Resource Utilization and Outcome in Gravely Ill Intensive Care Unit Patients With Predicted In-hospital Mortality Rates of 95% or Higher by APACHE III Scores: The Relationship With Physician and Family Expectations

2005 ◽  
Vol 80 (2) ◽  
pp. 166-173 ◽  
Author(s):  
Keith H. Berge ◽  
Deborah R. Maiers ◽  
David P. Schreiner ◽  
Stephen M. Jewell ◽  
Perry S. Bechtle ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Resource Utilization ◽  
Mortality Rates ◽  
Family Expectations ◽  
Apache Iii ◽  
The Relationship

scholarly journals Platelet-Lymphocyte Ratio as a New Predictor of In-hospital Mortality in Cardiac Intensive Care Unit Patients

2021 ◽  
Author(s):  
Guangyao Zhai ◽  
Biyang Zhang ◽  
Jianlong Wang ◽  
Yuyang Liu ◽  
Yujie Zhou
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Cardiovascular Diseases ◽  
Hospital Mortality ◽  
Subgroup Analysis ◽  
Cardiac Intensive Care Unit ◽  
Lymphocyte Ratio ◽  
Platelet Lymphocyte Ratio ◽  
Cardiac Intensive Care ◽  
The Relationship

Abstract Background: It has been discovered that both inflammation and platelet aggregation could cause crucial effect on the occurrence and development of cardiovascular diseases. As a combination of platelet and lymphocyte, platelet-lymphocyte ratio (PLR) was proved to be correlated with the severity as well as prognosis of cardiovascular diseases. Exploring the relationship between PLR and in-hospital mortality in cardiac intensive care unit (CICU) patients was the purpose of this study. Method: PLR was calculated by dividing platelet count by lymphocyte count. All patients were grouped by PLR quartiles and the primary outcome was in-hospital mortality. The independent effect of PLR was determined by binary logistic regression analysis. The curve in line with overall trend was drawn by local weighted regression (Lowess). Subgroup analysis was used to determine the relationship between PLR and in-hospital mortality in different subgroups. Result: We included 5577 CICU patients. As PLR quartiles increased, in-hospital mortality increased significantly (Quartile 4 vs Quartile 1: 13.9 vs 8.3, P <0.001). After adjusting for confounding variables, PLR was proved to be independently associated with increased risk of in-hospital mortality (Quartile 4 vs Quartile 1: OR, 95% CI: 1.99, 1.46-2.71, P<0.001, P for trend <0.001). The Lowess curves showed a positive relationship between PLR and in-hospital mortality. The subgroup analysis revealed that patients with low Acute Physiology and Chronic Health Evaluation IV (APACHE IV) or with less comorbidities had higher risk of mortality for PLR. Further, PLR quartiles had positive relation with length of CICU stay (Quartile 4 vs Quartile 1: 2.7, 1.6-5.2 vs 2.1, 1.3-3.9, P<0.001), and the length of hospital stay (Quartile 4 vs Quartile 1: 7.9, 4.6-13.1 vs 5.8, 3.3-9.8, P<0.001). Conclusion: PLR was independently associated with in-hospital mortality in CICU patients.

scholarly journals Platelet-lymphocyte ratio as a new predictor of in-hospital mortality in cardiac intensive care unit patients

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Guangyao Zhai ◽  
Jianlong Wang ◽  
Yuyang Liu ◽  
Yujie Zhou
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Cardiovascular Diseases ◽  
Hospital Mortality ◽  
Subgroup Analysis ◽  
Cardiac Intensive Care Unit ◽  
Lymphocyte Ratio ◽  
Platelet Lymphocyte Ratio ◽  
Cardiac Intensive Care ◽  
The Relationship

