A Risk Score for Predicting the Incidence of Hemorrhage in Critically Ill Neonates: Development and Validation Study

2020 ◽  
Author(s):  
Rozeta Sokou ◽  
Daniele Piovani ◽  
Aikaterini Konstantinidi ◽  
Andreas G. Tsantes ◽  
Stavroula Parastatidou ◽  
...  
Keyword(s):  
Prediction Model ◽  
Critically Ill ◽  
Risk Score ◽  
External Validation ◽  
Prognostic Index ◽  
Bleeding Risk ◽  
Outcome Variable ◽  
Calibration Plot ◽  
Characteristic Analysis ◽  
Critically Ill Neonates

AbstractThe aim of the study was to develop and validate a prediction model for hemorrhage in critically ill neonates which combines rotational thromboelastometry (ROTEM) parameters and clinical variables. This cohort study included 332 consecutive full-term and preterm critically ill neonates. We performed ROTEM and used the neonatal bleeding assessment tool (NeoBAT) to record bleeding events. We fitted double selection least absolute shrinkage and selection operator logit regression to build our prediction model. Bleeding within 24 hours of the ROTEM testing was the outcome variable, while patient characteristics, biochemical, hematological, and thromboelastometry parameters were the candidate predictors of bleeding. We used both cross-validation and bootstrap as internal validation techniques. Then, we built a prognostic index of bleeding by converting the coefficients from the final multivariable model of relevant prognostic variables into a risk score. A receiver operating characteristic analysis was used to calculate the area under curve (AUC) of our prediction index. EXTEM A10 and LI60, platelet counts, and creatinine levels were identified as the most robust predictors of bleeding and included them into a Neonatal Bleeding Risk (NeoBRis) index. The NeoBRis index demonstrated excellent model performance with an AUC of 0.908 (95% confidence interval [CI]: 0.870–0.946). Calibration plot displayed optimal calibration and discrimination of the index, while bootstrap resampling ensured internal validity by showing an AUC of 0.907 (95% CI: 0.868–0.947). We developed and internally validated an easy-to-apply prediction model of hemorrhage in critically ill neonates. After external validation, this model will enable clinicians to quantify the 24-hour bleeding risk.

The role of ROTEM variables based on clot elasticity and platelet component in predicting bleeding risk in thrombocytopenic critically ill neonates

2020 ◽  
Author(s):  
Stavroula Parastatidou ◽  
Rozeta Sokou ◽  
Andreas G Tsantes ◽  
Aikaterini Konstantinidi ◽  
Maria Lampridou ◽  
...  
Keyword(s):  
Critically Ill ◽  
Bleeding Risk ◽  
Critically Ill Neonates

scholarly journals External Validation of Model-Based Dosing Guidelines for Vancomycin, Gentamicin, and Tobramycin in Critically Ill Neonates and Children: A Pragmatic Two-Center Study

2020 ◽  
Vol 22 (4) ◽  
pp. 433-444 ◽  
Author(s):  
Stan J. F. Hartman ◽  
Lynn B. Orriëns ◽  
Samanta M. Zwaag ◽  
Tim Poel ◽  
Marika de Hoop ◽  
...  
Keyword(s):  
Critically Ill ◽  
External Validation ◽  
Model Based ◽  
Critically Ill Neonates ◽  
Center Study

A comprehensive prognostic index for patients with CLL.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 7015-7015
Author(s):  
Natali Pflug ◽  
Jasmin Bahlo ◽  
Tait D. Shanafelt ◽  
Barbara Eichhorst ◽  
Manuela Bergmann ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Mayo Clinic ◽  
External Validation ◽  
Prognostic Index ◽  
Observation Time ◽  
Clinical Staging ◽  
Newly Diagnosed ◽  
C Statistic ◽  
Very High

