PhD Scientific Days 2022

Clinical Medicine VI. (Poster discussion will take place on the terrace of the room during the Coffee Break)

Finding the Holy Grail: Ranking List of Prediction Scores in Out-of-Hospital Cardiac Arrest

Előadó neve

Dr. Kiss, Boldizsar

Előadó munkahelye

Heart and Vascular Centre, Semmelweis University, Budapest

Előadó telefonszáma

+36 20 666 3575

Előadó e-mail címe

b.kiss96@gmail.com

Az előadás címe

Finding the Holy Grail: Ranking List of Prediction Scores in Out-of-Hospital Cardiac Arrest

Szerző(k) neve és munkahelye

Boldizsár Kiss1, Rita Nagy2,3, Tamás Kói2, Henriette Mészáros1, Bettina Nagy1, Ádám Pál-Jakab1, Péter Hegyi2,3, Béla Merkely1, Endre Zima1

1 Heart and Vascular Centre, Semmelweis University, Budapest
2 Centre for Translational Medicine, Semmelweis University, Budapest
3 Division of Pancreatic Diseases, Heart and Vascular Center, Semmelweis University, Budapest

Bemutatás módja

Poszter

Szekció

Clinical Medicine VI. (Poster discussion will take place on the terrace of the room during the Coffee Break)

Language of the presentation

Hungarian

Preferred session

Clinical Medicine

Összefoglaló szövege

Introduction
Ongoing changes in medicine and the societal create a range of ethical challenges for clinicians. In the context of post cardiac arrest syndrome, ethically difficult decisions must be made when to continue or withdraw life-sustaining therapies. According to the guidelines, prognostication after cardiopulmonary resuscitation should base on clinical examination, biomarkers, imaging and electrophysiological testing. Several prognostic scores exist to predict neurological and mortality outcome in post-cardiac arrest patients.
Methods
Our systematic search was conducted on 8th November, 2021 in four databases: Medline, Embase, Central and Scopus. The patient population was successfully reanimated adult patients after out-of-hospital cardiac arrest. We included all prognostic score systems in our analysis which were suitable to estimate the primary outcome (neurologic function) and the secondary outcome (mortality). From the eligible articles data were collected by two authors independently. The accuracy of data was validated by a third reviewer.
For each score and outcome we collected the AUC values and their CIs and performed a meta-analysis using the random effect model to gain pooled AUC estimates with 95% CI. We made Summary Receiver Operating Characteristics (SROC) curves using 2 × 2 contingency tables. The statistical analysis was performed by R software.
Results
16501 records were identified and 69 met the selection criteria and were included in the qualitative analysis. Out of these, 12 studies were included in the quantitative synthesis. The pooled AUC (95%CI) was 0.89 (0.85-0.93) for CAHP, 0.84 (0.80-0.87) for OHCA, and 0.80 (0.74-0.85) for C-GRApH to predict neurological outcome at hospital discharge; 0.84 (0.73-0.96) for NULL-PLEASE and 0.84 (0.76-0.92) for OHCA to predict in-hospital mortality. High heterogeneity was shown in the analysis of CAHP (I2=75%; p < 0.01) and NULL-PLEASE (I2=81%; p < 0.01) scores.
Conclusion
Our results show that CAHP is the most accurate score system to predict neurological outcome at hospital discharge. Not only for accuracy but also for the rapid availability of the necessary data, we recommend the use of the CAHP scoring system in everyday clinical practice. NULL-PLEASE and OHCA scores are quite accurate to predict in-hospital mortality.
Funding
BK was supported by grant EFOP-3.6.3-VEKOP-16-2017-00009.

University and Doctoral School

Semmelweis University, Doctoral School of Theoretical and Translational Medicine

Supervisor

Prof. Endre Zima

Publication of my abstract

I do not give consent to the publication of my abstract on the website of the congress.

Kind

Szabad

Status

elfogadva

Accepted presentation method

poszter

Előadás fájl jóváhagyás

nem rendelkezett róla

Előadó

6033

Start

11:25

End

11:30

Authors (legacy)

Boldizsár Kiss1, Rita Nagy2,3, Tamás Kói2, Henriette Mészáros1, Bettina Nagy1, Ádám Pál-Jakab1, Péter Hegyi2,3, Béla Merkely1, Endre Zima1

1 Heart and Vascular Centre, Semmelweis University, Budapest
2 Centre for Translational Medicine, Semmelweis University, Budapest
3 Division of Pancreatic Diseases, Heart and Vascular Center, Semmelweis University, Budapest