Coagulopathy signature precedes and predicts severity of end‐organ heat stroke pathology in a mouse model

Proctor, Elizabeth A.; Dineen, Shauna M.; Nostrand, Stephen C. Van; Kuhn, Madison; Barrett, Christopher D.; Brubaker, Douglas K.; Yaffe, Michael B.; Lauffenburger, Douglas A.; Leon, Lisa R.

doi:10.1111/jth.14875

Cited by 33 publications

(25 citation statements)

References 33 publications

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“…Coagulopathy-promoting stimuli experienced in short succession might have produced a synergistic effect that explains the exacerbated heat stroke responses observed in PIC-injected mice. As described elsewhere, PIC-injected mice not only showed greater PLT exhaustion, but the PLTs were large and non-uniform in size, suggesting younger, more active platelets, with a possible contribution of the kidney, which we reported previously as showing evidence of coagulative necrosis in PIC-injected mice (Proctor et al, 2020). Depletion of PLTs results in a compromised endothelial layer, vascular leakage, increased cytokine levels and complement signalling (Claushuis et al, 2016;Morzunov, Khaiboullina, Jeor, Rizvanov, & Lombardi, 2015) and is correlated with decreased survival, increased bacterial loads, activation of coagulation and pro-inflammatory cytokines during infection (van den Boogaard et al, 2015).…”

Section: Discussionsupporting

confidence: 71%

Prior viral illness increases heat stroke severity in mice

Dineen

Ward

Leon

2020

Experimental Physiology

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It is hypothesized that prior illness exacerbates heat stroke (HS) in otherwise healthy organisms by augmenting hyperthermia during heat exposure or deactivating cellular pathways that protect against organ injury. To test these hypotheses, we injected telemetered male C57BL/6J mice with lipopolysaccharide (LPS; 50 µg kg −1 I.P.) or polyinosinic:polycytidylic acid (PIC; 100 µg I.P.) as a bacterial or a viral mimic, respectively, with saline (SAL; equivalent volume) as a control. Mice recovered for 48 or 72 h before HS (maximal core temperature = 42.4 • C). Platelet counts, cytokines, chemokines and organ injury were determined 48 or 72 h after injection (without heating) or at maximal core temperature and at 1 day of recovery from HS. In the absence of heat, PIC induced more robust signs of sickness and increased cytokines and chemokines (TNF-, RANTES, IP-10 and MIP-1) at 48 h, which was not observed with LPS (P < 0.05). Responses of both groups recovered by 72 h, although low platelet counts persisted after PIC (P < 0.05). Heat-induced hyperthermia was similar among mice injected with SAL, LPS and PIC; however, PIC-injected mice displayed more severe responses during recovery from HS, with reduced survival (48 h, 70 versus 100%; P < 0.05), deeper and longer post-HS hypothermia, greater reductions in platelets, elevated RANTES, IP-10, IL-6 and TNF-and greater duodenal injury (P < 0.05). By 72 h, survival from HS was no longer reduced in PIC-injected mice, although hypothermia, the reduction in platelets and elevated cytokines persisted. Our data indicate that prior illness exacerbates the severity of HS in the absence of signs of illness at the time of heat exposure and suggest that this is attributable to persistent coagulation and inflammatory reactions that might be targets for intervention to improve recovery.

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Section: Discussionsupporting

confidence: 71%

Prior viral illness increases heat stroke severity in mice

Dineen

Ward

Leon

2020

Experimental Physiology

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“…Similar synergistic effect was also explored as for the mechanism of increasing risk of heat stroke which related pathology following infection. Publication demonstrated coagulopathy might be a potential candidate for the mechanism since both heat and infection produced a coagulopathy dysfunction, which together create a positive feedback resulting in the collapse of the coagulation system [ 33 , 34 ].…”

Section: Discussionmentioning

confidence: 99%

NLRP3 ablation enhances tolerance in heat stroke pathology by inhibiting IL-1β-mediated neuroinflammation