7015 Background: Besides clinical staging, a number of biomarkers predicting OS in CLL have been identified. The multiplicity of markers, limited information on their independent value, and a lack of understanding of how to interpret discordant markers are major barriers to use in routine clinical practice. We developed an integrated prognostic index using the database of the German CLL Study Group (GCLLSG), which was subsequently validated in a cohort of untreated CLL patients (pts) from the Mayo Clinic. Methods: The analysis was based on a dataset collected between 1997 and 2006 in 3 GCLLSG phase III trials. The external validation was performed on a series of newly diagnosed CLL pts managed at Mayo Clinic. Results: The GCLLSG dataset (1,948 physically fit pts at early and advanced stage; median age: 60 yr (range 30-81); median observation time 63.4 mo) was used as a training dataset. 7 parameters were identified as independent predictors for OS: sex, age, ECOG status, del 17p, del 11q, IGHV mutation status, thymidine kinase and β2-microglobulin. By using a weighted grading a prognostic index was derived separating four different pts groups: low risk (score 0 - 2), intermediate risk (score 3-5), high risk (score 6-10) and very high risk (score 11-14) with significant different OS rates (95.2%, 86.9%, 67.7% and 18.7% OS after 5 yr for the low, intermediate, high and very high risk group respectively (p<0.001). This prognostic index was validated in a cohort of 676 newly diagnosed, untreated pts from the Mayo Clinic (median age 61.5 yr (range 32 - 89); median observation time 47.0 mo). The 4 risk groups were reproduced with 98.3%, 95.4%, 75.4% and 10.8% OS after 5 yr. The prognostic index predicts OS independent of Rai/Binet stage and provides accurate estimations regarding time to first treatment (TTF). C-statistic is 0.75. Conclusions: Using a multi-step process including external validation, we developed a comprehensive prognostic index combining clinical, serum, and molecular information into a single risk score for pts with untreated CLL. The prognostic index provides more accurate prediction of both TTF and OS. To our knowledge it is the first prognostic model in CLL to reach the C-statistic threshold (c > 0.70) necessary to have utility at the level of the individual.

scholarly journals Predicting major bleeding in patients with noncardioembolic stroke on antiplatelets

Neurology ◽  
2017 ◽  
Vol 89 (9) ◽  
pp. 936-943 ◽  
Author(s):  
Nina A. Hilkens ◽  
Ale Algra ◽  
Hans-Christoph Diener ◽  
Johannes B. Reitsma ◽  
Philip M. Bath ◽  
...  
Keyword(s):  
Risk Factors ◽  
Ischemic Stroke ◽  
Prediction Model ◽  
Major Bleeding ◽  
Randomized Clinical Trials ◽  
Cox Regression ◽  
External Validation ◽  
Antiplatelet Agents ◽  
Bleeding Risk ◽  
Asian Ethnicity

Objective:To develop and externally validate a prediction model for major bleeding in patients with a TIA or ischemic stroke on antiplatelet agents.Methods:We combined individual patient data from 6 randomized clinical trials (CAPRIE, ESPS-2, MATCH, CHARISMA, ESPRIT, and PRoFESS) investigating antiplatelet therapy after TIA or ischemic stroke. Cox regression analyses stratified by trial were performed to study the association between predictors and major bleeding. A risk prediction model was derived and validated in the PERFORM trial. Performance was assessed with the c statistic and calibration plots.Results:Major bleeding occurred in 1,530 of the 43,112 patients during 94,833 person-years of follow-up. The observed 3-year risk of major bleeding was 4.6% (95% confidence interval [CI] 4.4%–4.9%). Predictors were male sex, smoking, type of antiplatelet agents (aspirin-clopidogrel), outcome on modified Rankin Scale ≥3, prior stroke, high blood pressure, lower body mass index, elderly, Asian ethnicity, and diabetes (S2TOP-BLEED). The S2TOP-BLEED score had a c statistic of 0.63 (95% CI 0.60–0.64) and showed good calibration in the development data. Major bleeding risk ranged from 2% in patients aged 45–54 years without additional risk factors to more than 10% in patients aged 75–84 years with multiple risk factors. In external validation, the model had a c statistic of 0.61 (95% CI 0.59–0.63) and slightly underestimated major bleeding risk.Conclusions:The S2TOP-BLEED score can be used to estimate 3-year major bleeding risk in patients with a TIA or ischemic stroke who use antiplatelet agents, based on readily available characteristics. The discriminatory performance may be improved by identifying stronger predictors of major bleeding.

scholarly journals Bleeding risk prediction in elderly patients managed invasively for Acute Coronary Syndromes: external validation of the PRECISE-DAPT and PARIS risk scores

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
C Montalto ◽  
G Crimi ◽  
N Morici ◽  
L Piatti ◽  
D Grosseto ◽  
...  
Keyword(s):  
High Risk ◽  
Elderly Patients ◽  
Risk Score ◽  
External Validation ◽  
Bleeding Risk ◽  
Risk Scores ◽  
Risk Category ◽  
Net Benefit ◽  
Discrimination Power ◽  
Risk Categories

