Publications by authors named "Santino Rellum"

Objectives: Cardiac surgery is associated with perioperative complications, some of which might be attributable to hypotension. The Hypotension Prediction Index (HPI), a machine-learning-derived early warning tool for hypotension, has only been evaluated in noncardiac surgery. We investigated whether using HPI with diagnostic guidance reduced hypotension during cardiac surgery and in the ICU.

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Background: Clinical trials and validation studies demonstrate promising hypotension prediction capability by the Hypotension Prediction Index (HPI). Most studies that evaluate HPI derive it from invasive blood pressure readings, but a direct comparison with the noninvasive alternative remains undetermined. Such a comparison could provide valuable insights for clinicians in deciding between invasive and noninvasive monitoring strategies.

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: Hypotension is common in the post-anesthesia care unit (PACU) and intensive care unit (ICU), and is associated with adverse patient outcomes. The Hypotension Prediction Index (HPI) algorithm has been shown to accurately predict hypotension in mechanically ventilated patients in the OR and ICU and to reduce intraoperative hypotension (IOH). Since positive pressure ventilation significantly affects patient hemodynamics, we performed this validation study to examine the performance of the HPI algorithm in a non-ventilated PACU and ICU population.

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Purpose: The aim of this study is to provide a summary of the existing literature on the association between hypotension during intensive care unit (ICU) stay and mortality and morbidity, and to assess whether there is an exposure-severity relationship between hypotension exposure and patient outcomes.

Methods: CENTRAL, Embase, and PubMed were searched up to October 2022 for articles that reported an association between hypotension during ICU stay and at least one of the 11 predefined outcomes. Two independent reviewers extracted the data and assessed the risk of bias.

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Introduction: Hypotension is common during cardiac surgery and often persists postoperatively in the intensive care unit (ICU). Still, treatment is mainly reactive, causing a delay in its management. The Hypotension Prediction Index (HPI) can predict hypotension with high accuracy.

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Background: TAVI has shown to result in immediate and sustained hemodynamic alterations and improvement in health-related quality of life (HRQoL), but previous studies have been suboptimal to predict who might benefit from TAVI. The relationship between immediate hemodynamic changes and outcome has not been studied before. This study sought to assess whether an immediate hemodynamic change, reflecting myocardial contractile reserve, following TAVI is associated with improved HRQoL.

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Background: Machine learning (ML) is developing fast with promising prospects within medicine and already has several applications in perioperative care. We conducted a scoping review to examine the extent and potential limitations of ML implementation in perioperative anesthetic care, specifically in cardiac surgery patients.

Methods: We mapped the current literature by searching three databases: MEDLINE (Ovid), EMBASE (Ovid), and Cochrane Library.

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Objectives: The primary objectives of this meta-analysis in critically ill adult patients admitted to the intensive care unit (ICU) were to analyse whether erythropoiesis-stimulating agents (ESAs) reduced the number of patients receiving red blood cell (RBC) transfusion and resulted in a change in haemoglobin (Hb) concentration. Our secondary objectives were adverse events and mortality.

Background: Anaemia is common in ICU patients, and currently, the standard therapy is RBC transfusion, which is known to be associated with adverse events.

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