Zhang

Zhao

et al. 2021

J Neuroinflammation

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Background Patients with prior illness are more vulnerable to heat stroke-induced injury, but the underlying mechanism is unknown. Recent studies suggested that NLRP3 inflammasome played an important role in the pathophysiology of heat stroke. Methods In this study, we used a classic animal heat stroke model. Prior infection was mimicked by using lipopolysaccharide (LPS) or lipoteichoic acid (LTA) injection before heat stroke (LPS/LTA 1 mg/kg). Mice survival analysis curve and core temperature (TC) elevation curve were produced. NLRP3 inflammasome activation was measured by using real-time PCR and Western blot. Mice hypothalamus was dissected and neuroinflammation level was measured. To further demonstrate the role of NLRP3 inflammasome, Nlrp3 knockout mice were used. In addition, IL-1β neutralizing antibody was injected to test potential therapeutic effect on heat stroke. Results Prior infection simulated by LPS/LTA injection resulted in latent inflammation status presented by high levels of cytokines in peripheral serum. However, LPS/LTA failed to cause any change in animal survival rate or body temperature. In the absence of LPS/LTA, heat treatment induced heat stroke and animal death without significant systemic or neuroinflammation. Despite a decreased level of IL-1β in hypothalamus, Nlrp3 knockout mice demonstrated no survival advantage under mere heat exposure. In animals with prior infection, their heat tolerance was severely impaired and NLRP3 inflammasome induced neuroinflammation was detected. The use of Nlrp3 knockout mice enhanced heat tolerance and alleviated heat stroke-induced death by reducing mice hypothalamus IL-1β production with prior infection condition. Furthermore, IL-1β neutralizing antibody injection significantly extended endotoxemic mice survival under heat stroke. Conclusions Based on the above results, NLRP3/IL-1β induced neuroinflammation might be an important mechanistic factor in heat stroke pathology, especially with prior infection. IL-1β may serve as a biomarker for heat stroke severity and potential therapeutic method.

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“…Although several variables such as preexisting medical conditions and coagulation abnormalities were recognized as risk factors for the occurrence or poor outcome of heatstroke 25 – 27 , they were not used in the development of our machine learning models because of the huge amount of missing data in the dataset. The performance of the model might improve if these variables are available for machine learning in the future structured dataset.…”

Section: Discussionmentioning

confidence: 99%

Machine learning-based mortality prediction model for heat-related illness

Hirano

Kondo

Hifumi

et al. 2021

Sci Rep

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In this study, we aimed to develop and validate a machine learning-based mortality prediction model for hospitalized heat-related illness patients. After 2393 hospitalized patients were extracted from a multicentered heat-related illness registry in Japan, subjects were divided into the training set for development (n = 1516, data from 2014, 2017–2019) and the test set (n = 877, data from 2020) for validation. Twenty-four variables including characteristics of patients, vital signs, and laboratory test data at hospital arrival were trained as predictor features for machine learning. The outcome was death during hospital stay. In validation, the developed machine learning models (logistic regression, support vector machine, random forest, XGBoost) demonstrated favorable performance for outcome prediction with significantly increased values of the area under the precision-recall curve (AUPR) of 0.415 [95% confidence interval (CI) 0.336–0.494], 0.395 [CI 0.318–0.472], 0.426 [CI 0.346–0.506], and 0.528 [CI 0.442–0.614], respectively, compared to that of the conventional acute physiology and chronic health evaluation (APACHE)-II score of 0.287 [CI 0.222–0.351] as a reference standard. The area under the receiver operating characteristic curve (AUROC) values were also high over 0.92 in all models, although there were no statistical differences compared to APACHE-II. This is the first demonstration of the potential of machine learning-based mortality prediction models for heat-related illnesses.

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Coagulopathy signature precedes and predicts severity of end‐organ heat stroke pathology in a mouse model

Cited by 33 publications

References 33 publications

Prior viral illness increases heat stroke severity in mice

Prior viral illness increases heat stroke severity in mice

NLRP3 ablation enhances tolerance in heat stroke pathology by inhibiting IL-1β-mediated neuroinflammation

Machine learning-based mortality prediction model for heat-related illness

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