J-point Registry Research Articles

Association between the severity of hypothermia and in-hospital mortality in patients with infectious diseases: The J-Point registry.

Hypothermia is associated with poor prognosis in patients with sepsis. However, no studies have explored the correlation between the severity of hypothermia and prognosis. Using data from the Japanese accidental hypothermia network registry (J-Point registry), we examined adult patients aged ≥18 years with infectious diseases whose initial body temperature was ≤35°C from April 1, 2011 to March 31, 2016, in 12 centers. Patients were divided into three groups according to their body temperature: Tertile 1 (T1) (32.0-35.0°C), Tertile 2 (T2) (28.0-31.9°C), and Tertile 3 (T3) (<28.0°C). In-hospital mortality was employed as a metric to assess outcomes. We conducted a multivariate logistic regression analysis to investigate the relationship between the three categories and the occurrence of in-hospital mortality. A total of 572 patients were registered, and 170 eligible patients were identified. Of these patients, 55 were in T1 (32.0-35.0°C), 76 in T2 (28.0-31.9°C), and 39 in T3 (<28.0°C) groups. The overall in-hospital mortality rate in accidental hypothermia (AH) patients with infectious diseases was 34.1%. The in-hospital mortality rates in the T1, T2, and T3 groups were 34.5%, 36.8%, and 28.2%, respectively. The multivariable analysis demonstrated no significant differences regarding in-hospital mortality among the three groups (T2 vs. T1, adjusted odds ratio [OR]: 1.29; 95% confidence interval [CI]: 0.58-2.89 and T3 vs. T1, adjusted OR: 0.83; 95% CI: 0.30-2.31). In this multicenter retrospective observational study, hypothermia severity was not associated with in-hospital mortality in AH patients with infectious diseases.

Clinical relevance of impaired consciousness in accidental hypothermia: a Japanese multicenter retrospective study.

AimThis study aimed to investigate the association between level of impaired consciousness and severe hypothermia (<28°C) and to evaluate the association between level of impaired consciousness and inhospital mortality among accidental hypothermia patients.MethodsThis was a multicenter retrospective study using the J‐Point registry database, which includes data regarding patients whose core body temperature was 35.0°C or less and who were treated as accidental hypothermia in emergency departments between April 1, 2011 and March 31, 2016. We estimated adjusted odds ratios of the level of impaired consciousness for severe hypothermia less than 28°C and inhospital mortality using a logistic regression model.ResultsThe study included 505 of 572 patients in the J‐Point registry. Relative to mildly impaired consciousness (Glasgow Coma Scale [GCS] 13–15), the adjusted odds ratios for severe hypothermia less than 28°C were: moderate (GCS 9–12), 3.26 (95% confidence interval [CI], 1.69–6.25); and severe (GCS < 9), 4.68 (95% CI, 2.40–9.14). Relative to mildly impaired consciousness (GCS 13–15), the adjusted odds ratios for inhospital mortality were: moderate (GCS9–12), 1.65 (95% CI, 0.95–2.88); and severe (GCS < 9), 2.10 (95% CI, 1.17–3.78).ConclusionThe level of impaired consciousness in patients with accidental hypothermia was associated with severe hypothermia and inhospital mortality.

Machine learning-based prediction models for accidental hypothermia patients

BackgroundAccidental hypothermia is a critical condition with high risks of fatal arrhythmia, multiple organ failure, and mortality; however, there is no established model to predict the mortality. The present study aimed to develop and validate machine learning-based models for predicting in-hospital mortality using easily available data at hospital admission among the patients with accidental hypothermia.MethodThis study was secondary analysis of multi-center retrospective cohort study (J-point registry) including patients with accidental hypothermia. Adult patients with body temperature 35.0 °C or less at emergency department were included. Prediction models for in-hospital mortality using machine learning (lasso, random forest, and gradient boosting tree) were made in development cohort from six hospitals, and the predictive performance were assessed in validation cohort from other six hospitals. As a reference, we compared the SOFA score and 5A score.ResultsWe included total 532 patients in the development cohort [N = 288, six hospitals, in-hospital mortality: 22.0% (64/288)], and the validation cohort [N = 244, six hospitals, in-hospital mortality 27.0% (66/244)]. The C-statistics [95% CI] of the models in validation cohorts were as follows: lasso 0.784 [0.717–0.851] , random forest 0.794[0.735–0.853], gradient boosting tree 0.780 [0.714–0.847], SOFA 0.787 [0.722–0.851], and 5A score 0.750[0.681–0.820]. The calibration plot showed that these models were well calibrated to observed in-hospital mortality. Decision curve analysis indicated that these models obtained clinical net-benefit.ConclusionThis multi-center retrospective cohort study indicated that machine learning-based prediction models could accurately predict in-hospital mortality in validation cohort among the accidental hypothermia patients. These models might be able to support physicians and patient’s decision-making. However, the applicability to clinical settings, and the actual clinical utility is still unclear; thus, further prospective study is warranted to evaluate the clinical usefulness.

