Early prognostic impact of serum sodium level among out-of-hospital cardiac arrest patients: a nationwide multicentre observational study in Japan (the JAAM-OHCA registry)

Shida, Haruka; Matsuyama, Tasuku; Komukai, Sho; Irisawa, Taro; Yamada, Tomoki; Yoshiya, Kazuhisa; Park, Changhwi; Nishimura, Tetsuro; Ishibe, Takuya; Yagi, Yoshiki; Kishimoto, Masafumi; Kim, Sung Hoon; Hayashi, Yasuyuki; Sogabe, Taku; Morooka, Takaya; Sakamoto, Haruko; Suzuki, Keitaro; Nakamura, Fumiko; Nishioka, Norihiro; Okada, Yohei; Matsui, Satoshi; Yoshimura, Satoshi; Kimata, Shunsuke; Kawai, Shunsuke; Makino, Yuto; Iwami, Taku; Kitamura, Tetsuhisa

doi:10.1007/s00380-022-02020-3

Cited by 7 publications

(5 citation statements)

References 35 publications

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“…The search strategy identified a total of 11,834 records, of which 6914 were non‐duplicates. After applying all inclusion and exclusion criteria, 118 studies were included in the scoping review, as shown in Figure 1 11–128 …”

Section: Resultsmentioning

confidence: 99%

Intra‐arrest blood‐based biomarkers for out‐of‐hospital cardiac arrest: A scoping review

Benoit,

Hogan,

Connelly

et al. 2024

JACEP Open

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ObjectiveBlood‐based biomarkers play a central role in the diagnosis and treatment of critically ill patients, yet none are routinely measured during the intra‐arrest phase of out‐of‐hospital cardiac arrest (OHCA). Our objective was to describe methodological aspects, sources of evidence, and gaps in research surrounding intra‐arrest blood‐based biomarkers for OHCA.MethodsWe used scoping review methodology to summarize existing literature. The protocol was designed a priori following the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) Extension for Scoping Reviews. Inclusion criteria were peer‐reviewed scientific studies on OHCA patients with at least one blood draw intra‐arrest. We excluded in‐hospital cardiac arrest and animal studies. There were no language, date, or study design exclusions. We conducted an electronic literature search using PubMed and Embase and hand‐searched secondary literature. Data charting/synthesis were performed in duplicate using standardized data extraction templates.ResultsThe search strategy identified 11,834 records, with 118 studies evaluating 105 blood‐based biomarkers included. Only eight studies (7%) had complete reporting. The median number of studies per biomarker was 2 (interquartile range 1–4). Most studies were conducted in Asia (63 studies, 53%). Only 22 studies (19%) had blood samples collected in the prehospital setting, and only six studies (5%) had samples collected by paramedics. Pediatric patients were included in only three studies (3%). Out of eight predefined biomarker categories of use, only two were routinely assessed: prognostic (97/105, 92%) and diagnostic (61/105, 58%).ConclusionsDespite a large body of literature on intra‐arrest blood‐based biomarkers for OHCA, gaps in methodology and knowledge are widespread.

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Section: Resultsmentioning

confidence: 99%

Intra‐arrest blood‐based biomarkers for out‐of‐hospital cardiac arrest: A scoping review

Benoit,

Hogan,

Connelly

et al. 2024

JACEP Open

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“…The Na levels in both subphenotypes were similar and within the normal range but were slightly lower in SP2 patients than in SP1. Moreover, hypo-and hypernatremia were associated with a decreased probability of favorable neurological outcomes compared with normal Na [22] . It should also be noted that SP2 patients had lower Na even though they used sodium bicarbonate at a higher rate than SP1, suggesting that Na in SP2 patients might be lower before the use of sodium bicarbonate, and the difference between the two groups may be more signi cant.…”

Section: Discussionmentioning

confidence: 95%

Machine Learning Derivation of Two Cardiac Arrest Subphenotypes with Distinct Responses to Treatment

