleles. The magnitude of the risk (odds ratio) was calculated for each group by multiple logistic regression using the 5th decile as the reference group (median). In order to evaluate the ability of the aGRS to discriminate susceptibility to CAD, two genetic models were performed, the first with traditional risk factors (TRF) and second with TRF plus aGRS. The AUC of the two ROC curves was calculated. Results A higher prevalence of cases over controls became apparent from the 6th decile of the aGRS, reflecting the higher number of risk alleles present (see figure). The difference in CAD risk was only significant from the 6th decile, increasing gradually until the 10th decile. The odds ratio (OR) for the last decile related to 5th decile (median) was 1.87 (95% CI:1.36–2.56; p<0.0001). The first model yielded an AUC=0.738 (95% CI:0.720–0.755) and the second model was slightly more discriminative for CAD risk (AUC=0.748; 95% CI:0.730–0.765). The DeLong test was significant (p=0.0002). Conclusion Adding an aGRS to the non-genetic risk factors resulted in a modest improvement in the ability to discriminate the risk of CAD. Such improvement, even if statistically significant, does not appear to be of real value in clinical practice yet. We anticipate that with the development of further knowledge about different SNPs and their complex interactions, and with the inclusion of rare genetic variants, genetic risk scores will be better suited for use in a clinical setting. Funding Acknowledgement Type of funding source: None

Download Full-text

Prognostic Value of D-dimer in patients with acute coronary syndrome treated by percutaneous coronary intervention: a retrospective cohort study

Thrombosis Journal ◽

10.1186/s12959-021-00281-y ◽

2021 ◽

Vol 19 (1) ◽

Author(s):

Runzhen Chen ◽

Chen Liu ◽

Peng Zhou ◽

Yu Tan ◽

Zhaoxue Sheng ◽

...

Keyword(s):

Risk Factors ◽

Percutaneous Coronary Intervention ◽

Prognostic Value ◽

Coronary Intervention ◽

Risk Scores ◽

Risk Of Death ◽

Clinical Risk ◽

Percutaneous Coronary ◽

D Dimer

Abstract Background Associations between D-dimer and outcomes of patients with acute coronary syndromes (ACS) remain controversial. This study aimed to investigate the prognostic value of D-dimer in ACS patients treated by percutaneous coronary intervention (PCI). Methods In this observational study, 3972 consecutive patients with ACS treated by PCI were retrospectively recruited. The X-tile program was used to determine the optimal D-dimer thresholds for risk stratifications. Cox regression with multiple adjustments was used for outcome analysis. Restricted cubic spline (RCS) analysis was performed to assess the dose-response association between D-dimer and outcomes. The C-index was calculated to evaluate the additional prognostic value of D-dimer when added to clinical risk factors and commonly used clinical risk scores, with internal validations using bootstrapping methods. The primary outcome was all-cause death. Results During a median follow-up of 720 days, 225 deaths occurred. Based on the thresholds generated by X-tile, ACS-PCI patients with median (420–1150 ng/mL, hazard ratio [HR]: 1.58, 95 % confidence interval [CI]: 1.14–2.20, P = 0.007) and high (≥ 1150 ng/mL, HR: 1.98, 95 % CI: 1.36–2.89, P < 0.001) levels of D-dimer showed substantially higher risk of death compared to those with low D-dimer (< 420 ng/mL). RCS analysis depicted a constant relation between D-dimer and various outcomes. The addition of D-dimer levels significantly improved risk predictions for all-cause death when combined with the fully adjusted models (C-index: 0.853 vs. 0.845, P difference = 0.021), the GRACE score (C-index: 0.826 vs. 0.814, P difference = 0.027), and the TIMI score (C-index: 0.804 vs. 0.776, P difference < 0.001). The predicted mortality at the median follow-up (two years) was 1.7 %, 5.2 %, and 10.9 % for patients with low, median, and high D-dimer, respectively, which was well matched with the observed mortality (low D-dimer group: 1.2 %, median D-dimer group: 5.2 %, and high D-dimer group: 12.6 %). Conclusions For ACS patients treated by PCI, D-dimer level was an independent predictor for adverse outcomes, and provided additional prognostic value when combined with clinical risk factors and risk scores. Risk stratifications based on D-dimer was plausible to differentiate ACS-PCI patients with higher risk of death.

Download Full-text

An absolute risk-guided approach to cardiovascular risk management within a chest pain clinic: the ARCPAC randomized trial

European Heart Journal ◽

10.1093/ehjci/ehaa946.2916 ◽

2020 ◽

Vol 41 (Supplement_2) ◽

Author(s):

J.A Black ◽

J Campbell ◽

J Sharman ◽

M Nelson ◽

S Parker ◽

...

Keyword(s):

