scholarly journals 976. Development and Validation of a Risk Score for Predicting Cardiovascular Events in HIV-Infected Patients

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S35-S36
Author(s):  
Styliani Karanika ◽  
Theodoros Karantanos ◽  
Herman Carneiro ◽  
Sabrina A Assoumou
Keyword(s):  
Cardiovascular Disease ◽  
Logistic Regression ◽  
Scoring System ◽  
Validation Cohort ◽  
Assessment Tools ◽  
Operating Characteristics ◽  
Cvd Risk ◽  
Risk Scoring ◽  
Development And Validation ◽  
Risk Scoring System

Abstract Background HIV-infected individuals are at higher risk for developing cardiovascular disease (CVD). We aimed to develop a model to predict 10-year cardiovascular (CV) risk given that commonly used CVD risk assessment tools might not be accurate for HIV-infected patients. Methods We conducted a retrospective cohort study of HIV-infected patients seen at Boston Medical Center between March 2012 and January 2017. Exclusion criteria are shown in Figure 1. Patients were divided into model development and validation cohorts. Logistic regression was used to create a risk model for CV events using data from the development cohort. The relationship between risk factors and CVD risk was summarized using a point-based risk-scoring system. Areas under the receiver-operating-characteristics curve (AUC) were used to evaluate model discrimination. The model was subsequently tested using the validation cohort. Results Of 3,867 eligible HIV-infected patients, 1,914 individuals met inclusion criteria (Figure 1). There were 256 CV events in the development cohort. Ten independent prognostic factors were incorporated into the prediction function (Pmodel < 0.001). The model had excellent discrimination for CVD risk [AUC 0.94; (95% CI:0.93–0.96)] (Figure 2) and included the following variables: male sex (P < 0.001), African-American ethnicity (P = 0.023), current age (P = 0.020), age at HIV diagnosis (P = 0.006), peak HIV viral load (P = 0.012), nadir CD4 lymphocyte count (P < 0.001), hypertension (P < 0.001), hyperlipidemia (P = 0.001), diabetes (P < 0.001), and chronic kidney disease (P < 0.001). Scoring system and score sheets of risk estimates were developed to predict CV events in a 10-year follow-up period (Figures 3 and 4). The 10-parameter multiple logistic regression model also had excellent discrimination [AUC 0.96; (95% CI: 0.89–0.99)] when applied to the validation cohort. Conclusion We developed and validated a risk-scoring system based on 10 clinical factors that accurately predict the 10-year risk for CV events in an HIV-infected population. This assessment tool may provide clinicians with a rapid assessment of cardiovascular disease risk among HIV-infected patients and inform prevention measures during the era of effective antiretroviral therapy. Disclosures All Authors: No reported Disclosures.

scholarly journals Risk Scoring System of Mortality and Prediction Model of Hospital Stay for Critically Ill Patients Receiving Parenteral Nutrition

Healthcare ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 853
Author(s):  
Jee-Yun Kim ◽  
Jeong Yee ◽  
Tae-Im Park ◽  
So-Youn Shin ◽  
Man-Ho Ha ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Linear Regression ◽  
Parenteral Nutrition ◽  
Prediction Model ◽  
Scoring System ◽  
Prediction Equation ◽  
Icu Patients ◽  
Risk Scoring ◽  
Risk Scoring System

Predicting the clinical progression of intensive care unit (ICU) patients is crucial for survival and prognosis. Therefore, this retrospective study aimed to develop the risk scoring system of mortality and the prediction model of ICU length of stay (LOS) among patients admitted to the ICU. Data from ICU patients aged at least 18 years who received parenteral nutrition support for ≥50% of the daily calorie requirement from February 2014 to January 2018 were collected. In-hospital mortality and log-transformed LOS were analyzed by logistic regression and linear regression, respectively. For calculating risk scores, each coefficient was obtained based on regression model. Of 445 patients, 97 patients died in the ICU; the observed mortality rate was 21.8%. Using logistic regression analysis, APACHE II score (15–29: 1 point, 30 or higher: 2 points), qSOFA score ≥ 2 (2 points), serum albumin level < 3.4 g/dL (1 point), and infectious or respiratory disease (1 point) were incorporated into risk scoring system for mortality; patients with 0, 1, 2–4, and 5–6 points had approximately 10%, 20%, 40%, and 65% risk of death. For LOS, linear regression analysis showed the following prediction equation: log(LOS) = 0.01 × (APACHE II) + 0.04 × (total bilirubin) − 0.09 × (admission diagnosis of gastrointestinal disease or injury, poisoning, or other external cause) + 0.970. Our study provides the mortality risk score and LOS prediction equation. It could help clinicians to identify those at risk and optimize ICU management.

