A nomogram for predicting the in-hospital mortality after large hemispheric infarction

Sun, Wenzhe; Li, Guo; Liu, Ziqiang; Miao, Jinfeng; Yang, Zhaoxia; Zhou, Qiao; Zhu, Suiqiang; Zhu, Zhou

doi:10.1186/s12883-019-1571-4

Cited by 11 publications

(13 citation statements)

References 44 publications

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“…It can help clinicians make quick and sound decisions due to the characteristics of better accuracy, straightforward digital interfaces and readily comprehensible prognosis. 30 , 31 To the best of our knowledge, this is the first study to construct a nomogram for predicting the risk of in-hospital mortality in the NICU, which simply and easily depicted the associations of each predictor with in-hospital mortality risk. Moreover, the AUC of the present nomogram in predicting neonatal in-hospital mortality was 0.865, showing good predictive accuracy.…”

Section: Resultsmentioning

confidence: 99%

A nomogram to predict in-hospital mortality of neonates admitted to the intensive care unit

Huang

Liang

Tang

et al. 2021

International Health

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Background To explore the influencing factors for in-hospital mortality in the neonatal intensive care unit (NICU) and to establish a predictive nomogram. Methods Neonatal data were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) database. Both univariate and multivariate logit binomial general linear models were used to analyse the factors influencing neonatal death. The area under the receiver operating characteristics (ROC) curve was used to assess the predictive model, which was visualized by a nomogram. Results A total of 1258 neonates from the NICU in the MIMIC-III database were eligible for the study, including 1194 surviving patients and 64 deaths. Multivariate analysis showed that red cell distribution width (RDW) (odds ratio [OR] 0.813, p=0.003) and total bilirubin (TBIL; OR 0.644, p<0.001) had protective effects on neonatal in-hospital death, while lymphocytes (OR 1.205, p=0.025), arterial partial pressure of carbon dioxide (PaCO2; OR 1.294, p=0.016) and sequential organ failure assessment (SOFA) score (OR 1.483, p<0.001) were its independent risk factors. Based on this, the area under the curve of this predictive model was up to 0.865 (95% confidence interval 0.813 to 0.917), which was also confirmed by a nomogram. Conclusions The nomogram constructed suggests that RDW, TBIL, lymphocytes, PaCO2 and SOFA score are all significant predictors for in-hospital mortality in the NICU.

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Section: Resultsmentioning

confidence: 99%

A nomogram to predict in-hospital mortality of neonates admitted to the intensive care unit

Huang

Liang

Tang

et al. 2021

International Health

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“…Previous studies have used the midline shift to predict AIS patients' prognoses. Sun et al revealed that midline shift was an independent predictor of in-hospital mortality in patients with large hemispheric infarctions [17] . McKeown et al concluded that the presence of a midline shift was predictive of poor outcomes [18] .…”

Section: Discussionmentioning

confidence: 99%

Optic nerve sheath diameter as a new noninvasive marker for predicting the prognosis of patients with acute ischemic stroke in the intensive care unit

Wang

Xing

Liu

et al. 2023

Preprint

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Objective: Intracranial hypertension is linked to poor prognosis after acute ischemic stroke (AIS). Intracranial pressure can be evaluated by using the ultrasonographic optic nerve sheath diameter (ONSD) and transcranial Doppler (TCD). This study aims to determine whether ONSD and TCD parameters could noninvasively predict the prognosis of AIS patients. Design: Prospective observational blinded study. Setting: Neurology intensive care unit (ICU). Patients: Consecutive patients with AIS. Interventions: ONSD and TCD parameters of 81 AIS patients were obtained upon admission. The Glasgow Outcome Scale scores were evaluated at the 6-month follow-up. The clinical differences between the poor and good prognosis groups were compared. The association between variables and prognosis was assessed, and the cutoff values for the Glasgow Coma Scale (GCS) score and ONSD for predicting poor prognoses were analyzed. Measurements and main results: At the 6-month follow-up, 54 patients had poor prognosis; the ONSDs of the poor and good prognosis groups were 5.45±0.38 and 4.96±0.32, respectively (P<0.001). There were no significant differences in TCD parameters between the two groups. ONSD (odds ratio [OR] 1.4; 95% confidence interval [CI], 1.2–1.7; P<0.001) and GCS score (OR, 0.7; 95% CI, 0.5–0.9; P=0.003) were independent factors influencing poor prognosis. The best ONSD cutoff value for poor prognosis was 5.21 mm; the sensitivity, specificity, and area under the curve were 87.0%, 82.1%, and 0.862, respectively. Conclusions: Ultrasonographic measurement of ONSD may be a new prognostic indicator of functional outcomes in ICU AIS patients. However, TCD parameters have no significant prognostic value for AIS patients.

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“…However, both local and overseas studies have rarely focused on VLBW infants, and no risk prediction model has been established thus far. In recent times, the nomogram is widely used as a simple statistical visual tool for predicting the occurrence, development, and prognosis of various diseases ( 11 – 13 ).…”

Section: Introductionmentioning

confidence: 99%

A Prediction Nomogram for Acute Kidney Injury in Very-Low-Birth-Weight Infants: A Retrospective Study

Shi

Zeng

et al. 2021

Front. Pediatr.

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Background and objective: Acute kidney injury (AKI) is recognized as an independent predictor for mortality in very-low-birth-weight (VLBW) infants and is reported to have a high incidence. In this study, we sought to identify the predictors for AKI in VLBW infants and thereby develop a prediction nomogram for the early detection and management of VLBW infants at high risk of developing AKI.Methods: We designed a retrospective study wherein we investigated the baseline hospitalization data of VLBW infants treated at our hospital between January 2012 and October 2018. Independent predictors of AKI in VLBW infants, as identified by multivariate logistic regression, were incorporated into a model. Hosmer–Lemeshow test was used to test the goodness of fit of the model, and a receiver operating characteristic (ROC) curve was plotted to assess the discriminative ability of the model. The model was internally validated using the 10-fold cross-validation method. A nomogram was plotted to predict the risk of AKI in VLBW infants on the basis of the results of multivariate logistic regression analysis.Results: We investigated the data of 604 VLBW infants, of which 144 (23.8%) developed AKI; in 111 (77.1%) of these infants, AKI occurred within 7 days of birth. Multivariate logistic regression analysis identified the following as predictive factors for AKI in VLBW infants: gestational age, red blood cell count within 3 days of birth, serum calcium concentration within 3 days of birth, maternal age of ≥35 years, and pulmonary arterial hypertension or myocardial injury. Furthermore, the nomogram was found to be effective in estimating the risk of AKI in VLBW infants, with an area under the curve (AUC) of 0.794 [95% confidence interval (CI): 0.754–0.834; P < 0.001]. Internal validation done by cross-validation showed that the average AUC was 0.788.Conclusion: The nomogram developed in this study was found to be sensitive and specific for the preoperative prediction of AKI in VLBW infants, as per the Kidney Disease: Improving Global Outcomes (KDIGO) criteria modified for neonates.

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A nomogram for predicting the in-hospital mortality after large hemispheric infarction

Cited by 11 publications

References 44 publications

A nomogram to predict in-hospital mortality of neonates admitted to the intensive care unit

A nomogram to predict in-hospital mortality of neonates admitted to the intensive care unit

Optic nerve sheath diameter as a new noninvasive marker for predicting the prognosis of patients with acute ischemic stroke in the intensive care unit

A Prediction Nomogram for Acute Kidney Injury in Very-Low-Birth-Weight Infants: A Retrospective Study

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