Dysbiosis of intestinal microbiota to predict in-hospital mortality in critically ill patients: results of a prospective observational cohort study

Abstract Background: Despite the essential functions of the intestinal microbiota in human physiology, little research has been reported on the gut microbiota alteration in intensive care patients. This investigation aimed to explore the dysbacteriosis of intestinal flora in critically ill patients, and evaluate the prognostic performance of this dysbiosis to predict in-hospital mortality. Methods: A prospective cohort of patients were consecutively recruited at Intensive Care Units (ICUs) in Guangdong Provincial People's Hospital from March 2017 through October 2017. Acute Physiology and Chronic Health Evaluation (APACHE) II score and Sequential Organ Failure Assessment (SOFA) score were assessed, and fecal samples were taken for examination within 24 hours of ICU admission. The taxonomic composition of intestinal microbiome was determined using 16S rDNA gene sequencing. Patients were divided into survival and death group based on the outcomes in hospital. The two groups were statistically compared using the independent samples t test and Metastats analysis. Genera of bacteria showing significantly different abundance between groups were assessed for predictors of in-hospital death. The prognostic value of bacterial abundance alone and in combination with APACHE II or SOFA score were evaluated using the area under the receiver operating characteristic curve (AUROC). Results: Among the 61 patients that were examined, a total of 12 patients (19.7%) died during hospital stay. Bifidobacterium differed significantly in abundance between survival and death group ( P =0.031). The AUROC of Bifidobacterium abundance identifying in-hospital death at a cut-off probability of 0.0041 was 0.718 (95% confidence interval [CI], 0.588-0.826). The panel of Bifidobacterium abundance plus SOFA (AUROC, 0.882; 95% CI, 0.774-0.950) outperformed SOFA (AUROC, 0.649; 95% CI, 0.516-0.767; P =0.012) and Bifidobacterium abundance alone ( P =0.007). The panel of Bifidobacterium abundance plus APACHE II (AUROC, 0.876; 95% CI, 0.766-0.946) outperformed APACHE II (AUROC, 0.724; 95% CI, 0.595-0.831; P =0.035) and Bifidobacterium abundance alone ( P =0.012). Conclusions: Dysbiosis of intestinal microbiota with variable degree of reduction in Bifidobacterium abundance exhibits promising performance in predicting in-hospital mortality, and provides incremental prognostic value to existing scoring systems in the adult intensive care unit (ICU) setting.

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Outcomes of Critically Ill Gynecological Cancer Patients Admitted to Intensive Care Unit

American Journal of Hospice and Palliative Medicine® ◽

10.1177/1049909112437028 ◽

2012 ◽

Vol 30 (1) ◽

pp. 7-11 ◽

Cited By ~ 4

Author(s):

Silvio A. Ñamendys-Silva ◽

María O. González-Herrera ◽

Julia Texcocano-Becerra ◽

Angel Herrera-Gómez

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Prognostic Factors ◽

Mortality Rate ◽

Hospital Mortality ◽

Critically Ill ◽

Critically Ill Patients ◽

Gynecological Cancer ◽

Apache Ii ◽

Apache Ii Score

Purpose: To assess the characteristics of critically ill patients with gynecological cancer, and to evaluate their prognosis. Methods: Fifty-two critically ill patients with gynecological cancer admitted to intensive care unit (ICU) were included. Univariate and multivariate logistic regressions were used to identify factors associated with hospital mortality. Results: Thirty-five patients (67.3%) had carcinoma of the cervix uteri and 11 (21.2%) had ovarian cancer. The mortality rate in the ICU was 17.3% (9 of 52) and hospital mortality rate were 23%(12 of 52). In the multivariate analysis, independent prognostic factors for hospital mortality were vasopressor use (odds ratio [OR] = 8.60, 95% confidence interval [CI] 2.05-36; P = .03) and the Acute Physiology and Chronic Health Evaluation (APACHE) II score (OR = 1.43, 95% CI 1.01-2.09; P = .048). Conclusions: The independent prognostic factors for hospital mortality were the need for vasopressors and the APACHE II score.

