Hyperthermia is a predictor of high mortality in patients with sepsis

Shen, Yanfei; Lou, Yangfang; Zhu, Shiping

doi:10.1186/s13054-020-03263-0

Cited by 11 publications

(10 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Body temperature is a main area of focus in studies on sepsis [ 28 ]. For instance, two recent studies on body temperature and sepsis showed that hyperpyrexia was associated with poor prognosis in septic patients [ 29 , 30 ]. In addition, a randomized controlled trial demonstrated that fever control by external cooling, significantly reduced early mortality in septic shock [ 31 ].…”

Section: Discussionmentioning

confidence: 99%

Development and validation of a score to predict mortality in ICU patients with sepsis: a multicenter retrospective study

et al. 2021

View full text Add to dashboard Cite

Background Early and accurate identification of septic patients at high risk for ICU mortality can help clinicians make optimal clinical decisions and improve the patients’ outcomes. This study aimed to develop and validate (internally and externally) a mortality prediction score for sepsis following admission in the ICU. Methods We extracted data retrospectively regarding adult septic patients from one teaching hospital in Wenzhou, China and a large multi-center critical care database from the USA. Demographic data, vital signs, laboratory values, comorbidities, and clinical outcomes were collected. The primary outcome was ICU mortality. Through multivariable logistic regression, a mortality prediction score for sepsis was developed and validated. Results Four thousand two hundred and thirty six patients in the development cohort and 8359 patients in three validation cohorts. The Prediction of Sepsis Mortality in ICU (POSMI) score included age ≥ 50 years, temperature < 37 °C, Respiratory rate > 35 breaths/min, MAP ≤ 50 mmHg, SpO2 < 90%, albumin ≤ 2 g/dL, bilirubin ≥ 0.8 mg/dL, lactate ≥ 4.2 mmol/L, BUN ≥ 21 mg/dL, mechanical ventilation, hepatic failure and metastatic cancer. In addition, the area under the receiver operating characteristic curve (AUC) for the development cohort was 0.831 (95% CI, 0.813–0.850) while the AUCs ranged from 0.798 to 0.829 in the three validation cohorts. Moreover, the POSMI score had a higher AUC than both the SOFA and APACHE IV scores. Notably, the Hosmer–Lemeshow (H–L) goodness-of-fit test results and calibration curves suggested good calibration in the development and validation cohorts. Additionally, the POSMI score still exhibited excellent discrimination and calibration following sensitivity analysis. With regard to clinical usefulness, the decision curve analysis (DCA) of POSMI showed a higher net benefit than SOFA and APACHE IV in the development cohort. Conclusion POSMI was validated to be an effective tool for predicting mortality in ICU patients with sepsis.

show abstract

Section: Discussionmentioning

confidence: 99%

Development and validation of a score to predict mortality in ICU patients with sepsis: a multicenter retrospective study

et al. 2021

View full text Add to dashboard Cite

show abstract

“…There has been recent interest in determining the factors related to the outcome of sepsis. Lactic acid, renal insu ciency, thrombocytopenia, lung infection, and high fever are considered risk factors for poor sepsis outcomes [6,[18][19][20], while plasma albumin and plasma IgG levels can be protective factors [21,22]. However, there are relatively few studies on the risk factors related to the prognosis of sepsis patients with lung infection.…”

Section: Discussionmentioning

confidence: 99%

Risk Factor Analysis and Nomogram for Predicting In-Hospital Mortality in Patients with Sepsis and Lung Infection

