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- Hellsén, Gustaf, et al.
(författare)
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Predicting recurrent cardiac arrest in individuals surviving Out-of-Hospital cardiac arrest
- 2023
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Ingår i: Resuscitation. - : Elsevier BV. - 0300-9572 .- 1873-1570. ; 184
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Tidskriftsartikel (refereegranskat)abstract
- Background: Despite improvements in short-term survival for Out-of-Hospital Cardiac Arrest (OHCA) in the past two decades, long-term survival is still not well studied. Furthermore, the contribution of different variables on long-term survival have not been fully investigated. Aim: Examine the 1-year prognosis of patients discharged from hospital after an OHCA. Furthermore, identify factors predicting re-arrest and/or death during 1-year follow-up. Methods: All patients 18 years or older surviving an OHCA and discharged from the hospital were identified from the Swedish Register for Car-diopulmonary Resuscitation (SRCR). Data on diagnoses, medications and socioeconomic factors was gathered from other Swedish registers. A machine learning model was constructed with 886 variables and evaluated for its predictive capabilities. Variable importance was gathered from the model and new models with the most important variables were created. Results: Out of the 5098 patients included, 902 (-18%) suffered a recurrent cardiac arrest or death within a year. For the outcome death or re-arrest within 1 year from discharge the model achieved an ROC (receiver operating characteristics) AUC (area under the curve) of 0.73. A model with the 15 most important variables achieved an AUC of 0.69. Conclusions: Survivors of an OHCA have a high risk of suffering a re-arrest or death within 1 year from hospital discharge. A machine learning model with 15 different variables, among which age, socioeconomic factors and neurofunctional status at hospital discharge, achieved almost the same predictive capabilities with reasonable precision as the full model with 886 variables.
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| 2. |
- Thorén, A., et al.
(författare)
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ECG-monitoring of in-hospital cardiac arrest and factors associated with survival
- 2020
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Ingår i: Resuscitation. - : Elsevier BV. - 0300-9572 .- 1873-1570. ; 150, s. 130-138
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Tidskriftsartikel (refereegranskat)abstract
- Background: ECG-monitoring is a strong predictor for 30-days survival after in-hospital cardiac arrest (IHCA). The aim of the study is to investigate factors influencing the effect of ECG-monitoring on 30-days survival after IHCA and elements of importance in everyday clinical practice regarding whether patients are ECG-monitored prior to IHCA. Methods: In all, 19.225 adult IHCAs registered in the Swedish Registry for Cardiopulmonary Resuscitation (SRCR) were included. Cox-adjusted survival curves were computed to study survival post IHCA. Logistic regression was used to study the association between 15 predictors and 30-days survival. Using logistic regression we calculated propensity scores (PS) for ECG-monitoring; the PS was used as a covariate in a logistical regression estimating the association between ECG-monitoring and 30-days survival. Gradient boosting was used to study the relative importance of all predictors on ECG-monitoring. Results: Overall 30-days survival was 30%. The ECG-monitored group (n = 10.133, 52%) had a 38% lower adjusted mortality (HR 0.62 95% CI 0.60−0.64). We observed tangible variations in ECG-monitoring ratio at different centres. The predictors of most relative influence on ECG-monitoring in IHCA were location in hospital and geographical localization. Conclusion: ECG-monitoring in IHCA was associated to a 38% lower adjusted mortality, despite this finding only every other IHCA patient was monitored. The significant variability in the frequency of ECG-monitoring in IHCA at different centres needs to be evaluated in future research. Guidelines for in-hospital ECG-monitoring could contribute to an improved identification and treatment of patients at risk, and possibly to an improved survival. © 2020 Elsevier B.V.
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