Risk Factors ◽

Risk Factor ◽

Cardiovascular Risk ◽

Chest Pain ◽

Smoking Status ◽

Absolute Risk ◽

Pain Clinic ◽

Risk Scores ◽

Cardiovascular Risk Management ◽

Risk Factor Management

Abstract Background The majority of patients attending chest pain clinics are found not to have a cardiac cause of their symptoms, but have a high burden of cardiovascular risk factors that may be opportunistically addressed. Absolute risk calculators are recommended to guide risk factor management, although it is uncertain to what extent these calculations may assist with patient engagement in risk factor modification. Purpose We sought to determine the usefulness of a proactive, absolute risk-based approach, to guide opportunistic cardiovascular risk factor management within a chest pain clinic. Methods This was a prospective, open-label, blinded-endpoint study in 192 enhanced risk (estimated 5-year risk ≥8%, based on Australian Absolute Risk Calculator) patients presenting to a tertiary hospital chest pain clinic. Patients were randomized to best practice usual care, or intervention with development of a proactive cardiovascular risk management strategy framed around a discussion of the individual's absolute risk. Patients found to have a cardiac cause of symptoms were excluded as they constitute a secondary prevention population. Primary outcome was 5-year absolute cardiovascular risk score at minimum 12 months follow up. Secondary outcomes were individual modifiable risk factors (lipid profile, blood pressure, smoking status). Results 192 people entered the study; 100 in the intervention arm and 92 in usual care. There was no statistical difference between the two groups' baseline sociodemographic and clinical variables. The intervention group showed greater reduction in 5-year absolute risk scores (difference −2.77; p<0.001), and more favourable individual risk factors, although only smoking status and LDL cholesterol reached statistical significance (table). Conclusion An absolute risk-guided proactive risk factor management strategy employed opportunistically in a chest pain clinic significantly improves 5-year cardiovascular risk scores. Funding Acknowledgement Type of funding source: Foundation. Main funding source(s): Tasmanian Community Fund

Download Full-text

A Modified CAIDE Risk Score as a Screening Tool for Cognitive Impairment in Older Adults

Journal of Alzheimer s Disease ◽

10.3233/jad-210269 ◽

2021 ◽

pp. 1-14

Author(s):

Magdalena I. Tolea ◽

Jaeyeong Heo ◽

Stephanie Chrisphonte ◽

James E. Galvin

Keyword(s):

Risk Factors ◽

Older Adults ◽

Cognitive Impairment ◽

Risk Score ◽

Clinical Sample ◽

Community Sample ◽

Community Dwelling ◽

Cognitive Testing ◽

Risk Scores ◽

Predictive Values

Background: Although an efficacious dementia-risk score system, Cardiovascular Risk Factors, Aging, and Dementia (CAIDE) was derived using midlife risk factors in a population with low educational attainment that does not reflect today’s US population, and requires laboratory biomarkers, which are not always available. Objective: Develop and validate a modified CAIDE (mCAIDE) system and test its ability to predict presence, severity, and etiology of cognitive impairment in older adults. Methods: Population consisted of 449 participants in dementia research (N = 230; community sample; 67.9±10.0 years old, 29.6%male, 13.7±4.1 years education) or receiving dementia clinical services (N = 219; clinical sample; 74.3±9.8 years old, 50.2%male, 15.5±2.6 years education). The mCAIDE, which includes self-reported and performance-based rather than blood-derived measures, was developed in the community sample and tested in the independent clinical sample. Validity against Framingham, Hachinski, and CAIDE risk scores was assessed. Results: Higher mCAIDE quartiles were associated with lower performance on global and domain-specific cognitive tests. Each one-point increase in mCAIDE increased the odds of mild cognitive impairment (MCI) by up to 65%, those of AD by 69%, and those for non-AD dementia by > 85%, with highest scores in cases with vascular etiologies. Being in the highest mCAIDE risk group improved ability to discriminate dementia from MCI and controls and MCI from controls, with a cut-off of ≥7 points offering the highest sensitivity, specificity, and positive and negative predictive values. Conclusion: mCAIDE is a robust indicator of cognitive impairment in community-dwelling seniors, which can discriminate well between dementia severity including MCI versus controls. The mCAIDE may be a valuable tool for case ascertainment in research studies, helping flag primary care patients for cognitive testing, and identify those in need of lifestyle interventions for symptomatic control.

Download Full-text

Biventricular Unloading with Impella and Venoarterial Extracorporeal Membrane Oxygenation in Severe Refractory Cardiogenic Shock: Implications from the Combined Use of the Devices and Prognostic Risk Factors of Survival

Journal of Clinical Medicine ◽

10.3390/jcm10040747 ◽

2021 ◽

Vol 10 (4) ◽

pp. 747

Author(s):

Georgios Chatzis ◽

Styliani Syntila ◽

Birgit Markus ◽

Holger Ahrens ◽

Nikolaos Patsalis ◽

...

Keyword(s):

Risk Factors ◽

Extracorporeal Membrane Oxygenation ◽

Cardiogenic Shock ◽

Risk Scores ◽

Circulatory Support ◽

Membrane Oxygenation ◽

Venoarterial Extracorporeal Membrane Oxygenation ◽

Refractory Cardiogenic Shock ◽

Lactate Levels ◽

Va Ecmo

Since mechanical circulatory support (MCS) devices have become integral component in the therapy of refractory cardiogenic shock (RCS), we identified 67 patients in biventricular support with Impella and venoarterial Extracorporeal Membrane Oxygenation (VA-ECMO) for RCS between February 2013 and December 2019 and evaluated the risk factors of mortality in this setting. Mean age was 61.07 ± 10.7 and 54 (80.6%) patients were male. Main cause of RCS was acute myocardial infarction (AMI) (74.6%), while 44 (65.7%) were resuscitated prior to admission. The mean Simplified Acute Physiology Score II (SAPS II) and Sequential Organ Failure Assessment Score (SOFA) score on admission was 73.54 ± 16.03 and 12.25 ± 2.71, respectively, corresponding to an expected mortality of higher than 80%. Vasopressor doses and lactate levels were significantly decreased within 72 h on biventricular support (p < 0.05 for both). Overall, 17 (25.4%) patients were discharged to cardiac rehabilitation and 5 patients (7.5%) were bridged successfully to ventricular assist device implantation, leading to a total of 32.8% survival on hospital discharge. The 6-month survival was 31.3%. Lactate > 6 mmol/L, vasoactive score > 100 and pH < 7.26 on initiation of biventricular support, as well as Charlson comorbity index > 3 and prior resuscitation were independent predictors of survival. In conclusion, biventricular support with Impella and VA-ECMO in patients with RCS is feasible and efficient leading to a better survival than predicted through traditional risk scores, mainly via significant hemodynamic improvement and reduction in lactate levels.

Download Full-text