Development and Validation of a Nomogram to Predict the Risk of Lumbar Disk Reherniation within 2 Years After Percutaneous Endoscopic Lumbar Discectomy

Predicting the Risk of In-Hospital Mortality in Traumatic Brain Injury Patients on Invasive Mechanical Ventilation in the Intensive Care Unit: Construction and Validation of an Online Nomogram

OBJECTIVE

To explore mortality risk factors and to construct an online nomogram for predicting in-hospital mortality in traumatic brain injury (TBI) patients receiving invasive mechanical ventilation (IMV) in intensive care unit (ICU).

METHODS

We retrospectively analyzed TBI patients on IMV in ICU from Medical Information Mart for Intensive Care IV database and 2 hospitals. Least absolute shrinkage and selection operation regression and multiple logistic regression were used to detect predictors of in-hospital mortality and to construct an online nomogram. The predictive performance of nomogram was evaluated using area under the receiver operating characteristic curves (AUC), calibration curves, decision curve analysis, and clinical impact curves.

RESULTS

Five hundred ten from Medical Information Mart for Intensive Care IV database were enrolled for nomogram construction (80%, n = 408) and internal validation (20%, n = 102). One hundred eighty-five from 2 hospitals were enrolled for external validation. Least absolute shrinkage and selection operation-logistic regression revealed predictors of in-hospital mortality among TBI patients on IMV in ICU included Glasgow Coma Scale (GCS) after ICU admission, Acute Physiology Score III (APS III) after ICU admission, neutrophil and lymphocyte ratio after IMV, blood urea nitrogen after IMV, arterial serum lactate after IMV, and in-hospital tracheotomy. The AUC, calibration curves, decision curve analysis, and clinical impact curves indicated the nomogram had good discrimination, calibration, clinical benefit, and applicability. The multimodel comparisons revealed the nomogram had higher AUC than GCS, APS III, and Simplified Acute Physiology Score II.

CONCLUSIONS

We constructed and validated an online nomogram based on routinely recorded factors at admission to ICU and at the beginning of IMV to target prediction of in-hospital mortality among TBI patients on IMV in ICU.

Analysis of risk factors for post-operative recurrence after percutaneous endoscopic lumbar discectomy in patients with lumbar disc herniation: a meta-analysis

BACKGROUND

This study aimed to systematically evaluate risk factors for post-operative recurrence after percutaneous endoscopic lumbar discectomy (PELD) in patients with lumbar disc herniation (LDH).

METHODS

The eligible studies were retrieved from PubMed, Embase, and Web of Science databases. Quality assessment was performed. The effects of binary variables (sex, Modic change (MC), type 2 diabetes (T2DM), and smoking) on post-operative recurrence were evaluated as odds ratio (OR) and 95% confidence interval (CI). The effects of continuous variables (sagittal range of motion (SROM), body mass index (BMI), and age) were assessed as weighted mean difference (WMD) and 95% CI. Sensitivity analysis and publication bias were conducted to evaluate the reliability of pooled results.

RESULTS

Eight studies were included, and their methodological quality was medium. MC (OR (95% CI) = 3.88 (2.24-6.74), P < 0.001), smoking (OR (95% CI) = 1.87 (1.45, 2.42), P < 0.001), T2DM (OR (95% CI) = 1.61 (1.12, 2.31), P = 0.010), SROM (WMD (95% CI) = 2.33 (0.95, 3.70), P = 0.001), BMI (WMD (95% CI) = 1.68 (1.37, 1.99) kg/m2, P < 0.001), and age (WMD (95% CI) = 9.95 (5.05, 14.86) years, P < 0.001) were significantly related to post-operative recurrence in patients with LDH after PELD. Significant publication bias was not observed among studies in all outcome indicators.

CONCLUSION

Our findings reveal that high levels of age, BMI, and SROM, history of T2DM or smoking, or more MC may be correlated with post-operative recurrence after PELD.