Abstract Background Tailoring Dual Antiplatelet Therapy (DAPT) to each patient bleeding and ischemic risk profile is a majopr challenge in everyday clinical practice. As the elderlies were underrepresented in validation cohorts of bleeding risk scores, their generalizability in this context is uncertain. Purpose We sought to assess the clinical utility of the PRECISE-DAPT and PARIS bleeding risk scores to elderly patients suffering from ACS and undergoing invasive management. Methods Our external validation cohort included 1,883 patients older &gt;74 years admitted for ACS and treated with PCI from 3 multicenter, randomized trials. Bleeding risk scores were calculated on a patient-level and subjects were stratified into risk categories according to each risk score definition. Results After a median follow-up of 365 days, patients in the high-risk categories according to the PRECISE-DAPT score experienced a higher rate of BARC 3–5 bleedings (log rank p=0.002) while this was not observed for those in the high-risk category according to the PARIS risk score (log rank p=0.3). Both scores had a moderate discriminative power (c-statistics 0.70 and 0.64, respectively) and calibration was accurate for both risk scores (all χ2&gt;0.05), but PARIS risk score was associated to a greater overestimation of the risk (mean D observed-predicted probability = −0.65 for PRECISE DAPT and −4.62 for PARIS, p=0.02; Figure 1). Decision curve analysis was in favor of the PRECISE-DAPT score up to a risk threshold of 2%. A sensitivity showed that calibration and discrimination power was moderate for both risk scores also after including BARC 2 events. Conclusion In the setting of older adults managed invasively for ACS both the PARIS and the PRECISE-DAPT scores were moderately accurate in predicting bleeding risk. However, the use of the PRECISE-DAPT is associated with better performance and a higher net benefit. Figure 1 Funding Acknowledgement Type of funding source: None

Estimating Bleeding Risk in Patients with Cancer-Associated Thrombosis: Evaluation of Existing Risk Scores and Development of a New Risk Score

2021 ◽  
Author(s):  
Maria A. de Winter ◽  
Jannick A. N. Dorresteijn ◽  
Walter Ageno ◽  
Cihan Ay ◽  
Jan Beyer-Westendorf ◽  
...  
Keyword(s):  
Prediction Model ◽  
External Validation ◽  
Predictive Performance ◽  
Bleeding Risk ◽  
Risk Scores ◽  
Cancer Type ◽  
Clinical Predictors ◽  
Internal Validation ◽  
Patients With Cancer ◽  
Cancer Associated Thrombosis

Abstract Background Bleeding risk is highly relevant for treatment decisions in cancer-associated thrombosis (CAT). Several risk scores exist, but have never been validated in patients with CAT and are not recommended for practice. Objectives To compare methods of estimating clinically relevant (major and clinically relevant nonmajor) bleeding risk in patients with CAT: (1) existing risk scores for bleeding in venous thromboembolism, (2) pragmatic classification based on cancer type, and (3) new prediction model. Methods In a posthoc analysis of the Hokusai VTE Cancer study, a randomized trial comparing edoxaban with dalteparin for treatment of CAT, seven bleeding risk scores were externally validated (ACCP-VTE, HAS-BLED, Hokusai, Kuijer, Martinez, RIETE, and VTE-BLEED). The predictive performance of these scores was compared with a pragmatic classification based on cancer type (gastrointestinal; genitourinary; other) and a newly derived competing risk-adjusted prediction model based on clinical predictors for clinically relevant bleeding within 6 months after CAT diagnosis with nonbleeding-related mortality as the competing event (“CAT-BLEED”). Results Data of 1,046 patients (149 events) were analyzed. Predictive performance of existing risk scores was poor to moderate (C-statistics: 0.50–0.57; poor calibration). Internal validation of the pragmatic classification and “CAT-BLEED” showed moderate performance (respective C-statistics: 0.61; 95% confidence interval [CI]: 0.56–0.66, and 0.63; 95% CI 0.58–0.68; good calibration). Conclusion Existing risk scores for bleeding perform poorly after CAT. Pragmatic classification based on cancer type provides marginally better estimates of clinically relevant bleeding risk. Further improvement may be achieved with “CAT-BLEED,” but this requires external validation in practice-based settings and with other DOACs and its clinical usefulness is yet to be demonstrated.

Development and external validation of a post-discharge bleeding risk score in patients with acute coronary syndrome: The BleeMACS score

2018 ◽  
Vol 254 ◽  
pp. 10-15 ◽  
Author(s):  
Sergio Raposeiras-Roubín ◽  
Jonas Faxén ◽  
Andrés Íñiguez-Romo ◽  
Jose Paulo Simao Henriques ◽  
Fabrizio D'Ascenzo ◽  
...  
Keyword(s):  
Acute Coronary Syndrome ◽  
Risk Score ◽  
External Validation ◽  
Bleeding Risk ◽  
Post Discharge ◽  
Coronary Syndrome
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