Novel antiplatelet and anticoagulant agents in the cardiac care unit

Inclusion of frailty improved performance of delirium prediction for elderly patients in the cardiac intensive care unit (D-FRAIL): A prospective derivation and external validation study

BACKGROUND

The elderly patients admitted to cardiac intensive care unit (CICU) are at relatively high risk for developing delirium. A simple and reliable predictive model can benefit them from early recognition of delirium followed by timely and appropriate preventive strategies.

OBJECTIVE

To explore the role of frailty in delirium prediction and develop and validate a delirium predictive model including frailty for elderly patients in CICU.

DESIGN

A prospective, observational cohort study.

SETTINGS

CICU at China-Japan Friendship Hospital from March 1, 2022 to August 25, 2022 (derivation cohort); CICU at Beijing Anzhen Hospital affiliated to Capital Medical University from March 14, 2023 to May 8, 2023 (external validation cohort).

PARTICIPANTS

A total of 236 and 90 participants were enrolled in the derivation and external validation cohorts, respectively. Participants in the derivation cohort were assigned into either the delirium (n = 70) or non-delirium group (n = 166) based on the occurrence of delirium.

METHODS

The simplified Chinese version of the Confusion Assessment Method for the Diagnosis of Delirium in the Intensive Care Unit was used to assess delirium twice a day at 8:00-10:00 and 18:00-20:00 until the onset of delirium or discharge from the CICU. Frailty was assessed using the FRAIL scale during the first 24 h in the CICU. Other possible risk factors were collected prospectively through patient interviews and medical records review. After processing missing data via multiple imputations, univariate analysis and bootstrapped forward stepwise logistic regression were performed to select optimal predictors and develop the models. The models were internally validated using bootstrapping and evaluated comprehensively via discrimination, calibration, and clinical utility in both the derivation and external validation cohorts.

RESULTS

The study developed D-FRAIL predictive model using FRAIL score, hearing impairment, Acute Physiology and Chronic Health Evaluation-II score, and fibrinogen. The area under the receiver operating characteristic curve (AUC) was 0.937 (95% confidence interval [CI]: 0.907-0.967) and 0.889 (95%CI: 0.840-0.938) even after bootstrapping in the derivation cohort. Inclusion of frailty was demonstrated to improve the model performance greatly with the AUC increased from 0.851 to 0.937 (p < 0.001). In the external validation cohort, the AUC of D-FRAIL model was 0.866 (95%CI: 0.782-0.907). Calibration plots and decision curve analysis suggested good calibration and clinical utility of the D-FRAIL model in both the derivation and external validation cohorts.

CONCLUSIONS

For elderly patients in the CICU, FRAIL score is an independent delirium predictor and the D-FRAIL model demonstrates superior performance in predicting delirium.

Pharmacokinetics and dialytic clearance of apixaban during in vitro continuous renal replacement therapy

Background

To evaluate the transmembrane clearance (CL_TM) of apixaban during modeled in vitro continuous renal replacement therapy (CRRT), assess protein binding and circuit adsorption, and provide initial dosing recommendations.

Methods

Apixaban was added to the CRRT circuit and serial pre-filter bovine blood samples were collected along with post-filter blood and effluent samples. All experiments were performed in duplicate using continuous veno-venous hemofiltration (CVVH) and hemodialysis (CVVHD) modes, with varying filter types, flow rates, and point of CVVH replacement fluid dilution. Concentrations of apixaban and urea were quantified via liquid chromatography-tandem mass spectrometry. Plasma pharmacokinetic parameters for apixaban were estimated via noncompartmental analysis. CL_TM was calculated via the estimated area under the curve (AUC) and by the product of the sieving/saturation coefficient (SC/SA) and flow rate. Two and three-way analysis of variance (ANOVA) models were built to assess the effects of mode, filter type, flow rate, and point of dilution on CL_TM by each method. Optimal doses were suggested by matching the AUC observed in vitro to the systemic exposure demonstrated in Phase 2/3 studies of apixaban. Linear regression was utilized to provide dosing estimations for flow rates from 0.5–5 L/h.

Results

Mean adsorption to the HF1400 and M150 filters differed significantly at 38 and 13%, respectively, while mean (± standard deviation, SD) percent protein binding was 70.81 ± 0.01%. Effect of CVVH point of dilution did not differ across filter types, although CL_TM was consistently significantly higher during CRRT with the HF1400 filter compared to the M150. The three-way ANOVA demonstrated improved fit when CL_TM values calculated by AUC were used (adjusted R² 0.87 vs. 0.52), and therefore, these values were used to generate optimal dosing recommendations. Linear regression revealed significant effects of filter type and flow rate on CL_TM by AUC, suggesting doses of 2.5–7.5 mg twice daily (BID) may be needed for flow rates ranging from 0.5–5 L/h, respectively.

Conclusion

For CRRT flow rates most commonly employed in clinical practice, the standard labeled 5 mg BID dose of apixaban is predicted to achieve target systemic exposure thresholds. The safety and efficacy of these proposed dosing regimens warrants further investigation in clinical studies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12882-021-02248-7.