scholarly journals Serum lactate is an independent predictor of hospital mortality in critically ill patients in the emergency department: a retrospective study

2017 ◽  
Vol 25 (1) ◽  
Author(s):  
Ralphe Bou Chebl ◽  
Christopher El Khuri ◽  
Ali Shami ◽  
Eva Rajha ◽  
Nagham Faris ◽  
...  
Keyword(s):  
Emergency Department ◽  
Retrospective Study ◽  
Hospital Mortality ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Independent Predictor ◽  
Serum Lactate

scholarly journals Increased Length of Stay of Critically Ill Patients in the Emergency Department Associated with Higher In-hospital Mortality

2021 ◽  
Vol 25 (11) ◽  
pp. 1221-1225
Author(s):  
Ankur Verma ◽  
Amit Vishen ◽  
Meghna Haldar ◽  
Sanjay Jaiswal ◽  
Rinkey Ahuja ◽  
...  
Keyword(s):  
Emergency Department ◽  
Length Of Stay ◽  
Hospital Mortality ◽  
Critically Ill ◽  
Critically Ill Patients

Association of delayed time in the emergency department with the clinical outcomes for critically ill patients

QJM ◽  
2020 ◽  
Author(s):  
S Lin ◽  
S Ge ◽  
W He ◽  
M Zeng
Keyword(s):  
Emergency Department ◽  
Cohort Study ◽  
Hospital Mortality ◽  
Clinical Outcomes ◽  
Critically Ill ◽  
Waiting Time ◽  
Critically Ill Patients ◽  
Retrospective Cohort ◽  
Stratified Analysis ◽  
Delayed Time

Summary Background Previous studies have shown the association of waiting time in the emergency department with the prognosis of critically ill patients, but these studies linking the waiting time to clinical outcomes have been inconsistent and limited by small sample size. Aim To determine the relationship between the waiting time in the emergency department and the clinical outcomes for critically ill patients in a large sample population. Design A retrospective cohort study of 13 634 patients. Methods We used the Medical Information Mart for Intensive Care III database. Multivariable logistic regression was used to determine the independent relationships of the in-hospital mortality rate with the delayed time and different groups. Interaction and stratified analysis were conducted to test whether the effect of delayed time differed across various subgroups. Results After adjustments, the in-hospital mortality in the ≥6 h group increased by 38.1% (OR 1.381, 95% CI 1.221–1.562). Moreover, each delayed hour was associated independently with a 1.0% increase in the risk of in-hospital mortality (OR 1.010, 95% CI 1.008–1.010). In the stratified analysis, intensive care unit (ICU) types, length of hospital stay, length of ICU stay, simplified acute physiology score II and diagnostic category were found to have interactions with ≥6 h group in in-hospital mortality. Conclusions In this large retrospective cohort study, every delayed hour was associated with an increase in mortality. Furthermore, clinicians should be cautious of patients diagnosed with sepsis, liver/renal/metabolic diseases, internal hemorrhage and cardiovascular disease, and if conditions permit, they should give priority to transferring to the corresponding ICUs.

Effect of emergency critical care nurses and emergency department boarding time on in-hospital mortality in critically ill patients

2021 ◽  
Vol 41 ◽  
pp. 120-124
Author(s):  
Jason Nesbitt ◽  
Tsuyoshi Mitarai ◽  
Garrett K. Chan ◽  
Jennifer G. Wilson ◽  
Kian Niknam ◽  
...  
Keyword(s):  
Emergency Department ◽  
Critical Care ◽  
Hospital Mortality ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Critical Care Nurses

scholarly journals Differences in Characteristics, Hospital Care, and Outcomes between Acute Critically Ill Emergency Department Patients Receiving Palliative Care and Usual Care

2021 ◽  
Vol 18 (23) ◽  
pp. 12546
Author(s):  
Julia Chia-Yu Chang ◽  
Che Yang ◽  
Li-Ling Lai ◽  
Hsien-Hao Huang ◽  
Shih-Hung Tsai ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Emergency Department ◽  
Palliative Care ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Usual Care ◽  
Critically Ill ◽  
Resource Utilization ◽  
Critically Ill Patients ◽  
Hospital Care