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Combining Sequential Organ Failure Assessment (SOFA) Score with Acute Physiology and Chronic Health Evaluation (APACHE) II Score to Predict Hospital Mortality of Critically Ill Patients

Anaesthesia and Intensive Care ◽

10.1177/0310057x0703500409 ◽

2007 ◽

Vol 35 (4) ◽

pp. 515-521 ◽

Cited By ~ 41

Author(s):

K. M. Ho

Keyword(s):

Hospital Mortality ◽

Critically Ill ◽

Sofa Score ◽

Critically Ill Patients ◽

Characteristic Curve ◽

Apache Ii ◽

Brier Score ◽

Apache Ii Score ◽

Failure Assessment ◽

Predict Hospital Mortality

The ability to accurately adjust for the severity of illness in outcome studies of critically ill patients is essential. Previous studies have showed that Sequential Organ Failure Assessment (SOFA) score and Acute Physiology and Chronic Health Evaluation (APACHE) II score can predict hospital mortality of critically ill patients. The effects of combining these two scores to predict hospital mortality of critically ill patients has not been evaluated. This cohort study evaluated the performance of combining the APACHE II score with SOFA score in predicting hospital mortality of critically ill patients. A total of 1,311 consecutive adult patients admitted to a tertiary 22-bed multidisciplinary intensive care unit (ICU) in Western Australia were considered. The APACHE II, Admission SOFA, Delta SOFA and maximum SOFA score were all related to hospital survival in the univariate analyses. Combining Max SOFA (area under receiver operating characteristic curve 0.875 vs. 0.858, P=0.014; Nagelkerke R2: 0.411 vs. 0.371; Brier Score: 0.086 vs. 0.090) or Delta SOFA score (area under receiver operating characteristic curve 0.874 vs. 0.858, P=0.003; Nagelkerke R2: 0.412 vs. 0.371; Brier Score: 0.086 vs. 0.090) with the APACHE II score improved the discrimination and overall performance of the predictions when compared with using the APACHE II score alone, especially in the emergency ICU admissions. Combining Max SOFA or Delta SOFA score with the APACHE II score may improve the accuracy of risk adjustment in outcome studies of critically ill patients.

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The Impact of Serum Glucose on the Predictive Value of Serum Lactate for Hospital Mortality in Critically Ill Surgical Patients

Disease Markers ◽

10.1155/2019/1578502 ◽

2019 ◽

Vol 2019 ◽

pp. 1-10 ◽

Cited By ~ 2

Author(s):

Xue Chen ◽

Jianbin Bi ◽

Jia Zhang ◽

Zhaoqing Du ◽

Yifan Ren ◽

...

Keyword(s):

Hospital Mortality ◽

Critically Ill ◽

Sofa Score ◽

Critically Ill Patients ◽

High Glucose ◽

Predictive Ability ◽

Apache Ii ◽

Apache Ii Score ◽

Glucose Levels ◽

Glucose Group

Background. Lactate has been widely used as a risk indicator of outcomes in critically ill patients due to its ready measurement and good predictive ability. However, the interconnections between lactate metabolism and glucose metabolism have not been sufficiently explored, yet. In this study, we aimed to investigate whether glucose levels could influence the predictive ability of lactate and design a more comprehensive strategy to assess the in-hospital mortality of critically ill patients. Methods. We analyzed the clinical data of 293 critically ill patients. The primary outcome was in-hospital mortality. The logistic regression analysis and the area under the receiver operating characteristic curve (AUROC) were applied to evaluate the predictive ability of lactate in association with glucose. Results. The lactate level showed significant association with in-hospital mortality, and its predictive ability was also comparable to other prognostic scores such as the SOFA score and APACHE II score. We further divided 293 patients into three groups based on glucose levels: low-glucose group (<7 mmol/L), medium-glucose group (7-9 mmol/L), and high-glucose group (>9 mmol/L). The lactate level was associated with in-hospital mortality in the low- and high- glucose groups, but not in the medium-glucose group, whereas the SOFA score and APACHE II score were associated with in-hospital mortality in all three glucose groups. The AUROC of lactate in the medium-glucose group was also the lowest among the three glucose groups, indicating a decrease in its predictive ability. Conclusions. Our findings demonstrated that the predictive ability of lactate to assess in-hospital mortality could be influenced by glucose levels. In the medium glucose level (i.e., 7-9 mmol/L), lactate was inadequate to predict in-hospital mortality and the SOFA score; the APACHE II score should be utilized as a complementation in order to obtain a more accurate prediction.

