Rearrest during hospitalisation in adult comatose out-of-hospital cardiac arrest patients: Risk factors and prognostic impact, and predictors of favourable long-term outcomes

Jung, Yong Hun; Jeung, Kyung Woon; Lee, Hyoung Youn; Lee, Byung Kook; Lee, Dong Hun; Shin, Jonghwan; Lee, Hui Jai; Cho, In Soo; Kim, Young‐Min

doi:10.1016/j.resuscitation.2021.11.037

Cited by 5 publications

(4 citation statements)

References 33 publications

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“…[4,[7][8][9]24] Rearrest is a strong predictor of poor outcomes. [25] The 24-hour survival rate was signifi cantly lower in patients in our study with unsustained ROSC than in those with sustained ROSC, and no patients with unsustained ROSC survived to 28 d. Sufficient carbon monoxide (CO) and blood pressure are needed to maintain sustained ROSC. However, high-quality CPR only provides 15% to 25% of normal CO. [3] Prolonged CPR in patients with unsustained ROSC reduces the possibility of ROSC.…”

Section: Discussionmentioning

confidence: 71%

A novel predictor of unsustained return of spontaneous circulation in cardiac arrest patients through a combination of capnography and pulse oximetry: a multicenter observational study

Yang,

Tang,

Shao

et al. 2024

World Journal of Emergency Medicine

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BACKGROUND: Unsustained return of spontaneous circulation (ROSC) is a critical barrier to survival in cardiac arrest patients. This study examined whether end-tidal carbon dioxide (ETCO 2 ) and pulse oximetry photoplethysmogram (POP) parameters can be used to identify unsustained ROSC. METHODS:We conducted a multicenter observational prospective cohort study of consecutive patients with cardiac arrest from 2013 to 2014. Patients' general information, ETCO 2 , and POP parameters were collected and statistically analyzed. RESULTS:The included 105 ROSC episodes (from 80 cardiac arrest patients) comprised 51 sustained ROSC episodes and 54 unsustained ROSC episodes. The 24-hour survival rate was significantly higher in the sustained ROSC group than in the unsustained ROSC group (29.2% vs. 9.4%, P<0.05). The logistic regression analysis showed that the difference between after and before ROSC in ETCO 2 (ΔETCO 2 ) and the difference between after and before ROCS in area under the curve of POP (ΔAUCp) were independently associated with sustained ROSC (odds ratio [OR]=0.931, 95% confi dence interval [95% CI] 0.881-0.984, P=0.011 and OR=0.998, 95% CI 0.997-0.999, P<0.001). The area under the receiver operating characteristic curve of ΔETCO 2 , ΔAUCp, and the combination of both to predict unsustained ROSC were 0.752 (95% CI 0.660-0.844), 0.883 (95% CI 0.818-0.948), and 0.902 (95% CI 0.842-0.962), respectively. CONCLUSION: Patients with unsustained ROSC have a poor prognosis. The combination of ΔETCO 2 and ΔAUCp showed signifi cant predictive value for unsustained ROSC.

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Section: Discussionmentioning

confidence: 71%

A novel predictor of unsustained return of spontaneous circulation in cardiac arrest patients through a combination of capnography and pulse oximetry: a multicenter observational study

Yang,

Tang,

Shao

et al. 2024

World Journal of Emergency Medicine

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“…The incidence and related risk factors for the complication of rearrest are still not well reported. Previous research on the subject of rearrest has mostly concentrated on the causes, effects and incidence of rearrest in the prehospital setting 25. In IHCA patients, Salcido et al found that rearrest occurred frequently after resuscitation and it was associated with a decreased likelihood of survival 26.…”

Section: Discussionmentioning

confidence: 99%

“…Previous research on the subject of rearrest has mostly concentrated on the causes, effects and incidence of rearrest in the prehospital setting. 25 In IHCA patients, Salcido et al found that rearrest occurred frequently after resuscitation and it was associated with a decreased likelihood of survival. 26 A retrospective cohort study of patients with OHCA or ICHA also suggested that rearrest was common and occurred early in the course of their postarrest care.…”

Section: Discussionmentioning

confidence: 99%

How to predict the death risk after an in-hospital cardiac arrest (IHCA) in intensive care unit? A retrospective double-centre cohort study from a tertiary hospital in China

Zhang,

Rao,

Ran

et al. 2023

BMJ Open

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ObjectivesOur objective is to develop a prediction tool to predict the death after in-hospital cardiac arrest (IHCA).DesignWe conducted a retrospective double-centre observational study of IHCA patients from January 2015 to December 2021. Data including prearrest diagnosis, clinical features of the IHCA and laboratory results after admission were collected and analysed. Logistic regression analysis was used for multivariate analyses to identify the risk factors for death. A nomogram was formulated and internally evaluated by the boot validation and the area under the curve (AUC). Performance of the nomogram was further accessed by Kaplan-Meier survival curves for patients who survived the initial IHCA.SettingIntensive care unit, Tongji Hospital, China.ParticipantsAdult patients (≥18 years) with IHCA after admission. Pregnant women, patients with ‘do not resuscitation’ order and patients treated with extracorporeal membrane oxygenation were excluded.InterventionsNone.Primary and secondary outcome measuresThe primary outcome was the death after IHCA.ResultsPatients (n=561) were divided into two groups: non-sustained return of spontaneous circulation (ROSC) group (n=241) and sustained ROSC group (n=320). Significant differences were found in sex (p=0.006), cardiopulmonary resuscitation (CPR) duration (p<0.001), total duration of CPR (p=0.014), rearrest (p<0.001) and length of stay (p=0.004) between two groups. Multivariate analysis identified that rearrest, duration of CPR and length of stay were independently associated with death. The nomogram including these three factors was well validated using boot calibration plot and exhibited excellent discriminative ability (AUC 0.88, 95% CI 0.83 to 0.93). The tertiles of patients in sustained ROSC group stratified by anticipated probability of death revealed significantly different survival rate (p<0.001).ConclusionsOur proposed nomogram based on these three factors is a simple, robust prediction model to accurately predict the death after IHCA.

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“…We used a validated series of Canadian Classification of Health Interventions codes to identify those who received cardiopulmonary resuscitation (IHZ30JN, IHZ3OJY) and International Statistical Classification of Disease and Related Health Problems (ICD-10) codes to identify incidents of cardiac arrest (I46.1, I46.2, I46.8, I49.0, I49.01, I49.02, R96.0, R96.1, R98, R99). 23 , 31 , 32 In the rare case where two arrests occurred within the study period, we used the first event only, given the worse odds of survival following rearrest 33 , 34 and to mitigate the risk of correlated observations. We excluded patients who were not residents of Ontario and those without a valid Ontario Health Insurance Plan number or birth date.…”

Section: Methodsmentioning

confidence: 99%

Prognosis of cardiac arrest in home care clients and nursing home residents: A population-level retrospective cohort study

et al. 2022

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Rearrest during hospitalisation in adult comatose out-of-hospital cardiac arrest patients: Risk factors and prognostic impact, and predictors of favourable long-term outcomes

Cited by 5 publications

References 33 publications

A novel predictor of unsustained return of spontaneous circulation in cardiac arrest patients through a combination of capnography and pulse oximetry: a multicenter observational study

A novel predictor of unsustained return of spontaneous circulation in cardiac arrest patients through a combination of capnography and pulse oximetry: a multicenter observational study

How to predict the death risk after an in-hospital cardiac arrest (IHCA) in intensive care unit? A retrospective double-centre cohort study from a tertiary hospital in China

Prognosis of cardiac arrest in home care clients and nursing home residents: A population-level retrospective cohort study

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