A recalibrated prediction model can identify level-1 trauma patients at risk of nosocomial pneumonia.

INTRODUCTION: Nosocomial pneumonia has poor prognosis in hospitalized trauma patients. Croce et al. published a model to predict post-traumatic ventilator-associated pneumonia, which achieved high discrimination and reasonable sensitivity. We aimed to externally validate Croce's model to predict nosocomial pneumonia in patients admitted to a Dutch level-1 trauma center. MATERIALS AND METHODS: This retrospective study included all trauma patients (≥ 16y) admitted for > 24 h to our level-1 trauma center in 2017. Exclusion criteria were pneumonia or antibiotic treatment upon hospital admission, treatment elsewhere > 24 h, or death < 48 h. Croce's model used eight clinical variables-on trauma severity and treatment, available in the emergency department-to predict nosocomial pneumonia risk. The model's predictive performance was assessed through discrimination and calibration before and after re-estimating the model's coefficients. In sensitivity analysis, the model was updated using Ridge regression. RESULTS: 809 Patients were included (median age 51y, 67% male, 97% blunt trauma), of whom 86 (11%) developed nosocomial pneumonia. Pneumonia patients were older, more severely injured, and underwent more emergent interventions. Croce's model showed good discrimination (AUC 0.83, 95% CI 0.79-0.87), yet predicted probabilities were too low (mean predicted risk 6.4%), and calibration was suboptimal (calibration slope 0.63). After full model recalibration, discrimination (AUC 0.84, 95% CI 0.80-0.88) and calibration improved. Adding age to the model increased the AUC to 0.87 (95% CI 0.84-0.91). Prediction parameters were similar after the models were updated using Ridge regression. CONCLUSION: The externally validated and intercept-recalibrated models show good discrimination and have the potential to predict nosocomial pneumonia. At this time, clinicians could apply these models to identify high-risk patients, increase patient monitoring, and initiate preventative measures. Recalibration of Croce's model improved the predictive performance (discrimination and calibration). The recalibrated model provides a further basis for nosocomial pneumonia prediction in level-1 trauma patients. Several models are accessible via an online tool. LEVEL OF EVIDENCE: Level III, Prognostic/Epidemiological Study.

Changes in DXA and quantitative CT measures of musculoskeletal outcomes following pediatric renal transplantation.

This prospective study evaluated changes in dual energy X-ray absorptiometry (DXA) whole body bone mineral content (WB-BMC) and spine areal bone mineral density (spine-BMD), and tibia quantitative computed tomography (QCT) trabecular and cortical volumetric BMD and cortical area in 56 children over 12 months following renal transplantation. At transplant, spine-BMD Z-scores were greater in younger recipients (<13 years), versus 898 reference participants (p < 0.001). In multivariate models, greater decreases in spine-BMD Z-scores were associated with greater glucocorticoid dose (p < 0.001) and declines in parathyroid hormone levels (p = 0.008). Changes in DXA spine-BMD and QCT trabecular BMD were correlated (r = 0.47, p < 0.01). At 12 months, spine-BMD Z-scores remained elevated in younger recipients, but did not differ in older recipients (≥ 13) and reference participants. Baseline WB-BMC Z-scores were significantly lower than reference participants (p = 0.02). Greater glucocorticoid doses were associated with declines in WB-BMC Z-scores (p < 0.001) while greater linear growth was associated with gains in WB-BMC Z-scores (p = 0.01). Changes in WB-BMC Z-scores were associated with changes in tibia cortical area Z-scores (r = 0.52, p < 0.001), but not changes in cortical BMD Z-scores. Despite resolution of muscle deficits, WB-BMC Z-scores at 12 months remained significantly reduced. These data suggest that spine and WB DXA provides insight into trabecular and cortical outcomes following pediatric renal transplantation.