Development and validation of the Ex-Care BR model: a multicentre initiative for identifying Brazilian surgical patients at risk of 30-day in-hospital mortality.

BACKGROUND: Surgical risk stratification is crucial for enhancing perioperative assistance and allocating resources efficiently. However, existing models may not capture the complexity of surgical care in Brazil. Using data from various healthcare settings nationwide, we developed a new risk model for 30-day in-hospital mortality (the Ex-Care BR model). METHODS: A retrospective cohort study was conducted in 10 hospitals from different geographic regions in Brazil. Data were analysed using multilevel logistic regression models. Model performance was assessed using the area under the receiver operating characteristic curve (AUROC), Brier score, and calibration plots. Derivation and validation cohorts were randomly assigned. RESULTS: A total of 107,372 patients were included, and 30-day in-hospital mortality was 2.1% (n=2261). The final risk model comprised four predictors related to the patient and surgery (age, ASA physical status classification, surgical urgency, and surgical size), and the random effect related to hospitals. The model showed excellent discrimination (AUROC=0.93, 95% confidence interval [CI], 0.93-0.94), calibration, and overall performance (Brier score=0.017) in the derivation cohort (n=75,094). Similar results were observed in the validation cohort (n=32,278) (AUROC=0.93, 95% CI, 0.92-0.93). CONCLUSIONS: The Ex-Care BR is the first model to consider regional and organisational peculiarities of the Brazilian surgical scene, in addition to patient and surgical factors. It is particularly useful for identifying high-risk surgical patients in situations demanding efficient allocation of limited resources. However, a thorough exploration of mortality variations among hospitals is essential for a comprehensive understanding of risk. CLINICAL TRIAL REGISTRATION: NCT05796024.

Analytical and clinical validation of a dried blood spot assay for the determination of paclitaxel using high-performance liquid chromatography-tandem mass spectrometry.

BACKGROUND: Paclitaxel (PCT) is a chemotherapeutic drug widely used for the treatment of several types of tumors, and its use is associated with severe adverse events, mainly neurologic and hematopoietic toxicities. The relation between systemic exposure and clinical response to PCT was previously described, making paclitaxel a potential candidate for therapeutic drug monitoring (TDM). The use of dried blood spot (DBS) sampling could allow complex sampling schedules required for TDM of PCT. The aim of this study was to develop and validate an LC-MS/MS assay for the quantification of PCT in DBS. METHODS: PCT was extracted from one 8 mm DBS punch with a mixture of methanol and acetonitrile, followed by chromatographic separation in a Kinetex C18 (50 × 4.6 mm, 2.6 µm) column. Detection was performed in a 5500-QTRAP® mass spectrometer, with a run time of 2.3 min. RESULTS: The assay was linear in the range of 2.5 to 400 ng mL-1. Precision (CV%) and accuracy at the concentration levels of 7.5, 40 and 150 ng mL-1 were 1.69-4.9% and 106.25 to 109.92%, respectively. PCT was stable for 21 days at 25 and 45 °C. The method was applied to DBS samples obtained from 34 patients under PCT chemotherapy. The use of a simple correction factor, derived from the correlation between PCT concentrations in plasma and DBS in this set of patients, allowed unbiased estimation of PCT plasma concentrations from DBS measurements, with similar clinical decisions using either plasma or DBS measurements. CONCLUSIONS: DBS testing of PCT concentrations represents a promising alternative for the dissemination of PCT dose individualization.