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Feasibility of transitioning from APACHE II to SAPS III as prognostic model in a Brazilian general intensive care unit. A retrospective study

Sao Paulo Medical Journal ◽

10.1590/1516-3180.2013.8120014 ◽

2014 ◽

Vol 133 (3) ◽

pp. 199-205 ◽

Cited By ~ 6

Author(s):

Ary Serpa Neto ◽

Murillo Santucci Cesar de Assunção ◽

Andréia Pardini ◽

Eliézer Silva

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Retrospective Study ◽

Hospital Mortality ◽

Critically Ill ◽

Predictive Models ◽

Critically Ill Patients ◽

Goodness Of Fit ◽

Apache Ii ◽

Goodness Of Fit Test

CONTEXT AND OBJECTIVE: Prognostic models reflect the population characteristics of the countries from which they originate. Predictive models should be customized to fit the general population where they will be used. The aim here was to perform external validation on two predictive models and compare their performance in a mixed population of critically ill patients in Brazil.DESIGN AND SETTING: Retrospective study in a Brazilian general intensive care unit (ICU).METHODS: This was a retrospective review of all patients admitted to a 41-bed mixed ICU from August 2011 to September 2012. Calibration (assessed using the Hosmer-Lemeshow goodness-of-fit test) and discrimination (assessed using area under the curve) of APACHE II and SAPS III were compared. The standardized mortality ratio (SMR) was calculated by dividing the number of observed deaths by the number of expected deaths.RESULTS: A total of 3,333 ICU patients were enrolled. The Hosmer-Lemeshow goodness-of-fit test showed good calibration for all models in relation to hospital mortality. For in-hospital mortality there was a worse fit for APACHE II in clinical patients. Discrimination was better for SAPS III for in-ICU and in-hospital mortality (P = 0.042). The SMRs for the whole population were 0.27 (confidence interval [CI]: 0.23 - 0.33) for APACHE II and 0.28 (CI: 0.22 - 0.36) for SAPS III.CONCLUSIONS: In this group of critically ill patients, SAPS III was a better prognostic score, with higher discrimination and calibration power.

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Risk factors for mortality in critically ill patients with COVID-19: a multicenter retrospective case-control study

BMC Infectious Diseases ◽

10.1186/s12879-021-06300-7 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Jinghua Gao ◽

Li Zhong ◽

Ming Wu ◽

Jingjing Ji ◽

Zheying Liu ◽

...

Keyword(s):

