Nicola DE LUCA

Background: Acute heart failure (AHF) represents a leading cause of unscheduled hospital stays, frequent rehospitalisations, and mortality worldwide. The aim of our study was to develop a bedside prognostic tool, a multivariable predictive risk score, that is useful in daily practice, thus providing an early prognostic evaluation at admission and an accurate risk stratification after discharge in patients with AHF. Methods: This study is a subanalysis of the STADE HF study, which is a single-centre, prospective, randomised controlled trial enrolling 123 patients admitted to hospital for AHF. Here, 117 patients were included in the analysis, due to data exhaustivity. Regression analysis was performed to determine predictive variables for one-year mortality and/or rehospitalisation after discharge. Results: During the first year after discharge, 23 patients died. After modellisation, the variables considered to be of prognostic relevance in terms of mortality were (1) non-ischaemic aetiology of HF, (2) elevated creatinine levels at admission, (3) moderate/severe mitral regurgitation, and (4) prior HF hospitalisation. We designed a linear model based on these four independent predictive variables, and it showed a good ability to score and predict patient mortality with an AUC of 0.84 (95%CI: 0.76–0.92), thus denoting a high discriminative ability. A risk score equation was developed. During the first year after discharge, we observed as well that 41 patients died or were rehospitalised; hence, while searching for a model that could predict worsening health conditions (i.e., death and/or rehospitalisation), only two predictive variables were identified: non-ischaemic HF aetiology and previous HF hospitalisation (also included in the one-year mortality model). This second modellisation showed a more discrete discriminative ability with an AUC of 0.67 (95% C.I. 0.59–0.77). Conclusions: The proposed risk score and model, based on readily available predictive variables, are promising and useful tools to assess, respectively, the one-year mortality risk and the one-year mortality and/or rehospitalisations in patients hospitalised for AHF and to assist clinicians in the management of patients with HF aiming at improving their prognosis.

We investigated independent factors predicting neurological outcome and death, comparing in-hospital (IHCA) and out-of-hospital cardiac arrest (OHCA) patients. The study was conducted in the mixed 34-bed Intensive Care Department at the Hôpital Universitaire de Bruxelles (HUB), Belgium. All adult consecutive cardiac arrest (CA) survivors were included between 2004 and 2022. For all patients, demographic data, medical comorbidities, CA baseline characteristics, treatments received during Intensive Care Unit stay, in-hospital major complications, and neurological outcome at three months after CA, using the Cerebral Performance Category (CPC) scale, were collected. In the multivariable analysis, in the IHCA group (n = 540), time to return of spontaneous circulation (ROSC), older age, unwitnessed CA, higher lactate on admission, asystole as initial rhythm, a non-cardiac cause of CA, the occurrence of shock, the occurrence of acute kidney injury (AKI), and the presence of previous neurological disease and of liver cirrhosis were independent predictors of an unfavorable neurological outcome. Among patients with OHCA (n = 567), time to ROSC, older age, higher lactate level on admission, unwitnessed CA, asystole or pulseless electrical activity (PEA) as initial rhythm, the occurrence of shock, a non-cardiac cause of CA, and a previous neurological disease were independent predictors of an unfavorable neurological outcome. To conclude, in our large cohort of mixed IHCA and OHCA patients, we observed numerous factors independently associated with a poor neurological outcome, with minimal differences between the two groups, reflecting the greater vulnerability of hospitalized patients.