Impact of rewarming rate on the mortality of patients with accidental hypothermia: analysis of data from the J-Point registry

BackgroundAccidental hypothermia (AH) is defined as an involuntary decrease in core body temperature to < 35 °C. The management of AH has been progressing over the last few decades, and numerous techniques for rewarming have been validated. However, little is known about the association between rewarming rate (RR) and mortality in patients with AH.MethodThis was a multicentre chart review study of patients with AH visiting the emergency department of 12 institutions in Japan from April 2011 to March 2016 (Japanese accidental hypothermia network registry, J-Point registry). We retrospectively registered patients using the International Classification of Diseases, Tenth Revision code T68: ‘hypothermia’. We excluded patients whose body temperatures were unknown or ≥ 35 °C, who could not be rewarmed, whose rewarmed temperature or rewarming time was unknown, those aged < 18 years, or who or whose family members had refused to join the registry. RR was calculated based on the body temperature on arrival at the hospital, time of arrival at the hospital, the documented temperature during rewarming, and time of the temperature documentation. RR was classified into the following five groups: ≥2.0 °C/h, 1.5–< 2.0 °C/h, 1.0–< 1.5 °C/h, 0.5–< 1.0 °C/h, and < 0.5 °C/h. The primary outcome of this study was in-hospital mortality. The association between RR and in-hospital mortality was evaluated using multivariate logistic regression analysis.ResultDuring the study, 572 patients were registered in the J-Point registry, and 481 patients were included in the analysis. The median body temperature on arrival to the hospital was 30.7 °C (interquartile range [IQR], 28.2 °C–32.4 °C), and the median RR was 0.85 °C/h (IQR, 0.53 °C/h–1.31 °C/h). The in-hospital mortality rates were 19.3% (11/57), 11.1% (4/36), 14.4% (15/104), 20.1% (35/175), and 34.9% (38/109) in the ≥2.0 °C/h, 1.5–< 2.0 °C/h, 1.0–< 1.5 °C/h, 0.5–< 1.0 °C/h, and < 0.5 °C/h groups, respectively. Multivariate regression analysis revealed that in-hospital mortality rate increased with each 0.5 °C/h decrease in RR (adjusted odds ratio, 1.49; 95% confidence interval, 1.15–1.94; Ptrend < 0.01).ConclusionThis study showed that slower RR is independently associated with in-hospital mortality.

Prognostic ability of the sequential organ failure assessment score in accidental hypothermia: a multi-institutional retrospective cohort study

BackgroundSevere accidental hypothermia (AH) is life threatening. Thus, prognostic prediction in AH is essential to rapidly initiate intensive care. Several studies on prognostic factors for AH are known, but none have been established. We clarified the prognostic ability of the Sequential Organ Failure Assessment (SOFA) score in comparison with previously reported prognostic factors among patients with AH.MethodsThe J-point registry database is a multi-institutional retrospective cohort study for AH in 12 Japanese emergency departments. From this registry, we enrolled patients who were treated at the intensive care unit (ICU) in various critical care medical centers. In-hospital mortality was the primary outcome. We investigated the discrimination ability of each candidate prognostic factor and the in-hospital mortality by applying the logistic regression models with areas under the receiver operating characteristic curve (AUROC) with 95% confidence interval (CI).ResultsOf the 572 patients with AH registered in the J-point registry, 220 were eligible for the analyses. The in-hospital mortality was 23.2%. The AUROC of the SOFA score (0.80; 95% CI: 0.72–0.86) was the highest among all factors. The other factors were serum potassium (0.65; 95% CI: 0.55–0.73), lactate (0.67; 95% CI: 0.57–0.75), quick SOFA (qSOFA) (0.55; 95% CI: 0.46–0.65), systemic inflammatory response syndrome (SIRS) (0.60; 95% CI: 0.50–0.69), and 5A severity scale (0.77; 95% CI: 0.68–0.84).DiscussionAlthough serum potassium and lactate had relatively good discrimination ability as mortality predictors, the SOFA score had slightly better discrimination ability. The reason is that lactate and serum potassium were mainly reflected by the hemodynamic state; conversely, the SOFA score is a comprehensive score of organ failure, basing on six different scores from the respiratory, cardiovascular, hepatic, coagulation, renal, and neurological systems. Meanwhile, the qSOFA and SIRS scores underestimated the severity, with low discrimination abilities for mortality.ConclusionsThe SOFA score demonstrated better discrimination ability as a mortality predictor among all known prognostic factors in patients with AH.

Indoor Versus Outdoor Occurrence in Mortality of Accidental Hypothermia in Japan: The J-Point Registry.