Ren¹,

Zhang²,

Xu³

et al. 2021

Preprint

View full text Add to dashboard Cite

BackgroundLung infection is a common cause of sepsis, and patients with sepsis and lung infection are more ill and have a higher mortality rate than sepsis patients without lung infection. We constructed a nomogram prediction model to accurately evaluate the prognosis of and provide treatment advice for patients with sepsis and lung infection.MethodsData were retrospectively extracted from the Medical Information Mart for Intensive Care (MIMIC-III) open-source clinical database. The definition of Sepsis 3.0[10] was used, which includes patients with life-threatening organ dysfunction caused by an uncontrolled host response to infection, and SOFA score ≥2.The nomogram prediction model was constructed from the training set using logistic regression analysis, and was then internally validated and underwent sensitivity analysis.ResultsThe risk factors of age, lactate, temperature, oxygenation index, BUN, lactate, Glasgow Coma Score(GCS), liver disease, cancer, organ transplantation, Troponin T(TnT), neutrophil-to-lymphocyte ratio(NLR), and CRRT, MV, and vasopressor use were included in the nomogram. Compared with the Sequential Organ Failure Assessment (SOFA) score and Simplified Acute Physiology Score II (SAPSII), the nomogram had better discrimination ability, with areas under the receiver operating characteristic curve (AUROC) of 0.743 (95% confidence interval [95% CI]=0.713–0.773, p < 0.001) and 0.746 (95% CI=0.699–0.790, p < 0.001) in the training and validation sets, respectively. The calibration plot indicated that the nomogram was adequate for predicting the in-hospital mortality risk in both sets. The decision-curve analysis(DCA) of the nomogram revealed that it provided net benefits for clinical use over using the SOFA score and SAPSII in both sets. ConclusionOur new nomogram is a convenient tool for accurate predictions of in-hospital mortality among patients with sepsis and lung infection. Treatment strategies that improve the factors considered relevant in the model could increase in-hospital survival for these ICU patients.

show abstract

“…Although large clinical trials on targeted temperature management have not shown benefits in sepsis, national guidelines recommend normothermia in patients with trauma [ 5 ]. In a large adult cohort, sepsis-related fever was associated with worse outcome [ 6 ], whereas fever control using external cooling to maintain normothermia reduced mortality in septic shock [ 3 ]. Surprisingly, external forced-air warming of normothermic septic patients was associated with lower mortality when compared to afebrile patients [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

Ex Vivo Evaluation of Glutamine Treatment in Sepsis and Trauma in a Human Peripheral Blood Mononuclear Cells Model

et al. 2023

View full text Add to dashboard Cite

We aimed to assess the lipopolysaccharide (LPS), or heat shock (HS) induction, and glutamine-modulating effects on heat shock protein-90α (HSP90α) and cytokines in an ex vivo model using peripheral blood mononuclear cells (PBMCs). The PBMCs of patients with septic shock, trauma-related systemic inflammatory response syndrome (SIRS), and healthy subjects were incubated with 1 μg/mL LPS at 43 °C (HS). Glutamine 10 mM was added 1 hour before or after induction or not at all. We measured mRNA HSP90α, monocyte (m) and lymphocyte (l) HSP90α proteins, interleukin (IL)-1b, -6, -8, -10, tumor necrosis factor-α (TNF-α), and monocyte chemoattractant protein-1 (MCP-1) supernatant levels. Heat shock increased the HSP90α mRNA and mHSP90α in all groups (10-fold in sepsis, p < 0.001 and p = 0.047, respectively). LPS induced the mHSP90α and lHSP90α in healthy (p < 0.001) and mHSP90α in SIRS (p = 0.004) but not in sepsis. LPS induced the cytokines at 24 and 48 h in all groups, especially in trauma (p < 0.001); HS only induced the IL-8 in healthy (p = 0.003) and septic subjects (p = 0.05). Glutamine at 10 mM before or after stimulation did not alter any induction effect of LPS or HS on HSP90α mRNA and mHSP90α protein in sepsis. In SIRS, glutamine before LPS decreased the mHSP90α but increased it when given after HS (p = 0.018). Before or after LPS (p = 0.049) and before HS (p = 0.018), glutamine decreased the lHSP90α expression in sepsis but increased it in SIRS when given after HS (p = 0.003). Regarding cytokines, glutamine enhanced the LPS-induced MCP-1 at 48 h in healthy (p = 0.011), SIRS (p < 0.001), and sepsis (p = 0.006). In conclusion, glutamine at 10 mM, before or after LPS and HS, modulates mHSP90α and lHSP90α in sepsis and SIRS differently and unpredictably. Although it does not alter the stimulation effect on interleukins, glutamine enhances the LPS induction effect on supernatant MCP-1 in all groups. Future research should seek to elucidate better the impact of glutamine and temperature modulation on HSP90α and MCP-1 pathways in sepsis and trauma.

show abstract

Hyperthermia is a predictor of high mortality in patients with sepsis

Cited by 11 publications

References 5 publications

Development and validation of a score to predict mortality in ICU patients with sepsis: a multicenter retrospective study

Development and validation of a score to predict mortality in ICU patients with sepsis: a multicenter retrospective study

Risk Factor Analysis and Nomogram for Predicting In-Hospital Mortality in Patients with Sepsis and Lung Infection

Ex Vivo Evaluation of Glutamine Treatment in Sepsis and Trauma in a Human Peripheral Blood Mononuclear Cells Model

Contact Info

Product

Resources

About