AbstractIt has been discovered that both inflammation and platelet aggregation could cause crucial effect on the occurrence and development of cardiovascular diseases. As a combination of platelet and lymphocyte, platelet-lymphocyte ratio (PLR) was proved to be correlated with the severity as well as prognosis of cardiovascular diseases. Exploring the relationship between PLR and in-hospital mortality in cardiac intensive care unit (CICU) patients was the purpose of this study. PLR was calculated by dividing platelet count by lymphocyte count. All patients were grouped by PLR quartiles and the primary outcome was in-hospital mortality. The independent effect of PLR was determined by binary logistic regression analysis. The curve in line with overall trend was drawn by local weighted regression (Lowess). Subgroup analysis was used to determine the relationship between PLR and in-hospital mortality in different subgroups. We included 5577 CICU patients. As PLR quartiles increased, in-hospital mortality increased significantly (Quartile 4 vs. Quartile 1: 13.9 vs. 8.3, P < 0.001). After adjusting for confounding variables, PLR was proved to be independently associated with increased risk of in-hospital mortality (Quartile 4 vs. Quartile 1: OR 95% CI 1.55, 1.08–2.21, P = 0.016, P for trend < 0.001). The Lowess curves showed a positive relationship between PLR and in-hospital mortality. The subgroup analysis revealed that patients with low Acute Physiology and Chronic Health Evaluation IV (APACHE IV) or with less comorbidities had higher risk of mortality for PLR. Further, PLR quartiles had positive relation with length of CICU stay (Quartile 4 vs. Quartile 1: 2.7, 1.6–5.2 vs. 2.1, 1.3–3.9, P < 0.001), and the length of hospital stay (Quartile 4 vs. Quartile 1: 7.9, 4.6–13.1 vs. 5.8, 3.3–9.8, P < 0.001). PLR was independently associated with in-hospital mortality in CICU patients.

scholarly journals National trends in coronary intensive care unit admissions, resource utilization, and outcomes

2019 ◽  
Vol 9 (8) ◽  
pp. 923-930
Author(s):  
Sarah Woolridge ◽  
Wendimagegn Alemayehu ◽  
Padma Kaul ◽  
Christopher B Fordyce ◽  
Patrick R Lawler ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Critical Care ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Odds Ratio ◽  
Adjusted Odds Ratio ◽  
Mortality Rates ◽  
St Segment Elevation ◽  
Segment Elevation Myocardial Infarction ◽  
St Segment

Background: Emerging evidence suggests that coronary intensive care units are evolving into intensive care environments with an increasing burden of non-cardiovascular illness, but previous studies have been limited to older populations or single center experiences. Methods: Canadian national health-care data was used to identify all patients ≥18 years admitted to dedicated coronary intensive care units (2005–2015) and admissions were categorized as primary cardiac or non-cardiac. The outcomes of interest included longitudinal trends in admission diagnoses, critical care therapies, and all-cause in-hospital mortality. Results: Among the 373,992 patients admitted to a coronary intensive care unit, minimal changes in the proportion of patients admitted with a primary cardiac (88.2% to 86.9%; p<0.001) and non-cardiac diagnoses (11.8% to 13.1%; p<0.001) were observed. Among cardiac admissions, a temporal increase in the proportion of ST-segment elevation myocardial infarction (19.4% to 24.1%, p<0.001), non-ST-segment elevation myocardial infarction (14.6% to 16.2%, p<0.001), heart failure (7.3% to 8.4%, p<0.001), shock (4.9% to 5.7%, p<0.001), and decline in unstable angina (4.9% to 4.0%, p<0.001) and stable coronary diseases (21.3% to 12.4%, p<0.001) was observed. The proportion of patients requiring critical care therapies (57.8% to 63.5%, p<0.001) including mechanical ventilation (9.6% to 13.1%, p<0.001) increased. In-hospital mortality rates for patients with primary cardiac (4.9% to 4.4%; adjusted odds ratio 0.71, 95% confidence interval 0.63–0.79) and non-cardiac (17.8% to 16.1%; adjusted odds ratio 0.84, 0.73–0.97) declined; results were consistent when stratified by academic vs community hospital, and by the presence of on-site percutaneous coronary intervention. Conclusion: In a national dataset we observed a changing case-mix among patients admitted to a coronary intensive care unit, though the proportion of patients with a primary cardiac diagnosis remained stable. There was an increase in clinical acuity highlighted by critical care therapies, but in-hospital mortality rates for both primary cardiac and non-cardiac conditions declined across all hospitals. Our findings confirm the changing coronary intensive care unit case-mix and have implications for future coronary intensive care unit training and staffing.

scholarly journals Validation of APACHE II, APACHE III and SAPS II scores in in-hospital and one year mortality prediction in a mixed intensive care unit in Poland: a cohort study

2020 ◽  
Author(s):  
Szymon Czajka ◽  
Katarzyna Ziębińska ◽  
Konstanty Marczenko ◽  
Barbara Posmyk ◽  
Anna Szczepańska ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Diagnostic Accuracy ◽  
Mortality Prediction ◽  
Apache Ii ◽  
Post Discharge ◽  
Saps Ii ◽  
Apache Iii