Background: The early integration of palliative care in the emergency department (ED-PC) provides several benefits, including improved quality of life with optimal comfort measures, and symptom control. Whether palliative care could affect the intensive care unit admissions, hospital care and resource utilization requires further investigation. Aim: To determine the differences in inpatient characteristics, hospital care, survival, and resource utilization between patients receiving palliative care (ED-PC) and usual care (UC). Design: Retrospective observational study. Setting/participants: We enrolled consecutive, acute, critically ill patients admitted to the emergency intensive care unit at Taipei Veterans General Hospital from 1 February 2018 to 31 January 2020. Results: A total of 1273 patients were evaluated for unmet palliative care needs; 685 patients received ED-PC and 588 received UC. The palliative care patients were more severely frail (AOR 2.217 (1.295–3.797), p = 0.004), had functional deterioration with three ADLs (AOR 1.348 (1.040–1.748), p = 0.024), biopsychosocial discomfort (AOR 1.696 (1.315–2.187), p < 0.001), higher Taiwan Triage and Acuity Scale 1 (p = 0.024), higher in-hospital mortality (AOR 1.983 (1.540–2.555), p < 0.001), were four times more likely to sign an DNR (AOR 4.536 (2.522–8.158), p < 0.001), and were twice as likely to sign an DNR at admission (AOR 2.1331.619–2.811), p < 0.001). Palliative care patients received less epinephrine (AOR 0.424 (0.265–0.678), p < 0.001), more frequent withdrawal of an endotracheal tube (AOR 8.780 (1.122–68.720), p = 0.038), and more narcotics (AOR1.675 (1.132–2.477), p = 0.010). Palliative care patients exhibited lower 7-day, 30-day, and 90-day survival rates (p < 0.001). There was no significant difference in the hospital length of stay (LOS) (21.2 ± 26.6 vs. 21.7 ± 20.6, p = 0.709) nor total hospital expenses (293,169 ± 350,043 vs. 294,161 ± 315,275, p = 0.958). Conclusion: Acute critically ill patients receiving palliative care were more frail, more critical, and had higher in-hospital mortality. Palliative care patients received less epinephrine, more endotracheal extubation, and more narcotics. There was no difference in the hospital LOS or hospital costs between the palliative and usual care groups. The synthesis of ED-PC is new but achievable with potential benefits to align care with patient goals.

scholarly journals Pulmonary Hypertension at Admission predicts ICU Mortality in Elderly Critically ill with Severe COVID-19 Pneumonia: retrospective cohort study

2022 ◽  
Author(s):  
Marko Kurnik ◽  
Helena Božič ◽  
Anže Vindišar ◽  
Petra Kolar ◽  
Matej Podbregar
Keyword(s):  
Elderly Patients ◽  
Hospital Mortality ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Independent Predictor ◽  
Strong Predictor ◽  
Invasive Mechanical Ventilation ◽  
Icu Mortality ◽  
Non Invasive ◽  
Icu Stay

Abstract BackgroundPoint-of-care ultrasound (POCUS) is a useful diagnostic tool for non-invasive assessment of critically ill patients. Mortality of elderly patients with COVID-19 pneumonia is high and there is still scarcity of definitive predictors. Aim of our study was to assess the prediction value of combined lung and heart POCUS data on mortality of elderly critically ill patients with severe COVID-19 pneumonia.MethodsThis was a retrospective observational study. Data of patients older than 70 years, with severe COVID-19 pneumonia admitted to 25-bed mixed, level 3, intensive care unit (ICU) was analyzed retrospectively. POCUS was performed at admission; our parameters of interest were pulmonary artery systolic pressure (PASP) and presence of diffuse B-line pattern (B-pattern) on lung ultrasound.ResultsBetween March 2020 and February 2021, 117 patients aged 70 years or more (average age 77±5 years) were included. Average length of ICU stay was 10.7±8.9 days. High-flow oxygenation, non-invasive ventilation and invasive mechanical ventilation were at some point used to support 36/117 (31%), 39/117 (33%) and 75/117 (64%) patients respectively. ICU mortality was 50.9%. ICU stay was shorter in survivors (8.8±8.3 vs 12.6±9.3 days, p=0.02). PASP was lower in ICU survivors (32.5±9.8 vs. 40.4±14.3 mmHg, p=0.024). B-pattern was more often detected in non-survivals (35/59 (59%) vs. 19/58 (33%), p=0.005). PASP and B-pattern at admission were both univariate predictors of mortality. PASP at admission was an independent predictor of ICU (OR 1.0683, 95%CI: 1.0108-1.1291, p=0.02) and hospital (OR 1.0813, 95%CI 1.0125-1.1548, p=0.02) mortality. Ventilator associated pneumonia (VAP) was a strong predictor of ICU and hospital mortality.ConclusionsPASP at admission is an independent predictor of ICU and hospital mortality of elderly patients with severe COVID-19 pneumonia. During ICU stay development of VAP was a strong predictor of ICU and hospital mortality.

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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