Development and validation of a risk-prediction nomogram for patients with ureteral calculi associated with urosepsis: A retrospective analysis

Autor: Li-xian Guan, Xuejiang Cui, Weilie Hu, Quan-yao Feng, Xun Xu, Zhan-ying Zhang, Xintai Zhong, Ming Hu, Yiheng Huang
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Male
Physiology
030232 urology & nephrology
lcsh:Medicine
Urine
Logistic regression
urologic and male genital diseases
Pathology and Laboratory Medicine
Diagnostic Radiology
0302 clinical medicine
Mathematical and Statistical Techniques
Risk Factors
Medicine and Health Sciences
Medicine
lcsh:Science
Tomography
Multidisciplinary
Radiology and Imaging
Middle Aged
female genital diseases and pregnancy complications
Systemic Inflammatory Response Syndrome
Body Fluids
Chemistry
030220 oncology & carcinogenesis
Predictive value of tests
Physical Sciences
Female
Radiology
Anatomy
Statistics (Mathematics)
Research Article
Adult
medicine.medical_specialty
Ureteral Calculi
Imaging Techniques
Concordance
Neuroimaging
Research and Analysis Methods
Models
Biological
03 medical and health sciences
Signs and Symptoms
Sex Factors
Diagnostic Medicine
Predictive Value of Tests
Sepsis
Linear regression
Humans
Statistical Methods
Nitrites
Retrospective Studies
Receiver operating characteristic
business.industry
lcsh:R
Univariate
Chemical Compounds
Biology and Life Sciences
Retrospective cohort study
Kidneys
Renal System
Nomogram
Computed Axial Tomography
Nomograms
lcsh:Q
business
Tomography
X-Ray Computed
Mathematics
Forecasting
Neuroscience
Zdroj: PLoS ONE
PLoS ONE, Vol 13, Iss 8, p e0201515 (2018)
ISSN: 1932-6203
Popis: Objectives To develop and validate an individualized nomogram to predict probability of patients with ureteral calculi developing into urosepsis. Methods The clinical data of 747 patients with ureteral calculi who were admitted from June 2013 to December 2015 in Affiliated Nanhai Hospital of Southern Medical University were selected and included in the development group, while 317 ureteral calculi patients who were admitted from January 2016 to December 2016 were included in the validation group. The independent risk factors of ureteral calculi associated with urosepsis were screened using univariate and multivariate logistic regression analyses. The corresponding nomogram prediction model was drawn according to the regression coefficients. The area under the receiver operating characteristic curves and the GiViTI calibration belts were used to estimate the discrimination and calibration of the prediction model, respectively. Results Multivariate logistic regression analysis showed that the five risk factors of gender, mean computed tomography(CT) attenuation value of hydronephrosis, functional solitary kidney, urine white blood cell(WBC) count and urine nitrite were independent risk factors of ureteral calculi associated with urosepsis. The areas under the receiver operating characteristic curve of the development group and validation group were 0.913 and 0.874 respectively, suggesting that the new prediction model had good discrimination capacity. P-values of the GiViTI calibration test of the two groups were 0.247 and 0.176 respectively, and the 95% CIs of GiViTI calibration belt in both groups did not cross the diagonal bisector line. Therefore the predicted probability of the model was consistent with the actual probability which suggested that the calibration of the prediction model in both groups were perfect and prediction model had strong concordance performance. Conclusion The individualized prediction model for patients with ureteral calculi can facilitate improved screening and early identification of patients having higher risk of urosepsis.
Databáze: OpenAIRE
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