Daniel García-López

Dr. Daniel García-López

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Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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23 September 2022 in Journal of Clinical Medicine
Verified
Journal Article
Open access
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MGManuel Ignacio Monge García
Manuel Ignacio Monge García
DGDaniel García-López
Daniel García-López
ÉGÉtienne Gayat
Étienne Gayat
MSMichael Sander
Michael Sander
PBPeter Bramlage
Peter Bramlage
BSBernd Saugel
Bernd Saugel
Background: Intraoperative hypotension is common in patients having non-cardiac surgery and associated with postoperative acute myocardial injury, acute kidney injury, and mortality. Avoiding intraoperative hypotension is a complex task for anesthesiologists. Using artificial intelligence to predict hypotension from clinical and hemodynamic data is an innovative and intriguing approach. The AcumenTM Hypotension Prediction Index (HPI) software (Edwards Lifesciences; Irvine, CA, USA) was developed using artificial intelligence—specifically machine learning—and predicts hypotension from blood pressure waveform features. We aimed to describe the incidence, duration, severity, and causes of intraoperative hypotension when using HPI monitoring in patients having elective major non-cardiac surgery. Methods: We built up a European, multicenter, prospective, observational registry including at least 700 evaluable patients from five European countries. The registry includes consenting adults (≥18 years) who were scheduled for elective major non-cardiac surgery under general anesthesia that was expected to last at least 120 min and in whom arterial catheter placement and HPI monitoring was planned. The major objectives are to quantify and characterize intraoperative hypotension (defined as a mean arterial pressure [MAP] < 65 mmHg) when using HPI monitoring. This includes the time-weighted average (TWA) MAP < 65 mmHg, area under a MAP of 65 mmHg, the number of episodes of a MAP < 65 mmHg, the proportion of patients with at least one episode (1 min or more) of a MAP < 65 mmHg, and the absolute maximum decrease below a MAP of 65 mmHg. In addition, we will assess causes of intraoperative hypotension and investigate associations between intraoperative hypotension and postoperative outcomes. Discussion: There are only sparse data on the effect of using HPI monitoring on intraoperative hypotension in patients having elective major non-cardiac surgery. Therefore, we built up a European, multicenter, prospective, observational registry to describe the incidence, duration, severity, and causes of intraoperative hypotension when using HPI monitoring in patients having elective major non-cardiac surgery.

11 July 2023 in Revista Española de Anestesiología y Reanimación
Verified
Journal Article
Closed access
MGManuel Ignacio Monge García
Manuel Ignacio Monge García
ILI. Jiménez López
I. Jiménez López
JOJuan Victor Lorente Olazábal
Juan Victor Lorente Olazábal
DGDaniel García-López
Daniel García-López
ALA.R. Fernández López
A.R. Fernández López
JRJavier Ripollés-Melchor
Javier Ripollés-Melchor