The impact of the location where accidental hypothermia (AH) occurs has not been fully investigated thus far. This was a multicenter retrospective study of patients with a body temperature ≤35°C obtained at the emergency department of 12 hospitals in Japan between April 2011 and March 2016. We divided the patients into two groups according to the location where AH occurred (indoor group versus outdoor group). The association between each location of the occurrence of AH and in-hospital mortality was evaluated via a multivariable logistic regression analysis. The primary outcome of this study was in-hospital death. The secondary outcomes were the lengths of ICU and hospital stay. A total of 572 patients were enrolled in the hypothermia database, and 537 patients were included in the analyses. A total of 119 and 418 patients experienced hypothermia with outdoor and indoor occurrence, respectively. The indoor group was older and had worse activities of daily living compared with the outdoor group. With regard to the outcome, the proportion of in-hospital death was higher in the indoor group than in the outdoor group (28.2% [118/418] vs. 10.9% [13/119], p < 0.001). The multivariable logistic regression analysis showed that the adjusted odds ratio of the indoor group was 2.48 (95% confidence interval, 1.18-5.17). In terms of secondary outcomes, both the lengths of ICU and hospital stay of the survivors were longer in the indoor group than in the outdoor group. Hypothermia with indoor occurrence accounts for ∼78% of the total AH cases in this study, and the proportion of in-hospital deaths was higher in the indoor group than in the outdoor group. Warnings about the indoor onset of AH must be provided, and countermeasures for the prevention and early recognition of AH with indoor occurrence must be taken.

The development and validation of a \u201c5A\u201d severity scale for predicting in-hospital mortality after accidental hypothermia from J-point registry data

BackgroundAccidental hypothermia is a serious condition that requires immediate and accurate assessment to determine severity and treatment. Currently, accidental hypothermia is evaluated using the Swiss grading system which uses core body temperature and clinical findings; however, research has shown that core body temperature is not associated with in-hospital mortality in urban settings. Therefore, we developed and validated a severity scale for predicting in-hospital mortality among urban Japanese patients with accidental hypothermia.MethodsData for this multi-center retrospective cohort study were obtained from the J-point registry. We included patients with accidental hypothermia who were admitted to an emergency department. The total cohort was divided into a development cohort and validation cohort, based on the location of each institution. We developed a logistic regression model for predicting in-hospital mortality using the development cohort and assessed its internal validity using bootstrapping. The model was then subjected to external validation using the validation cohorts.ResultsAmong the 572 patients in the J-point registry, 532 were ultimately included and divided into the development cohort (N = 288, six hospitals, in-hospital mortality 22.0%) and the validation cohort (N = 244, six hospitals, in-hospital mortality 27.0%). The 5 “A” scoring system based on age, activities-of-daily-living status, near arrest, acidemia, and serum albumin level was developed based on the variables’ coefficients in the development cohort. In the validation cohort, the prediction performance was validated.ConclusionOur “5A” severity scoring system could accurately predict the risk of in-hospital mortality among patients with accidental hypothermia.

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

IntroductionIn cases of severe accidental hypothermia (AH) in urban areas, the prognostic factors are unknown. We identified factors associated with in-hospital mortality in patients with moderate-to-severe AH in urban areas of Japan. MethodThe J-Point registry database is a multi-institutional retrospective cohort study for AH in 12 Japanese emergency departments. From this registry, we enrolled patients whose core body temperature was 32 °C or less on admission. In-hospital death was the primary outcome of this study. We investigated the association between each candidate prognostic factor and in-hospital death by applying the multivariate logistic regression analyses with adjusted odds ratios (AORs) and their 95% confidence interval [CI] as the effect variables. ResultsOf 572 patients registered in the J-point registry, 358 hypothermic patients were eligible for analyses. Median body temperature was 29.2 °C (interquartile range, 27.0 °C–30.8 °C). In-hospital deaths comprised 26.3% (94/358) of all study patients. Factors associated with in-hospital death were age ≥ 75 years (AOR, 3.09; 95% CI, 1.31–7.27), need for assistance with activities of daily living (ADL; AOR, 3.06; 95% CI, 1.68–5.59), hemodynamic instability (AOR, 2.49; 95% CI, 1.32–4.68), and hyperkalemia (≥5.6 mEq/L; AOR, 2.65; 95% CI, 1.13–6.21). ConclusionThe independent prognostic factors associated with in-hospital mortality of patients with moderate-to-severe AH in urban areas of Japan were age ≥ 75 years, need for assistance with ADL, hemodynamic instability, and hyperkalemia.

Characteristics and outcomes of accidental hypothermia in Japan: the J-Point registry

BackgroundAccidental hypothermia (AH) has higher incidence and mortality in geriatric populations. Japan has a rapidly ageing population, and little is known about the epidemiology of hypothermia in this country.MethodsWe created...