Clinical characteristics and outcomes of mechanically ventilated elderly patients in intensive care units: a Chinese multicentre retrospective study

Development and internal validation of a clinical prediction model to predict independence in daily living at discharge for patients with heart failure: analysis using a Japanese national inpatient database real-world dataset

PURPOSE

To develop a clinical prediction model (CPM) to predict independence in activities of daily living (ADLs) in patients with heart failure.

SUBJECTS AND METHODS

We collected the data of the individuals who were admitted and rehabilitated for heart failure from January 2017 to June 2022 from Japan's Diagnosis Procedure Combination database. We assessed the subjects' ADLs at discharge using the Barthel Index and classified them into independence, partial-independence, and total-dependence groups based on their ADLs at discharge. Two CPMs (an independence model and a partial-independence model) were developed by a binomial logistic regression analysis. The predictors included subject characteristics, treatment, and post-hospitalization disease onset. The CPMs' accuracy was validated by the area under the curve (AUC). Internal validation was performed using the bootstrap method. The final CPM is presented in a nomogram.

RESULTS

We included 96,753 patients whose ADLs could be traced at discharge. The independence model had a 0.73 mean AUC and a 1.0 slope at bootstrapping. We thus developed a simplified model using nomograms, which also showed adequate predictive accuracy in the independence model. The partial-independence model had a 0.65 AUC and inadequate predictive accuracy.

CONCLUSIONS

The independence model of ADLs in patients with heart failure is a useful CPM.

A cluster randomized trial on inspiratory effort-targeted pressure support adjustment strategy in patients undergoing assisted mechanical ventilation: protocol for the IT-PSV study

Background

Pressure support ventilation (PSV) is one of the most frequently used ventilator modes in the intensive care unit (ICU). The successful implementation of PSV depends on matching the patient's inspiratory effort with the ventilator support. In clinical practice, the pressure support level is usually set and adjusted according to tidal volume and respiratory rate. However, these parameters may not fully represent the patient's effort. Previous studies have shown that pressure muscle index (PMI), which is measured as the difference between the peak and plateau airway pressure during an end-inspiratory airway occlusion, could reliably determine the low and high inspiratory effort during PSV. Herein we present the study protocol for the Inspiratory effort-Targeted Pressure Support Ventilation (IT-PSV) trial to determine the effect of a PMI-targeted pressure support setting strategy on clinical outcomes in patients undergoing PSV.

Methods and analysis

This is a cluster randomized controlled trial. Sixteen ICUs in academic hospitals will be included, eight of which will be randomly allocated to the PMI-targeted group and eight to the tidal volume/respiratory rate-targeted group. Before the initiation of the study, a four-week comprehensive training program, which includes courses of PSV initiation, pressure support adjustment, and weaning process, will be conducted for all staff in the participating ICUs. Adult patients with acute hypoxic respiratory failure and undergoing PSV within 24 h will be included. Pressure support setting and adjustment will follow the strategy according to the grouping. The primary outcome is the ventilator-free days at 28 days after enrollment. The patients will be followed up until successful weaning or separation of mechanical ventilation, death, hospital discharge, or until 28 days after randomization, whichever comes first.

Discussion

The IT-PSV trial will examine the effect of an inspiratory effort-targeted PSV setting strategy on the duration of mechanical ventilation. If positive, it will provide a new physiological-based PSV management that could potentially facilitate protective assisted ventilation.

Clinical trial registration

ClinicalTrials.gov, identifier NCT06526598.