Risk Factors ◽

Organ Failure ◽

Critically Ill ◽

Sofa Score ◽

Lymphocyte Count ◽

Cox Regression ◽

Survival Curve ◽

Apache Ii ◽

Apache Ii Score ◽

Hospital Death

Abstract Background Coronavirus disease 2019 (COVID-19) has spread around the world, until now, the number of positive and death cases is still increasing. Therefore, it remains important to identify risk factors for death in critically patients. Methods We collected demographic and clinical data on all severe inpatients with COVID-19. We used univariable and multivariable Cox regression methods to determine the independent risk factors related to likelihood of 28-day and 60-day survival, performing survival curve analysis. Results Of 325 patients enrolled in the study, Multi-factor Cox analysis showed increasing odds of in-hospital death associated with basic illness (hazard ratio [HR] 6.455, 95% Confidence Interval [CI] 1.658–25.139, P = 0.007), lymphopenia (HR 0.373, 95% CI 0.148–0.944, P = 0.037), higher Sequential Organ Failure Assessment (SOFA) score on admission (HR 1.171, 95% CI 1.013–1.354, P = 0.033) and being critically ill (HR 0.191, 95% CI 0.053–0.687, P = 0.011). Increasing 28-day and 60-day mortality, declining survival time and more serious inflammation and organ failure were associated with lymphocyte count < 0.8 × 109/L, SOFA score > 3, Acute Physiology and Chronic Health Evaluation II (APACHE II) score > 7, PaO2/FiO2 < 200 mmHg, IL-6 > 120 pg/ml, and CRP > 52 mg/L. Conclusions Being critically ill and lymphocyte count, SOFA score, APACHE II score, PaO2/FiO2, IL-6, and CRP on admission were associated with poor prognosis in COVID-19 patients.

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Abstract 15293: Noninvasive Echocardiographic Cardiac Power Output Predicts Mortality in Cardiac Intensive Care Unit Patients

Circulation ◽

10.1161/circ.142.suppl_3.15293 ◽

2020 ◽

Vol 142 (Suppl_3) ◽

Author(s):

Barry Burstein ◽

Vidhu Anand ◽

Bradley Ternus ◽

Meir Tabi ◽

Nandan S Anavekar ◽

...

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Hospital Mortality ◽

Critically Ill ◽

Power Output ◽

Critically Ill Patients ◽

Cardiac Intensive Care Unit ◽

Cardiac Power ◽

The Mean ◽

Cardiac Intensive Care

Introduction: A low cardiac power output (CPO), measured invasively, identifies critically ill patients at increased risk of mortality. CPO can also be measured non-invasively with transthoracic echocardiography (TTE), although prognostic data in critically ill patients is not available. Hypothesis: Reduced CPO measured by TTE is associated with increased hospital mortality in cardiac intensive care unit (CICU) patients. Methods: Using a database of CICU patients admitted between 2007 and 2018, we identified patients with TTE within one day (before or after) of CICU admission who had data necessary for calculation of CPO. Multivariable logistic regression determined the relationship between CPO and adjusted hospital mortality. Results: We included 5,585 patients with a mean age of 68.3±14.8 years, including 36.7% females. Admission diagnoses included acute coronary syndrome (ACS) in 57%, heart failure (HF) in 50%, cardiac arrest (CA) in 12%, and cardiogenic shock (CS) in 13%. The mean left ventricular ejection fraction (LVEF) was 47±16%, and the mean CPO was 1.0±0.4 W. CPO was inversely associated with the risk of hospital mortality (Figure A), including among patients with ACS, HF, and CS (Figure B). On multivariable analysis, lower CPO was associated with higher hospital mortality (OR 0.96 per 0.1 W, 95% CI 0.0.93-0.99, p=0.03). Hospital mortality was highest in patients with low CPO coupled with reduced LVEF, increased vasopressor requirements, or higher admission lactate. Hospital mortality was higher among patients with a CPO <0.6 W (adjusted OR 1.57, 95% CI 1.13-2.19, p = 0.007), particularly in the presence of admission lactate level >4 mmol/L (50.9%). Conclusions: Echocardiographic CPO was inversely associated with hospital mortality in CICU patients, particularly among patients with increased lactate and vasopressor requirements. Routine measurement of CPO provides important information beyond LVEF and should be considered in CICU patients.

