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Clinical Risk Score (clinical + risk_score)

Distribution by Scientific Domains
Medical Sciences100%

Selected Abstracts

A Clinical Risk Score to Predict the Time to First Appropriate Device Therapy in Recipients of Implantable Cardioverter Defibrillators

PACING AND CLINICAL ELECTROPHYSIOLOGY, Issue 3 2007
HAITHAM HREYBE M.D.
Background:To develop a risk score to predict the occurrence of appropriate defibrillator [implantable cardioverter-defibrillator (ICD)] therapies. A simple clinical score predicting the risk of appropriate ICD therapy is lacking. Methods:A Cox regression model was developed from a database of ICD patients at a single tertiary center to predict the time to appropriate ICD therapy defined as shock or antitachycardia pacing. A risk score was derived from this model using half of the database and was validated using the other half. Results:A total of 399 patients were entered into the database between July 2001 and February 2004. There were no statistically significant differences between the derivation (n = 200) and validation (n = 199) groups in any of the demographic or clinical variables recorded. The risk score included three independent variables: indication for ICD implantation (P = 0.03), serum creatinine level (P = 0.015), and QRS width (P = 0.028). The observed risk scores were highly predictive of time to ICD therapy in the validation group (P = 0.02). Conclusion:We describe a new clinical risk score that predicts the time to appropriate device therapy in ICD recipients of a single tertiary center hospital. The performance of this risk score needs to be investigated prospectively in a larger patient population. [source]

A Screening test for the prediction of Dravet syndrome before one year of age

EPILEPSIA, Issue 4 2008
Junri Hattori
Summary Purpose: Our aim was to develop a screening test to predict Dravet syndrome before the first birthday based on the clinical characteristics of infants and the SCN1A mutation analysis. Methods: Ninety-six patients who experienced febrile seizures before the age of one were enrolled. The patients were divided into two groups,the Dravet syndrome group (n = 46) and the non-Dravet syndrome group (n = 50). We compared the clinical characteristics before one year of age of the two groups. We analyzed all coding exons of the SCN1A gene by the direct sequencing method. Scores from 0 to 3 were assigned to each risk factor based on the odds ratio and p-value. Results: An age of onset of febrile seizure , 7 months, a total number of seizures , 5, and prolonged seizures lasting more than 10 min. were regarded as significant risk factors for Dravet syndrome. Other factors highly predictive of this syndrome were hemiconvulsions, partial seizures, myoclonic seizures, and hot water,induced seizures. A total clinical score of six or above was the cutoff value indicating a high risk of Dravet syndrome. SCN1A missense and truncated mutations were detected significantly more often in the Dravet syndrome group than in the non-Dravet syndrome group. Discussion: This simple screening test was designed to be used by general pediatricians. It could help to predict Dravet syndrome before one year of age. If the sum of the clinical risk score is , 6, then the performance of an SCN1A mutation analysis is recommended. [source]

A Clinical Risk Score to Predict the Time to First Appropriate Device Therapy in Recipients of Implantable Cardioverter Defibrillators

PACING AND CLINICAL ELECTROPHYSIOLOGY, Issue 3 2007
HAITHAM HREYBE M.D.
Background:To develop a risk score to predict the occurrence of appropriate defibrillator [implantable cardioverter-defibrillator (ICD)] therapies. A simple clinical score predicting the risk of appropriate ICD therapy is lacking. Methods:A Cox regression model was developed from a database of ICD patients at a single tertiary center to predict the time to appropriate ICD therapy defined as shock or antitachycardia pacing. A risk score was derived from this model using half of the database and was validated using the other half. Results:A total of 399 patients were entered into the database between July 2001 and February 2004. There were no statistically significant differences between the derivation (n = 200) and validation (n = 199) groups in any of the demographic or clinical variables recorded. The risk score included three independent variables: indication for ICD implantation (P = 0.03), serum creatinine level (P = 0.015), and QRS width (P = 0.028). The observed risk scores were highly predictive of time to ICD therapy in the validation group (P = 0.02). Conclusion:We describe a new clinical risk score that predicts the time to appropriate device therapy in ICD recipients of a single tertiary center hospital. The performance of this risk score needs to be investigated prospectively in a larger patient population. [source]

Evaluation of Risk Score Algorithms for Detection of Chlamydial and Gonococcal Infections in an Emergency Department Setting

ACADEMIC EMERGENCY MEDICINE, Issue 2 2008
Alia A. Al-Tayyib PhD
Abstract Objectives:, To develop and evaluate screening algorithms to predict current chlamydial and gonococcal infections in emergency department (ED) settings and assess their performance. Methods:, Between 2002 and 2005, adult patients aged 18 to 35 years attending an urban ED were screened for Chlamydia trachomatis (Ct) and Neisseria gonorrhoeae (GC) and completed a brief demographic and behavioral questionnaire. Using multiple unconditional logistic regressions, the authors developed four separate predictive models and applicable clinical risk scores to screen for infection. They developed models for females and males separately, for Ct and GC infections combined, and for Ct infection alone. The sensitivities and specificities of the clinical risk scores at different cutoffs were used to examine performance of the algorithms. Results:, Among 5,537 patients successfully screened for Ct and GC, the overall prevalence of infection was 9.6%. Age was the strongest predictor of infection. Adjusting for other predictors, the prevalence odds ratio (POR) was 2.2 (95% confidence interval [CI] = 1.7 to 2.8) for Ct and GC combined and 2.9 (95% CI = 2.1 to 4.1) for Ct alone comparing females 25 years and younger to females older than 25 years. Among males, the association was stronger with an adjusted POR of 3.3 (95% CI = 2.3 to 4.7) for Ct and GC combined and 3.2 (95% CI = 2.1 to 4.7) for Ct infection alone. Conclusions:, If the decision to incorporate Ct and GC screening into routine ED care is made, age alone appears to be a sufficient screening criterion. [source]