scholarly journals Pulmonary Hypertension an Independent Risk Factor for Death in Intensive Care Unit: Correlation of Hemodynamic Factors with Mortality

2015 ◽  
Vol 9 ◽  
pp. CCRPM.S22199 ◽  
Author(s):  
Ghulam Saydain ◽  
Aamir Awan ◽  
Palaniappan Manickam ◽  
Paul Kleinow ◽  
Safwan Badr
Keyword(s):  
Intensive Care Unit ◽  
Pulmonary Hypertension ◽  
Risk Factor ◽  
Intensive Care ◽  
Pulmonary Artery ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Independent Risk Factor ◽  
Apache Ii ◽  
Hemodynamic Parameters

Objective Critically ill patients with pulmonary hypertension (PH) pose additional challenges due to the existence of right ventricular (RV) dysfunction. The purpose of this study was to assess the impact of hemodynamic factors on the outcome. Methods We reviewed the records of patients with a diagnosis of PH admitted to the intensive care unit. In addition to evaluating traditional hemodynamic parameters, we defined severe PH as right atrial pressure >20 mmHg, mean pulmonary artery pressure >55 mmHg, or cardiac index (CI) <2 L/min/m2. We also defined the RV functional index (RFI) as pulmonary artery systolic pressure (PASP) adjusted for CI as PASP/CI; increasing values reflect RV dysfunction. Results Fifty-three patients (mean age 60 years, 72% women, 79% Blacks), were included in the study. Severe PH was present in 68% of patients who had higher Sequential Organ Failure Assessment (SOFA) score (6.8 ± 3.3 vs 3.8 ± 1.6; P = 0.001) and overall in-hospital mortality (36% vs 6%; P = 0.02) compared to nonsevere patients, although Acute Physiology and Chronic Health Evaluation (APACHE) II scores (19.9 ± 7.5 vs 18.5 ± 6.04; P = 0.52) were similar and sepsis was more frequent among nonsevere PH patients (31 vs 64%; P = 0.02). Severe PH ( P = 0.04), lower mean arterial pressure ( P = 0.04), and CI ( P = 0.01); need for invasive ventilation ( P = 0.02) and vasopressors ( P = 0.03); and higher SOFA ( P = 0.001), APACHE II ( P = 0.03), pulmonary vascular resistance index (PVRI) ( P = 0.01), and RFI ( P = 0.004) were associated with increased mortality. In a multivariate model, SOFA [OR = 1.45, 95% confidence interval (C.I.) = 1.09-1.93; P = 0.01], PVRI (OR = 1.12, 95% C.I. = 1.02-1.24; P = 0.02), and increasing RFI (OR = 1.06, 95% C.I. = 1.01-1.11; P = 0.01) were independently associated with mortality. Conclusion PH is an independent risk factor for mortality in critically ill patients. Composite factors rather than individual hemodynamic parameters are better predictors of outcome. Monitoring of RV function using composite hemodynamic factors resulting in specific interventions is likely to improve survival and needs to be studied further.

scholarly journals New-onset atrial fibrillation in critically ill patients with coronavirus disease 2019 (COVID-19)

2021 ◽  
Author(s):  
BİŞAR ERGÜN ◽  
BEGUM ERGAN ◽  
Melih Kaan SÖZMEN ◽  
Mehmet Nuri YAKAR ◽  
Murat KÜÇÜK ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Intensive Care Unit ◽  
Risk Factor ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Independent Risk Factor ◽  
Onset Atrial Fibrillation ◽  
New Onset

Abstract Objectives: To determine the incidence, risk factors, and outcomes of new-onset atrial fibrillation (NOAF) in a cohort of critically ill patients with coronavirus disease 2019 (COVID-19). Methods: We conducted a retrospective study on patients admitted to the intensive care unit (ICU) with a diagnosis of COVID-19. NOAF was defined as atrial fibrillation that was detected after diagnosis of COVID-19 without a prior history. The primary outcome of the study was the effect of NOAF on mortality in critically ill COVID-19 patients. Results: We enrolled 248 eligible patients. NOAF incidence was 14.9% (n=37), and 78% of patients (n=29) were men in NOAF positive group. Median age of the NOAF group was 79.0 (interquartile range, 71.5-84.0). Hospital mortality was higher in the NOAF group (87% vs 67%, respectively, p=0.019). However, in multivariate analysis, NOAF was not an independent risk factor for hospital mortality (OR 1.42, 95% CI 0.40–5.09, p=0.582) Conclusions: The incidence of NOAF was 14.9% in critically ill COVID-19 patients. Hospital mortality was higher in the NOAF group. However, NOAF was not an independent risk factor for hospital mortality in patients with COVID-19. Keywords: Atrial fibrillation, critical care, intensive care unit, COVID-19, mortality, hospital mortality

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

2018 ◽  
Vol 46 (3) ◽  
pp. 1254-1262 ◽  
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.

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

2012 ◽  
Vol 30 (1) ◽  
pp. 7-11 ◽  
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.

Can nights and weekends hospitalizations be classified as a risk factor for critically ill patients at an intensive care unit?

2017 ◽  
Vol 42 ◽  
pp. 417-418
Author(s):  
Paulo Cesar Gottardo ◽  
Ana Beatriz Nepomuceno Cunha ◽  
Ciro Leite Mendes ◽  
Igor Mendonça do Nascimento ◽  
Rurick Chumacero Vanderlei ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Risk Factor ◽  
Intensive Care ◽  
Critically Ill ◽  
Critically Ill Patients

Comparison of Cardiac Output Determined by Bioimpedance, Thermodilution, and the Fick Method

2005 ◽  
Vol 14 (1) ◽  
pp. 40-45 ◽  
Author(s):  
Milo Engoren ◽  
Daniel Barbee
Keyword(s):  
Intensive Care Unit ◽  
Cardiac Output ◽  
Intensive Care ◽  
Pulmonary Artery ◽  
Pulmonary Artery Catheter ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Mean Difference ◽  
Heterogenous Population ◽  
Method Bias

• Background Cardiac output can be determined by using a variety of methods.• Objectives To determine the precision and bias between 3 methods for determining cardiac output: bioimpedance, thermodilution, and the Fick method.• Methods Cardiac output was determined by using bioimpedance via neck and thorax patches and thermodilution via pulmonary artery catheter in 46 patients in the intensive care unit. A subset of 15 patients also had cardiac output determined by using the Fick method.• Results Mean (SD) cardiac output in all patients was 6.3 (2.2) L/min by thermodilution and 5.6 (2.0) L/min by bioimpedance. In the 15 patients in whom all 3 methods were used, mean cardiac output was 6.0 (1.7) L/min by thermodilution, 5.3 (1.7) L/min by bioimpedance, and 8.6 (4.5) L/min by the Fick method. Bias and precision (mean difference ± 2 SDs) were 0.7 ± 2.9 L/min between thermodilution and bioimpedance, 1.7 ± 3.8 L/min between the Fick method and thermodilution, and 2.4 ± 4.7 L/min between the Fick method and bioimpedance.• Conclusion Bioimpedance, thermodilution, and Fick determinations of cardiac outputs are not interchangeable in a heterogenous population of critically ill patients.

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

2014 ◽  
Vol 133 (3) ◽  
pp. 199-205 ◽  
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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