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Serum potassium levels and outcomes in critically ill patients in the medical intensive care unit

Journal of International Medical Research ◽

10.1177/0300060517744427 ◽

2018 ◽

Vol 46 (3) ◽

pp. 1254-1262 ◽

Cited By ~ 3

Author(s):

Surat Tongyoo ◽

Tanuwong Viarasilpa ◽

Chairat Permpikul

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Critically Ill ◽

Serum Potassium ◽

Critically Ill Patients ◽

Medical Intensive Care Unit ◽

Apache Ii ◽

Apache Ii Score ◽

Icu Mortality ◽

Medical Intensive Care

Objective To compare the outcomes of patients with and without a mean serum potassium (K+) level within the recommended range (3.5–4.5 mEq/L). Methods This prospective cohort study involved patients admitted to the medical intensive care unit (ICU) of Siriraj Hospital from May 2012 to February 2013. The patients’ baseline characteristics, Acute Physiology and Chronic Health Evaluation II (APACHE II) score, serum K+ level, and hospital outcomes were recorded. Patients with a mean K+ level of 3.5 to 4.5 mEq/L and with all individual K+ values of 3.0 to 5.0 mEq/L were allocated to the normal K+ group. The remaining patients were allocated to the abnormal K+ group. Results In total, 160 patients were included. Their mean age was 59.3±18.3 years, and their mean APACHE II score was 21.8±14.0. The normal K+ group comprised 74 (46.3%) patients. The abnormal K+ group had a significantly higher mean APACHE II score, proportion of coronary artery disease, and rate of vasopressor treatment. An abnormal serum K+ level was associated with significantly higher ICU mortality and incidence of ventricular fibrillation. Conclusion Critically ill patients with abnormal K+ levels had a higher incidence of ventricular arrhythmia and ICU mortality than patients with normal K+ levels.

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Clinical Significance of Bioimpedance Spectroscopy in Critically Ill Patients

Journal of Intensive Care Medicine ◽

10.1177/0885066617702591 ◽

2017 ◽

Vol 34 (6) ◽

pp. 495-502 ◽

Cited By ~ 3

Author(s):

Shang-Feng Yang ◽

Ching-Min Tseng ◽

I-Fan Liu ◽

Shin-Hung Tsai ◽

Wein-Shung Kuo ◽

...

Keyword(s):

Hospital Mortality ◽

Critically Ill ◽

Critically Ill Patients ◽

Fluid Management ◽

Laboratory Data ◽

Acute Stage ◽

Volume Control ◽

Hospital Death ◽

Icu Admission ◽

The Third

Background: Early fluid resuscitation is a key aspect in the successful management of critically ill patients, but the optimal goal for volume control after the acute stage of critical illness remains unclear. This study aimed to evaluate the prognostic value of bioimpedance spectrometry for fluid management in critically ill patients. Methods: In this prospective observational study, patients who consented to participate were screened within the first 24 hours of admission to a medical intensive care unit (ICU) from February 4, 2015, to January 31, 2016. Information on demographics, comorbidities, primary reasons for admission, baseline laboratory data, and ventilator or inotropic use were documented. Data of fluid intake, fluid output, and body weight were recorded for the first 3 days of ICU admission. Bioimpedance spectrometry was performed on the first and third days after ICU admission. All participants were followed until death or hospital discharge. Results: Of the 140 enrolled patients (median age: 70 years, interquartile range: 60-77 years), 23 (16.4%) patients died during hospitalization. Independent predictors of hospital mortality were Acute Physiology and Chronic Health Evaluation II scores (per 1 point increase, odds ratio [OR]: 1.101) and overhydration (OH) volume on the first day (per 1 L increase, OR: 1.216). Compared to normal OH status (OH volume between −1 and 1 L), hyper OH status (OH volume < −1 L) on the third day after ICU admission was an independent predictor of hospital death (OR: 7.609). Normal OH status on the third day was associated with greater numbers of ICU-free and ventilator-free days. Conclusion: Bioimpedance spectrometry can be used to predict outcomes in critically ill patients. Increased OH volume on day 1 and hyper OH volume on day 3 of ICU admission are associated with a greater risk of hospital mortality. Volume status on day 3 is associated with durations of ventilator use and ICU stay.

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