Zhang,

Wu,

et al. 2024

Preprint

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INTRODUCTION: Cardiac arrest (CA), characterized by its heterogeneity, poses challenges in patient management. This study aimed to identify clinical subphenotypes in CA patients to aid in patient classification, prognosis assessment, and treatment decision-making. METHODS: For this study, comprehensive data were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) 2.0 database. We excluded patients under 16 years old, those not initially admitted to the intensive care unit (ICU), or treated in the ICU for less than 72 hours. A total of 52 clinical parameters relevant to CA patients were selected for analysis. These included demographic data, vital signs, and laboratory parameters. After an extensive literature review and expert consultations, key factors such as temperature (T), sodium (Na), creatinine (CR), glucose (GLU), heart rate (HR), PaO2/FiO2 ratio (P/F), hemoglobin (HB), mean arterial pressure (MAP), platelets (PLT), and white blood cell count (WBC) were identified as the most significant for cluster analysis. Consensus cluster analysis was utilized to examine the mean values of these routine clinical parameters within the first 24 hours post-ICU admission to categorize patient classes. Furthermore, in-hospital and 28-day mortality rates of patients across different CA subphenotypes were assessed using multivariate logistic and Cox regression analysis. RESULTS: After applying exclusion criteria, 719 CA patients were included in the study, with a median age of 67.22 years (IQR: 55.50-79.34), of whom 63.28% were male. The analysis delineated two distinct subphenotypes: Subphenotype 1 (SP1) and Subphenotype 2 (SP2). Compared to SP1, patients in SP2 exhibited significantly higher levels of P/F, HB, MAP, PLT, and Na, but lower levels of T, HR, GLU, WBC, and CR. SP2 patients had a notably higher in-hospital mortality rate compared to SP1 (53.01% for SP2 vs. 39.36% for SP1, P < 0.001). 28-day mortality decreased continuously for both subphenotypes, with a more rapid decline in SP2. These differences remained significant after adjusting for potential covariates (adjusted OR = 1.82, 95% CI: 1.26–2.64, P = 0.002; HR = 1.84, 95% CI: 1.40–2.41, P < 0.001). CONCLUSIONS: The study successfully identified two distinct clinical subphenotypes of CA by analyzing routine clinical data from the first 24 hours following ICU admission. SP1 was characterized by a lower rate of in-hospital and 28-day mortality when compared to SP2. This differentiation could play a crucial role in tailoring patient care, assessing prognosis, and guiding more targeted treatment strategies for CA patients.

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“…Thus, in the general ICU population, hyponatremia and hypernatremia were independently associated with increased mortality [ 8 ]. One of the few studies of natremia in patients comatose after cardiac arrest and ROSC had a large sample size of 5160 and found that survival with a favourable outcome after 1 month was 17.6%, 8.2%, and 5.7% in the groups with normal, low, and high natremia, respectively [ 25 ]. In another retrospective study, early hypernatremia was associated with a lower probability of a favourable CPC after 1 year (aOR for each 1 mmol/L increase, 1.13; 95%CI 1.04–1.23; p = 0.004 [ 26 ]).…”

Section: Discussionmentioning

confidence: 99%

Dysnatremia at ICU admission and functional outcome of cardiac arrest: insights from four randomised controlled trials

Lascarrou,

Ermel,

Cariou

et al. 2023

Crit Care

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Purpose To evaluate the potential association between early dysnatremia and 6-month functional outcome after cardiac arrest. Methods We pooled data from four randomised clinical trials in post-cardiac-arrest patients admitted to the ICU with coma after stable return of spontaneous circulation (ROSC). Admission natremia was categorised as normal (135–145 mmol/L), low, or high. We analysed associations between natremia category and Cerebral Performance Category (CPC) 1 or 2 at 6 months, with and without adjustment on the modified Cardiac Arrest Hospital Prognosis Score (mCAHP). Results We included 1163 patients (581 from HYPERION, 352 from TTH48, 120 from COMACARE, and 110 from Xe-HYPOTHECA) with a mean age of 63 ± 13 years and a predominance of males (72.5%). A cardiac cause was identified in 63.6% of cases. Median time from collapse to ROSC was 20 [15–29] minutes. Overall, mean natremia on ICU admission was 137.5 ± 4.7 mmol/L; 211 (18.6%) and 31 (2.7%) patients had hyponatremia and hypernatremia, respectively. By univariate analysis, CPC 1 or 2 at 6 months was significantly less common in the group with hyponatremia (50/211 [24%] vs. 363/893 [41%]; P = 0.001); the mCAHP-adjusted odds ratio was 0.45 (95%CI 0.26–0.79, p = 0.005). The number of patients with hypernatremia was too small for a meaningful multivariable analysis. Conclusions Early hyponatremia was common in patients with ROSC after cardiac arrest and was associated with a poorer 6-month functional outcome. The mechanisms underlying this association remain to be elucidated in order to determine whether interventions targeting hyponatremia are worth investigating. Registration ClinicalTrial.gov, NCT01994772, November 2013, 21.

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Early prognostic impact of serum sodium level among out-of-hospital cardiac arrest patients: a nationwide multicentre observational study in Japan (the JAAM-OHCA registry)

Cited by 7 publications

References 35 publications

Intra‐arrest blood‐based biomarkers for out‐of‐hospital cardiac arrest: A scoping review

Intra‐arrest blood‐based biomarkers for out‐of‐hospital cardiac arrest: A scoping review

Machine Learning Derivation of Two Cardiac Arrest Subphenotypes with Distinct Responses to Treatment

Dysnatremia at ICU admission and functional outcome of cardiac arrest: insights from four randomised controlled trials

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