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Letter to the Editor| Volume 151, P215-216, June 2020

Risk factors associated with cardiac arrest

Published:April 13, 2020DOI:https://doi.org/10.1016/j.resuscitation.2020.02.045
Risk factors associated with cardiac arrest
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      To the Editor,
      We read the innovative article by Ohlsson et al.,
      • Ohlsson M.A.
      • Kennedy L.M.A.
      • Juhlin T.
      • et al.
      Risk prediction of future cardiac arrest by evaluation of a genetic risk score alone and in combination with traditional risk factors.
      Resuscitation. 2020; 146: 74-79https://doi.org/10.1016/j.resuscitation.2019.11.005
      the authors should be commended for combining polygenetic genetic risk scores with traditional risk factors to form a novel composite risk score to help identify individuals who will suffer cardiac arrest (CA). Though this study sounds scientific, some critical issues should be discussed.
      First, in the study by Ohlsson et al.,
      • Ohlsson M.A.
      • Kennedy L.M.A.
      • Juhlin T.
      • et al.
      Risk prediction of future cardiac arrest by evaluation of a genetic risk score alone and in combination with traditional risk factors.
      Resuscitation. 2020; 146: 74-79https://doi.org/10.1016/j.resuscitation.2019.11.005
      some variables were included and adjusted in their multivariate cox proportional model, however, anemia had not been included. Actually, anemia is closely correlated with CA, a Korean cohort study containing 494,948 subjects indicated that 1-unit decrease in hemoglobin was associated with 21–24% increase in the risk of sudden CA,
      • Kim I.J.
      • Yang P.S.
      • KimF T.H
      • et al.
      Relationship between anemia and the risk of sudden cardiac arrest – a nationwide cohort study in South Korea.
      Circ J. 2018; 82: 2962-2969https://doi.org/10.1253/circj.CJ-18-0046
      hence, anemia is an independent risk factor of CA and should not be ignored.
      Second, in the commented paper,
      • Ohlsson M.A.
      • Kennedy L.M.A.
      • Juhlin T.
      • et al.
      Risk prediction of future cardiac arrest by evaluation of a genetic risk score alone and in combination with traditional risk factors.
      Resuscitation. 2020; 146: 74-79https://doi.org/10.1016/j.resuscitation.2019.11.005
      factors like smoking, diabetes mellitus, hypertension, serum lipid, obesity were included and adjusted without checking the interactions between these covariates, nevertheless, these covariates might be correlated with each other,
      • Knol M.J.
      • Egger M.
      • Scott P.
      • et al.
      When one depends on the other: reporting of interaction in case–control and cohort studies.
      Epidemiology. 2009; 20: 161-166https://doi.org/10.1097/EDE.0b013e318186651
      the authors had better check the multicollinearity of these variables.
      Third, Table 1 showed that both systolic blood pressure (BP) and diastolic BP both distributed statistically differently between the control group and cardiac origin arrest group. As we all know, BP can be divided into 3 categories: hypertension, hypotension and normal BP. But in the study by Ohlsson et al.,
      • Ohlsson M.A.
      • Kennedy L.M.A.
      • Juhlin T.
      • et al.
      Risk prediction of future cardiac arrest by evaluation of a genetic risk score alone and in combination with traditional risk factors.
      Resuscitation. 2020; 146: 74-79https://doi.org/10.1016/j.resuscitation.2019.11.005
      only hypertension was chosen as covariate, in practice, hypotension or shock was more frequent in CA patients and shock was verified to be an independent risk factor of CA patients,
      • Siriphuwanun V.
      • Punjasawadwong Y.
      • Saengyo S.
      • et al.
      Incidences and factors associated with perioperative cardiac arrest in trauma patients receiving anesthesia.
      Risk Manag Healthc Policy. 2018; 11: 177-187https://doi.org/10.2147/RMHPS178950
      thus we suggest BP should be divided into 3 groups – hypertension group, hypotension group and normal BP group to reduce biases.
      Fourth, Ohlsson et al. tried to develop a novel composite risk score model for patients with future cardiac arrest, however, the events of cardiac origin CA (n = 181) and non-cardiac origin CA (n = 71) were so small which could result in non-significant statistical values and subsequent biases. Furthermore, internal and external validity procedures should be performed to check the comprehensive validity of this model to make the results more precise.
      • Steyerberg E.W.
      • Vergouwe Y.
      Towards better clinical prediction models: seven steps for development and an ABCD for validation.
      Eur Heart J. 2014; 35: 1925-1931https://doi.org/10.1093/eurheartj/ehu207
      In a word, the results of this innovative study should be interpreted prudently and more work should be done in the future.

      Conflict of interest

      None declared.

      Funding

      Guanghua Tang and Xianshi Zhou are funded by Guangdong Provincial Key Laboratory of Research on Emergency in TCM (No. 2017B030314176). The funders had no role in writing the manuscript or the decision to submit. The authors have reported that they have no relationships relevant to the contents of this paper to disclose.

      References

        • Ohlsson M.A.
        • Kennedy L.M.A.
        • Juhlin T.
        • et al.
        Risk prediction of future cardiac arrest by evaluation of a genetic risk score alone and in combination with traditional risk factors.
        Resuscitation. 2020; 146: 74-79https://doi.org/10.1016/j.resuscitation.2019.11.005
        View in Article
        • Kim I.J.
        • Yang P.S.
        • KimF T.H
        • et al.
        Relationship between anemia and the risk of sudden cardiac arrest – a nationwide cohort study in South Korea.
        Circ J. 2018; 82: 2962-2969https://doi.org/10.1253/circj.CJ-18-0046
        View in Article
        • Knol M.J.
        • Egger M.
        • Scott P.
        • et al.
        When one depends on the other: reporting of interaction in case–control and cohort studies.
        Epidemiology. 2009; 20: 161-166https://doi.org/10.1097/EDE.0b013e318186651
        View in Article
        • Siriphuwanun V.
        • Punjasawadwong Y.
        • Saengyo S.
        • et al.
        Incidences and factors associated with perioperative cardiac arrest in trauma patients receiving anesthesia.
        Risk Manag Healthc Policy. 2018; 11: 177-187https://doi.org/10.2147/RMHPS178950
        View in Article
        • Steyerberg E.W.
        • Vergouwe Y.
        Towards better clinical prediction models: seven steps for development and an ABCD for validation.
        Eur Heart J. 2014; 35: 1925-1931https://doi.org/10.1093/eurheartj/ehu207
        View in Article

      Article info

      Publication history

      Published online: April 13, 2020
      Received: February 8, 2020

      Identification

      DOI: https://doi.org/10.1016/j.resuscitation.2020.02.045

      Copyright

      © 2020 Elsevier B.V. All rights reserved.

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