Predicting Outcomes in Emergency Medical Admissions Using a Laboratory Only Nomogram
المؤلفون المشاركون
Cournane, Seán
Conway, Richard
Byrne, Declan
O’Riordan, Deirdre
Silke, Bernard
المصدر
Computational and Mathematical Methods in Medicine
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-8، 8ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-11-14
دولة النشر
مصر
عدد الصفحات
8
التخصصات الرئيسية
الملخص EN
Background.
We describe a nomogram to explain an Acute Illness Severity model, derived from emergency room triage and admission laboratory data, to predict 30-day in-hospital survival following an emergency medical admission.
Methods.
For emergency medical admissions (96,305 episodes in 50,612 patients) between 2002 and 2016, the relationship between 30-day in-hospital mortality and admission laboratory data was determined using logistic regression.
The previously validated Acute Illness Severity model was then transposed to a Kattan-style nomogram with a Stata user-written program.
Results.
The Acute Illness Severity was based on the admission Manchester triage category and biochemical laboratory score; these latter were based on the serum albumin, sodium, potassium, urea, red cell distribution width, and troponin status.
The laboratory admission data was predictive with an AUROC of 0.85 (95% CI: 0.85, 0.86).
The sensitivity was 94.4%, with a specificity of 62.7%.
The positive predictive value was 21.2%, with a negative predictive value of 99.1%.
For the Kattan-style nomogram, the regression coefficients are converted to a 100-point scale with the predictor parameters mapped to a probability axis.
The nomogram would be an easy-to-use tool at the bedside and for educational purposes, illustrating the relative importance of the contribution of each predictor to the overall score.
Conclusion.
A nomogram to illustrate and explain the prognostic factors underlying an Acute Illness Severity Score system is described.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Cournane, Seán& Conway, Richard& Byrne, Declan& O’Riordan, Deirdre& Silke, Bernard. 2017. Predicting Outcomes in Emergency Medical Admissions Using a Laboratory Only Nomogram. Computational and Mathematical Methods in Medicine،Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1142175
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Cournane, Seán…[et al.]. Predicting Outcomes in Emergency Medical Admissions Using a Laboratory Only Nomogram. Computational and Mathematical Methods in Medicine No. 2017 (2017), pp.1-8.
https://search.emarefa.net/detail/BIM-1142175
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Cournane, Seán& Conway, Richard& Byrne, Declan& O’Riordan, Deirdre& Silke, Bernard. Predicting Outcomes in Emergency Medical Admissions Using a Laboratory Only Nomogram. Computational and Mathematical Methods in Medicine. 2017. Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1142175
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1142175
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر