Prognostic factors for patients with accidental hypothermia: A multi-institutional retrospective cohort study

Okada, Yohei; Matsuyama, Tasuku; Morita, Sachiko; Ehara, Naoki; Miyamae, Nobuhiro; Jo, Takaaki; Sumida, Yorihisa; Okada, Nobunaga; Kitamura, Tetsuhisa; Iiduka, Ryoji

doi:10.1016/j.ajem.2018.06.025

Cited by 25 publications

(28 citation statements)

References 21 publications

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“…We described the patients and hospital characteristics as follows: sex age, season (Spring: March-June; Summer: July-August; Autumn: September-November; and Winter: December-February), and regions of Japan (Northern, Eastern, Western, and Southern). The season and area were de ned by the de nition of the Japan Meteorological Agency (details of the area are described in the supplementary materials) [18]. In addition, we described pre-hospital and in-hospital patient data as follows: bystander witness, bystander CPR, shockable on initial rhythm, advanced airway inserted by paramedics, cardiac rhythm on hospital arrival [return of spontaneous circulation (ROSC), shockable, pulseless electrical activity (PEA), asystole], core BT on arrival, and ECMO implementation.…”

Section: Discussionmentioning

confidence: 99%

Predictive Accuracy of Biomarkers for Survival Among Cardiac Arrest Patients With Hypothermia: A Prospective Observational Cohort Study in Japan

Okada

Irisawa

Yoshiya

et al. 2020

Preprint

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Background:There is little information onthe predictive accuracy of commonly used predictors, such as lactate,pH or serum potassium for the survival among out-of-hospital cardiac arrest (OHCA) patients with hypothermia. This studyaimed to identify the predictive accuracy of these biomarkers forsurvival among OHCA patients with hypothermia.Methods: In this retrospective study, we analyzed the data from a multicenter, prospective nationwide registry among OHCA patients transported to emergency departments in Japan (the JAAM-OHCA Registry). We included all adult (≥18 years) OHCA patients with hypothermia (≤32.0°C)who were registeredfrom June 2014 to December 2017and whose blood test results on hospital arrival were recorded. We calculated the predictive accuracy of pH and lactate for 1-month survival.Results: Of the 34,754 patients in the JAAM-OHCA database, we included 754 patients from 66 hospitals. The 1-monthsurvival was 5.8% (44/754). The areas under the curve of the predictors were as follows: pH 0.829[0.767–0.877] and lactate 0.843[0.793–0.882]. On setting the cutoff points of 6.9 in pH, and 120 mg/dL (13.3 mmol/L) in lactate, the predictors had a high sensitivity (lactate: 0.91, and pH 0.91) and a low LR- (lactate: 0.14 and pH 0.13), which are suitable to rule-out 1-month survival.Conclusion: Among adult OHCA patients with hypothermia, pH 6.9 and lactate 120 mg/dLcan predictivelyrule out 1-month survival.

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Section: Discussionmentioning

confidence: 99%

Predictive Accuracy of Biomarkers for Survival Among Cardiac Arrest Patients With Hypothermia: A Prospective Observational Cohort Study in Japan

Okada

Irisawa

Yoshiya

et al. 2020

Preprint

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“…In previous studies that have investigated predictors for mortality in urban patients with hypothermia, poor outcome was associated with shock, need for vasoactive drugs, 14 high BUN value, low platelet count, 2 indoor occurrence, 2,15 age 75 years old or older, need for assistance with activities of daily living (ADL), hemodynamic instability, and hyperkalemia. 5 Danzl et al 9 advocated a hypothermia outcome score consisting of five parameters: BUN value, systolic blood pressure, with or without prehospital cardiopulmonary resuscitation, need for tracheal intubation, and nasogastric tube placement. Elbaz et al 7 also suggested five parameters as risk factors for in-hospital death in patients with hypothermia in an urban setting in a desert climate: age ≥70 years, mean arterial pressure <90 mmHg, pH < 7.35, creatinine > 1.5 mg/dL, and confusion.…”

Section: Discussionmentioning

confidence: 99%

“…Many previous studies regarding accidental hypothermia have been undertaken in alpine settings, and few studies have been carried out in urban settings. Previous studies have reported that accidental hypothermia in urban settings is associated with a high mortality rate (12%, 26%, 29%, and 47%).…”

Section: Introductionmentioning

confidence: 99%

Derivation of a model to predict mortality in urban patients with accidental hypothermia: a retrospective observational study

Uemura

Kimura

Matsuda

et al. 2019

Acute Medicine & Surgery

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Aim: Accidental hypothermia in urban settings is associated with high mortality rates. However, the predictors of mortality remain under discussion. The purpose of this study was to evaluate prognostic factors and develop a prediction model in patients with accidental hypothermia in urban settings. Methods: We retrospectively reviewed medical records in patients with hypothermia brought to our hospital by ambulance in a 7year study period. Patients' records of survival discharge or in-hospital death and clinical data were collected from medical records. We analyzed factors to predict in-hospital death using multiple logistic regression analysis. Recursive partitioning analysis was used to construct a prediction model using predictors from multiple logistic regression analysis. Results: In the study period, 192 patients were included in this study. Of them, 154 patients were discharged alive and 38 patients died. Multiple logistic regression analysis revealed that in-hospital death was related to Glasgow Coma Scale (GCS) score, prothrombin timeinternational normalized ratio (PT-INR) value, and fibrin degradation product (FDP). Recursive partitioning analysis revealed that patients with accidental hypothermia could be divided into four groups: very high risk (FDP ≥ 14 µg/mL, PT-INR ≥ 1.4), high risk (FDP ≥ 14 µg/mL, PT-INR < 1.4), moderate risk (FDP < 14 µg/mL, GCS < 10), and low risk (FDP < 14 µg/mL, GCS ≥ 10). Conclusion: High FDP and PT-INR values and low GCS score on arrival at the emergency department were associated with in-hospital mortality in urban patients with hypothermia. A simple prediction model for grouping risk was developed using these predictors.

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“…This multicenter retrospective study aimed to clarify the relationship between the level of consciousness and core BT and to determine whether the level of consciousness could be used to predict severe hypothermia and in-hospital mortality among patients with AH. We used data from the J-point registry database [2,8], which has been previously described [2,[8][9][10]. Brie y, the registry includes information regarding patients with BT unknown or ≤35°C who were treated for AH in emergency departments between April 1, 2011 and March 31, 2016.…”

Section: Study Design and Settingmentioning

confidence: 99%

“…The JCS is widely accepted by paramedics and nurses working in the emergency department and is correlated with the GCS [14]. Therefore, when GCS data were missing, we imputed values for mildly impaired consciousness (JCS level 1, 1-3), moderately impaired consciousness (JCS level 2, 10-30), and severely impaired consciousness (JCS level 3, 100-300) based on previous reports [8,9]. sex, ADL, consciousness, systolic blood pressure, and heart rate.…”

Section: Exposurementioning

confidence: 99%

Clinical Relevance of Impaired Consciousness in Accidental Hypothermia: A Japanese Multicenter Retrospective Study

Fukuda¹,

Nozawa²,

Okada³

et al. 2020

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Background: Severe accidental hypothermia (AH) is a life-threatening condition, and early identification can enable transport to an appropriate medical facility. The Swiss staging model has been used to classify patients with AH, but little is known regarding the relationship between the degree of impaired consciousness and core body temperature (BT) in AH. This study aimed to clarify the relationship between the level of consciousness and core BT and determine whether the level of consciousness could be used to predict severe hypothermia and in-hospital mortality among patients with AH.Methods: We retrospectively investigated the clinical relevance of impaired consciousness in AH. We included adult patients with AH and excluded patients with out-of-hospital cardiac arrest. The patients were identified from the J-point registry, which contains information regarding patients treated for AH between April 1, 2011 and March 31, 2016 in any of the 12 participating institutions in Japan. The primary exposure of interest was the level of consciousness at hospital arrival. Odds ratios were calculated for severe hypothermia and in-hospital mortality.Results: Overall, 505 of the 572 patients in the registry were included. Compared to mildly impaired consciousness, the adjusted odds ratio for severe hypothermia was 3.3 (95% confidence interval [CI]: 1.7–6.3) for moderately impaired consciousness and 4.7 (95% CI: 2.4–9.1) for severely impaired consciousness. Severely impaired consciousness as a predictor severe hypothermia had a sensitivity of 0.44 (95% CI: 0.34–0.54), specificity of 0.78 (95% CI: 0.74–0.82), positive likelihood ratio of 2.04, and negative likelihood ratio of 0.71. Compared to mildly impaired consciousness, the adjusted odds ratio for in-hospital mortality was 1.7 (95% CI: 0.95–2.9) for moderately impaired consciousness and 2.1 (95% CI: 1.2–3.8) for severely impaired consciousness.Conclusions: Severely impaired consciousness was a reliable predictor of severe hypothermia and in-hospital mortality in patients with AH. Thus, in an urban out-of-hospital emergency setting, the level of impaired consciousness may be helpful for triaging patients to the appropriate hospital.

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Prognostic factors for patients with accidental hypothermia: A multi-institutional retrospective cohort study

Cited by 25 publications

References 21 publications

Predictive Accuracy of Biomarkers for Survival Among Cardiac Arrest Patients With Hypothermia: A Prospective Observational Cohort Study in Japan

Predictive Accuracy of Biomarkers for Survival Among Cardiac Arrest Patients With Hypothermia: A Prospective Observational Cohort Study in Japan

Derivation of a model to predict mortality in urban patients with accidental hypothermia: a retrospective observational study

Clinical Relevance of Impaired Consciousness in Accidental Hypothermia: A Japanese Multicenter Retrospective Study

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