Comparison of a new predictive model with other critical scores for predicting in-hospital mortality among children with pneumonia-related bacteremia

Lin, Jilei; Yin, Zhang; Song, Anchao; Yang, Nan; Ying, Linyan; Dai, Jihong

doi:10.1136/jim-2020-001688

Cited by 4 publications

(1 citation statement)

References 18 publications

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“…Consistent with previous studies, the present study found that PCIS was a vital risk factor for SAE development in children with sepsis. Moreover, the PCIS showed good accuracy and discriminatory ability in the prognostic prediction of many other critical diseases, such as pneumonia-related bacteremia, hand-foot-and-mouth disease, acute paraquat poisoning, and acute leukemia [ 36 – 39 ]. However, data on the correlation between PCIS and SAE are limited, and future high-quality studies are needed for further exploration.…”

Section: Discussionmentioning

confidence: 99%

Development and validation of a nomogram to predict the risk of sepsis-associated encephalopathy for septic patients in PICU: a multicenter retrospective cohort study

Wang,

Jiang,

et al. 2024

j intensive care

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Background Patients with sepsis-associated encephalopathy (SAE) have higher mortality rates and longer ICU stays. Predictors of SAE are yet to be identified. We aimed to establish an effective and simple-to-use nomogram for the individual prediction of SAE in patients with sepsis admitted to pediatric intensive care unit (PICU) in order to prevent early onset of SAE. Methods In this retrospective multicenter study, we screened 790 patients with sepsis admitted to the PICU of three hospitals in Shandong, China. Least absolute shrinkage and selection operator regression was used for variable selection and regularization in the training cohort. The selected variables were used to construct a nomogram to predict the risk of SAE in patients with sepsis in the PICU. The nomogram performance was assessed using discrimination and calibration. Results From January 2017 to May 2022, 613 patients with sepsis from three centers were eligible for inclusion in the final study. The training cohort consisted of 251 patients, and the two independent validation cohorts consisted of 193 and 169 patients. Overall, 237 (38.7%) patients developed SAE. The morbidity of SAE in patients with sepsis is associated with the respiratory rate, blood urea nitrogen, activated partial thromboplastin time, arterial partial pressure of carbon dioxide, and pediatric critical illness score. We generated a nomogram for the early identification of SAE in the training cohort (area under curve [AUC] 0.82, 95% confidence interval [CI] 0.76–0.88, sensitivity 65.6%, specificity 88.8%) and validation cohort (validation cohort 1: AUC 0.80, 95% CI 0.74–0.86, sensitivity 75.0%, specificity 74.3%; validation cohort 2: AUC 0.81, 95% CI 0.73–0.88, sensitivity 69.1%, specificity 83.3%). Calibration plots for the nomogram showed excellent agreement between SAE probabilities of the observed and predicted values. Decision curve analysis indicated that the nomogram conferred a high net clinical benefit. Conclusions The novel nomogram and online calculator showed performance in predicting the morbidity of SAE in patients with sepsis admitted to the PICU, thereby potentially assisting clinicians in the early detection and intervention of SAE.

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Section: Discussionmentioning

confidence: 99%

Development and validation of a nomogram to predict the risk of sepsis-associated encephalopathy for septic patients in PICU: a multicenter retrospective cohort study

Wang,

Jiang,

et al. 2024

j intensive care

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Predicting Clinical Deterioration and Mortality at Differing Stages During Hospitalization: A Systematic Review of Risk Prediction Models in Children in Low- and Middle-Income Countries

Brink¹,

Vries²,

Datema³

et al. 2023

The Journal of Pediatrics

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Value of cardiac enzyme spectrum for the risk assessment of mortality in critically ill children: a single-centre retrospective study

Wang,

Chen,

Shen

et al. 2024

BMJ Open

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ObjectivesIdentifying high-risk paediatric patients with a poor prognosis and providing timely and adequate treatment are critical. This study aimed to evaluate the effects of different types of cardiac enzyme spectrum within 24 hours of admission on the short-term prognosis of patients in paediatric intensive care units.DesignA retrospective study.SettingA single-centre, tertiary care hospital in China, with patient data from 2010 to 2018.ParticipantsA total of 4343 critically ill children were enrolled.InterventionNone.Primary and secondary outcome measuresThe main outcome measure was in-hospital mortality, which was defined as death from any cause during hospitalisation. The secondary outcome was 30-day mortality, intensive care unit (ICU) length of stay (LOS) and total LOS.ResultsUsing the local polynomial regression fitting method, an approximately linear increase in in-hospital mortality was detected for creatine kinase (CK), creatine kinase MB (CK-MB), aspartate aminotransferase (AST) and lactate dehydrogenase (LDH). Among the different types of cardiac enzyme spectrum, LDH had the highest area under the curve value (0.729), followed by AST (0.701), CK-MB (0.613) and CK (0.557). The Kaplan‒Meier analysis showed that the patients in the high LDH group had higher 30-day mortality. The multivariate logistic regression revealed that high LDH was independently associated with in-hospital mortality (OR 2.45, 95% CI 1.84 to 3.24). After propensity score matching (PSM) and sensitivity analysis, the results remained consistent.ConclusionsLDH is a reliable outcome predictor in critically ill children, including those with various comorbidities.

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Comparison of a new predictive model with other critical scores for predicting in-hospital mortality among children with pneumonia-related bacteremia

Cited by 4 publications

References 18 publications

Development and validation of a nomogram to predict the risk of sepsis-associated encephalopathy for septic patients in PICU: a multicenter retrospective cohort study

Development and validation of a nomogram to predict the risk of sepsis-associated encephalopathy for septic patients in PICU: a multicenter retrospective cohort study

Predicting Clinical Deterioration and Mortality at Differing Stages During Hospitalization: A Systematic Review of Risk Prediction Models in Children in Low- and Middle-Income Countries

Value of cardiac enzyme spectrum for the risk assessment of mortality in critically ill children: a single-centre retrospective study

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