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

Total bilirubin level is associated with acute kidney injury in neonates admitted to the neonatal intensive care units: based on MIMIC-III database

OBJECTIVE

The objective of this study was to investigate the association between total bilirubin and acute kidney injury (AKI) in neonates admitted to neonatal intensive care units (NICU).

METHODS

All data utilized were extracted from Medical Information Mart for Intensive Care-III (MIMIC-III) in this retrospective cohort study. The primary outcome was the occurrence of AKI during hospitalization in the NICU, and the exposure was the initial measurement of total bilirubin levels within 24 h of neonatal admission to the NICU. The relationship between serum total bilirubin and AKI was evaluated by employing univariate and multivariate logistic regression models. Additionally, subgroup analyses were conducted based on birth weight, sepsis, and mechanical ventilation.

RESULTS

This retrospective cohort study included a population of 1,726 neonates, and 95 neonates developed AKI. Total bilirubin, as a continuous variable, was linked with decreased AKI risk among neonates admitted to the NICU [odds ratio (OR) = 0.77, 95% confidence interval (CI): 0.64-0.92]. Similarly, when total bilirubin levels were categorized by tertiles, tertiles 3 showed a significant association with decreased AKI risk (OR = 0.39, 95%CI: 0.19-0.83). The relationship of total bilirubin level and AKI was also existent among neonates admitted to the NICU who were underweight, had not sepsis, and received mechanical ventilation.

CONCLUSION

Total bilirubin level may be a protective factor for the risk of developing AKI.

Epidemiology and Nomogram for Predicting the Cancer-specific Survival of Ovarian Granulosa Cell Tumor: A Seer database study

OBJECTIVE

ovarian granulosa cell tumor (OGCT) is a kind of infrequent ovarian malignant tumor with limited epidemiological data available. we established a predictive nomograph to verify the clinical prognosis.

METHODS

1005 diagnosed with ovarian granulosa cell tumor (OGCT) were extracted from Surveillance, Epidemiology, and End Results (SEER) public database from 2000-2018. Kaplan-Meier analysis was applied to distinguish risk factors, univariate and multivariate Cox analyses were used to determine the independent prognostic factors for cancer-specific survival (CSS) of OGCT patients. The obtained prognostic variables were combined to construct a nomogram model for predicting CSS in OGCT patients.

RESULTS

Model performance was detected and evaluated with ROC curves and calibration plots. Data collected from 1005 patients were divided into two groups: training cohort(n=703,70%) and validation cohort(n=302,30%). The multivariate Cox model identified five covariates including age, marital status, AJCC stages, surgery and chemotherapy as independent interfering factors of CSS. The nomogram has shown a promising and excellent accuracy in evaluating 3 -, 5 -, 8-year CSS in OGCT patients. In terms of the CSS of the training cohort, the AUC values of the 3 -, 5 -, 8-year ROC curves were 0.819,0.8,0.819, while in terms of the CSS of the validation cohort, the AUC values of the validation cohort were 0.822,0.84,0.823, respectively. All the calibration curves showed pleasant consistency between predicted and actual survival rates. The nomogram model established in the study can improve the veracity of prognosis prediction, thereby improving the accuracy of individualized survival risk assessment, and providing targeted and constructive recommendations for specific treatment options.

CONCLUSION

Age, advanced clinical stage, widower and without surgery therapy are independent risk factors for poor prognosis and the nomogram we constructed can help clinicians efficiently recognize high-risk OGCT patients to guide targeted therapies and improve their outcomes.