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http://dx.doi.org/10.29220/CSAM.2021.28.4.339

Identification of risk factors and development of the nomogram for delirium  

Shin, Min-Seok (Department of Statistics, Yeungnam University)
Jang, Ji-Eun (Department of Statistics, Yeungnam University)
Lee, Jea-Young (Department of Statistics, Yeungnam University)
Publication Information
Communications for Statistical Applications and Methods / v.28, no.4, 2021 , pp. 339-350 More about this Journal
Abstract
In medical research, the risk factors associated with human diseases need to be identified to predict the incidence rate and determine the treatment plan. Logistic regression analysis is primarily used in order to select risk factors. However, individuals who are unfamiliar with statistics outcomes have trouble using these methods. In this study, we develop a nomogram that graphically represents the numerical association between the disease and risk factors in order to identify the risk factors for delirium and to interpret and use the results more effectively. By using the logistic regression model, we identify risk factors related to delirium, construct a nomogram and predict incidence rates. Additionally, we verify the developed nomogram using a receiver operation characteristics (ROC) curve and calibration plot. Nursing home, stroke/epilepsy, metabolic abnormality, hemodynamic instability, and analgesics were selected as risk factors. The validation results of the nomogram, built with the factors of training set and the test set of the AUC showed a statistically significant determination of 0.893 and 0.717, respectively. As a result of drawing the calibration plot, the coefficient of determination was 0.820. By using the nomogram developed in this paper, health professionals can easily predict the incidence rate of delirium for individual patients. Based on this information, the nomogram could be used as a useful tool to establish an individual's treatment plan.
Keywords
delirium; incidence rate; logistic regression analysis; nomogram; risk factor;
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  • Reference
1 Ahn JH (2013). Nomogram for Prediction of Prostate Cancer in Korean Men with Serum ProstateSpecific Antigen Less Than 10ng/mL, Busan University, Busan.
2 Arend E and Christensen M (2009). Delirium in the intensive care unit: A review, British association of critical care nurses, Nursing in Critical Care, 14, 145-154.   DOI
3 D'Agostino RB, Grundy S, Sullivan LM, and Wilson P (2001). Validation of the Framingham coronary heart disease prediction scores, Journal of the American Medical Association, 286, 180-187.   DOI
4 Dubois M, Strobik Y, Bergeron N, Dumont M, and Dial S (2001). Delirium in an intensive care unit: A study of risk factors, Intensive Care Medicine, 27, 1297-1304.   DOI
5 Heo MH and Lee YG (2008). Data-Mining Modeling and Example, Hannarae, Seoul.
6 Iasonos A, Schrag D, Raj GV, and Panageas KS (2008). How to build and interpret a nomogram for cancer prognosis, Journal of Clinical Oncology, 26, 1364--1370.   DOI
7 Inouye S (1994). The dilemma of delirium: Clinical and research controversies regarding diagnosis and evaluation of delirium in hospitalized elderly medical patients, The American Journal of Medicine, 97, 278-288.   DOI
8 Inouye S, Schlesinger M, and Lyndon T (1999). Delirium: A symptom of how hospital care is failing older persons and a window to improve quality of hospital care, The American Journal of Medicine,106, 565-573.   DOI
9 Jang JE (2017). Identification of Risk Factors and Development of the Nomogram for Delirium(Master's thesis), Yeungnam University, Gyeongsan.
10 Jun HJ (2015). Establishment of a Nomogram to Predict the Prognosis of Metastatic or Recurrent Gastric Cancer Patients, Yonsei University, Seoul.
11 Lee SC (2015). Development and Validation of Web-Based Nomogram to Predict Postoperative Invasive Component in Ductal Carcinoma in Situ at Core Needle Breast Biopsy, Dankook University, Seoul.
12 Cole M and Primeau F (1993). Prognosis of delirium in elderly hospital patients, Canadian Medical Association Journal, 149, 41-46.
13 Kim SH, Shin K, Kim HY, Cho YJ, Noh JK, Suh JS, and Yang WI (2014). Postoperative nomogram to predict the probability of metastasis in Enneking stage IIB extremity osteosarcoma, The BioMed Central Cancer, 12, 666.
14 Lee JW, Park MR, and Yu HN (2005). Statistical Method for Bioscience Research, Freedom Academy, Seoul.
15 Nam BH and D'Agostino RB (2002). Discrimination Index, the Area Under the ROC Curve, Goodnessof-Fit Tests and Model Validity, Birkhauser, Boston.
16 Qiu SQ et al. (2016). A nomogram to predict the probability of axillary lymph node metastasis in early breast cancer patients with positive axillary ultrasound. Scientific Reports, 6.
17 Skrobik Y, Ouimet S, and Kavanagh BP (2007). Incidence, risk factor and consequences of icu delirium. Intensive Care Med, 33, 66-73.   DOI
18 Vuk M and Curk T (2006). ROC curve, lift chart and calibration plot, Metodoloski Zvezki, 3, 89-108.
19 Yang D (2014). Build prognostic nomograms for risk assessment using sas. In Proceedings of SAS Global Forum 2013, 264--2013.
20 Kwak KH, Do BS, Park SY, and Lee SB (2011). Original articles: risk factors for delirium in elderly patients visiting an emergency department, Journal of the Korean Society of Emergency Medicine, 22, 489-493.
21 Kang HC, Han ST, Choi JH, Lee SG, Kim ES, and Eom IH (2014). Data-Mining Methodology for Big Data Analysis, Freedom academy, Seoul.
22 Lee KM, Kim WJ, and Yun SJ (2009). A clinical nomogram construction method using genetic algorithm and naive bayesian technique, Journal of Korean Institute of Intelligent Systems, 19, 769-801.