scholarly journals Development and Validation of a Risk Scoring System for Cephamycin-Associated Hemorrhagic Events

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Tong-Ling Chien ◽  
Fei-Yuan Hsiao ◽  
Li-Ju Chen ◽  
Yu-Wen Wen ◽  
Shu-Wen Lin
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Scoring System ◽  
Goodness Of Fit ◽  
Bleeding Tendency ◽  
Multivariate Logistic Regression ◽  
Goodness Of Fit Test ◽  
Hemorrhagic Events ◽  
Risk Scoring ◽  
Risk Scoring System

Abstract Cephamycin-associated hemorrhages have been reported since their launch. This research aimed to determine risk factors for cephamycin-associated hemorrhagic events and produce a risk scoring system using National Taiwan University Hospital (NTUH) database. Patients who were older than 20 years old and consecutively used study antibiotics for more than 48 hours (epidode) at NTUH between January 1st, 2009 and December 31st, 2015 were included. The population was divided into two cohorts for evaluation of risk factors and validation of the scoring system. Multivariate logistic regression was used for the assessment of the adjusted association between factors and the outcome of interest. Results of the multivariate logistic regression were treated as the foundation to develop the risk scoring system. There were 46402 and 22681 episodes identified in 2009–2013 and 2014–2015 cohorts with 356 and 204 hemorrhagic events among respective cohorts. Use of cephamycins was associated with a higher risk for hemorrhagic outcomes (aOR 2.03, 95% CI 1.60–2.58). Other risk factors included chronic hepatic disease, at least 65 years old, prominent bleeding tendency, and bleeding history. A nine-score risk scoring system (AUROC = 0.8035, 95% CI 0.7794–0.8275; Hosmer-Lemeshow goodness-of-fit test p = 0.1044) was developed based on the identified risk factors, with higher scores indicating higher risk for bleeding. Use of cephamycins was associated with more hemorrhagic events compared with commonly used penicillins and cephalosporins. The established scoring system, CHABB, may help pharmacists identify high-risk patients and provide recommendations according to the predictive risk, and eventually enhance the overall quality of care.

scholarly journals Development and Validation of a Risk Scoring System for Severe Acute Lower Gastrointestinal Bleeding

2016 ◽  
Vol 14 (11) ◽  
pp. 1562-1570.e2 ◽  
Author(s):  
Tomonori Aoki ◽  
Naoyoshi Nagata ◽  
Takuro Shimbo ◽  
Ryota Niikura ◽  
Toshiyuki Sakurai ◽  
...  
Keyword(s):  
Gastrointestinal Bleeding ◽  
Scoring System ◽  
Lower Gastrointestinal Bleeding ◽  
Risk Scoring ◽  
Development And Validation ◽  
Risk Scoring System

scholarly journals Development and Validation of a New Risk Scoring System for Cancer Patients with Suspected Infection

2021 ◽  
Author(s):  
Bora Chae ◽  
Seonok Kim ◽  
Yoon-Seon Lee
Keyword(s):  
Cancer Patients ◽  
Scoring System ◽  
Validation Cohort ◽  
Performance Status ◽  
Eastern Cooperative Oncology Group ◽  
Peripheral Oxygen Saturation ◽  
Suspected Infection ◽  
Risk Scoring ◽  
Risk Scoring System ◽  
New Scoring

Abstract Purpose: This study aimed to develop a new prognostic model for predicting 30-day mortality in cancer patients with suspected infection.Methods: This study is a retrospective cohort study and was conducted from August 2019 to December 2019 at a single center. Adult active cancer patients with suspected infection were enrolled among visitors to the emergency room (ER). Logistic regression analysis was used to identify potential predictors for a new model. Results: A total of 899 patients were included; 450 in the development cohort and 449 in the validation cohort. Six independent variables predicted 30-day mortality: Eastern Cooperative Oncology Group (ECOG) performance status (PS), peripheral oxygen saturation (SpO2), creatinine, bilirubin, C-reactive protein (CRP), and lactate. The C-statistic of the new scoring system was 0.799 in the development cohort and 0.793 in the validation cohort. The C-statistics in the development cohort was significantly higher than those of SOFA [0.723 (95% CI: 0.663–0.783)], qSOFA [0.596 (95% CI: 0.537–0.655)], and SIRS [0.547 (95% CI: 0.483–0.612)]. Conclusions: The discriminative capability of the new cancer-specific risk scoring system was good in cancer patients with suspected infection. The new scoring system was superior to SOFA, qSOFA, and SIRS in predicting mortality.

69 Development and Validation of a Stent Thrombosis Risk Scoring System

Heart ◽  
2014 ◽  
Vol 100 (Suppl 3) ◽  
pp. A39-A40 ◽  
Author(s):  
Nikesh Malik ◽  
Amerjeet Banning ◽  
Anthony Gershlick
Keyword(s):  
Stent Thrombosis ◽  
Scoring System ◽  
Thrombosis Risk ◽  
Risk Scoring ◽  
Development And Validation ◽  
Risk Scoring System

scholarly journals Factors Associated With Outcomes of Patients With Primary Sclerosing Cholangitis and Development and Validation of a Risk Scoring System

Hepatology ◽  
2019 ◽  
Vol 69 (5) ◽  
pp. 2120-2135 ◽  
Author(s):  
Elizabeth C. Goode ◽  
Allan B. Clark ◽  
George F. Mells ◽  
Brijesh Srivastava ◽  
Kelly Spiess ◽  
...  
Keyword(s):  
Primary Sclerosing Cholangitis ◽  
Scoring System ◽  
Sclerosing Cholangitis ◽  
Factors Associated ◽  
Risk Scoring ◽  
Development And Validation ◽  
Risk Scoring System

scholarly journals Development And Validation of a Risk Scoring System to Predict Pneumothorax in CT-Guided Percutaneous Transthoracic Needle Biopsy

2021 ◽  
Author(s):  
Qiuhong Yang ◽  
Lin cheng Luo ◽  
Xinyi Peng ◽  
Hailong Wei ◽  
Qun Yi ◽  
...  
Keyword(s):  
Scoring System ◽  
Validation Cohort ◽  
Transthoracic Needle Biopsy ◽  
Ct Guided ◽  
Score System ◽  
Derivation Cohort ◽  
Risk Scoring ◽  
Risk Score System ◽  
Risk Scoring System ◽  
Percutaneous Transthoracic Needle Biopsy

Abstract Objective: To develop and validate a risk scoring system using variables easily obtained for the prediction of pneumothorax in CT-guided percutaneous transthoracic needle biopsy (PTNB).Methods: The derivation cohort was comprised of 1001 patients who underwent CT-guided PTNB. Multivariate logistic regression was used to identify risk factors for pneumothorax, which were treated as the foundation to develop the risk scoring system. To validate the system, a validation cohort group of 230 patients was enrolled.Results: Age, puncture times, puncture depth, smoking index, number of specimens, bleeding from the needle path, and lobular lesion were identified as risk factors in the derivation cohort. A risk scoring system (Hosmer-Lemeshow goodness-of-fit test p =0.33) was developed. The area under the receiver operating characteristic curve (AUROC) was 0.601 by using the risk score system. This risk score system demonstrated a better diagnostic effect with increasing age. In the group of patients older than 80 years, the AUROC was 0.76, showing good predictive power. This risk scoring system was confirmed in the validation cohort with an AUROC of 0.736.Conclusion: This scoring system has a good predictive effect in both derivation and validation cohort.

Sign in / Sign up

Export Citation Format

Share Document