P19.11: Nomogram for prediction of preterm birth in symptomatic uterine contraction in twin pregnant women

Kim, J.; Lee, S.; Kim, S.; Hue, Hye Jeong; Park, C.; Park, J.; Jun, Jong Kwan

doi:10.1002/uog.21070

Cited by 1 publication

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A few minutes to a few hours after SAH is the first high-incidence period, mostly in the blood vessels surrounding the ruptured aneurysm with the significance of the location of the tumor-bearing artery. The second high-incidence period is usually 4-16 days after SAH, with 7-10 days being the most common; most of them are diffuse and multisegmental and have no positioning value for the tumor-bearing artery [ 2 ]. According to Poiseuille's law of hemodynamics, the blood flow per unit time is proportional to the 4th power of the vessel radius.…”

Section: Introductionmentioning

confidence: 99%

Predictive Model of Cerebral Vasospasm in Subarachnoid Hemorrhage Based on Regression Equation

Zhou

Wang

et al. 2022

Scanning

View full text Add to dashboard Cite

In order to explore the regression equation for the prediction model of subarachnoid hemorrhage and cerebral vasospasm, the nomogram prediction model of SCVS occurrence was established. This study is a retrospective analysis of 125 cases of aSAH admitted to a hospital; the patients were divided into SCVS group and non-SCVS group. Select SIRI as a simple and reliable marker of inflammation, analyze its correlation with SCVS and its predictive value, and analyze the predictive value of SIRI to SCVS through ROC curve. Based on the SIRI inflammation level and other related risk factors, a nomogram prediction model for the occurrence of SCVS was built. The experimental results show that the SIRI level of patients in the SCVS group was significantly higher than that of the non-SCVS group, and logistic regression analysis found that SIRI is an independent risk factor for SCVS. S I R I = 3.63 × 10 9 / L is the best cutoff value for diagnosing the occurrence of SCVS. When TC = 2.24 mmol/L and SIRI = 3.63 × 10 %/L, its Youden Index is the largest (0.312, 0.296) and is the best cutoff value for predicting the occurrence of SCVS; at the same time, its prediction accuracy (area under the ROC curve (AUC)), sensitivity, specificity, the positive predictive value, and negative predictive value are 0.743, 72.70%, 80.10%, 77.53%, and 94.24% and 0.725, 70.60%, 76.90%, 73.49%, and 93.59%. Nomogram prediction model establishment and evaluation combined with the results of multifactor analysis are used to build an individual nomogram prediction model. The model has good prediction consistency (C- index = 0.685 , P < 0.01 ). ROC analysis results showed that the model that combined SIRI and other standard variables ( AUC = 0.896 , 95% CI was 0.803-0.929, P < 0.001 ) was better than the model that did not combine SIRI ( AUC = 0.859 , 95% CI was 0.759-0.912, P < 0.001 ) and the model based only on SIRI ( AUC = 0.725 , 95% CI was 0.586-0.793, P = 0.001 ) has better predictive value for SCVS. Joint SIRI will optimize the prediction performance of the nomogram model and improve the early recognition and screening capabilities of SCVS.

show abstract

Section: Introductionmentioning

confidence: 99%