Abstract Background. There are several scores used for in-hospital mortality prediction in critical illness. Their application in a local scenario requires validation to ensure appropriate diagnostic accuracy. Moreover, their use in assessing post-discharge mortality in intensive care unit (ICU) survivors has not been extensively studied. We aimed to validate APACHE II, APACHE III and SAPS II scores in short- and long-term mortality prediction in a mixed adult ICU in Poland. APACHE II, APACHE III and SAPS II scores, with corresponding predicted mortality ratios, were calculated for 303 consecutive patients admitted to a 10-bed ICU in 2016. Short-term (in-hospital) and long-term (12-month post-discharge) mortality was assessed. Results. Median APACHE II, APACHE III and SAPS II scores were 19 (IQR 12-24), 67 (36.5-88) and 44 (27-56) points, with corresponding in-hospital mortality ratios of 25.8% (IQR 12.1-46.0), 18.5% (IQR 3.8-41.8) and 34.8% (IQR 7.9-59.8). Observed in-hospital mortality was 35.6%. Moreover, 12-month post-discharge mortality reached 17.4%. All the scores predicted in-hospital mortality (p<0.05): APACHE II (AUC=0.78; 95%CI 0.73-0.83), APACHE III (AUC=0.79; 95%CI 0.74-0.84) and SAPS II (AUC=0.79; 95%CI 0.74-0.84); as well as mortality after hospital discharge (p<0.05): APACHE II (AUC=0.71; 95%CI 0.64-0.78), APACHE III (AUC=0.72; 95%CI 0.65-0.78) and SAPS II (AUC=0.69; 95%CI 0.62-0.76), with no statistically significant difference between the scores (p>0.05). The calibration of the scores was good. Conclusions. All the scores are acceptable predictors of in-hospital mortality. In the case of post-discharge mortality, their diagnostic accuracy is lower and of borderline clinical relevance. Further studies are needed to create scores estimating the long-term prognosis of subjects successfully discharged from the ICU.

scholarly journals Prospective Independent Validation of APACHE III Models in an Australian Tertiary Adult Intensive Care Unit

2002 ◽  
Vol 30 (3) ◽  
pp. 308-315 ◽  
Author(s):  
D. A. Cook ◽  
C. J. Joyce ◽  
R. J. Barnett ◽  
S. P. Birgan ◽  
H. Playford ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Princess Alexandra Hospital ◽  
Icu Mortality ◽  
Discharge Data ◽  
Mortality Model ◽  
Apache Iii ◽  
Mortality Models ◽  
Hospital Characteristics

Evaluation of the performance of the APACHE III (Acute Physiology and Chronic Health Evaluation) ICU (intensive care unit) and hospital mortality models at the Princess Alexandra Hospital, Brisbane is reported. Prospective collection of demographic, diagnostic, physiological, laboratory, admission and discharge data of 5681 consecutive eligible admissions (1 January 1995 to 1 January 2000) was conducted at the Princess Alexandra Hospital, a metropolitan Australian tertiary referral medical/surgical adult ICU. ROC (receiver operating characteristic) curve areas for the APACHE III ICU mortality and hospital mortality models demonstrated excellent discrimination. Observed ICU mortality (9.1%) was significantly overestimated by the APACHE III model adjusted for hospital characteristics (10.1%), but did not significantly differ from the prediction of the generic APACHE III model (8.6%). In contrast, observed hospital mortality (14.8%) agreed well with the prediction of the APACHE III model adjusted for hospital characteristics (14.6%), but was significantly underestimated by the unadjusted APACHE III model (13.2%). Calibration curves and goodness-of-fit analysis using Hosmer-Lemeshow statistics, demonstrated that calibration was good with the unadjusted APACHE III ICU mortality model, and the APACHE III hospital mortality model adjusted for hospital characteristics. Post hoc analysis revealed a declining annual SMR (standardized mortality rate) during the study period. This trend was present in each of the non-surgical, emergency and elective surgical diagnostic groups, and the change was temporally related to increased specialist staffing levels. This study demonstrates that the APACHE III model performs well on independent assessment in an Australian hospital. Changes observed in annual SMR using such a validated model support an hypothesis of improved survival outcomes 1995–1999.

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 Validation of APACHE II, APACHE III and SAPS II scores in in-hospital and one year mortality prediction in a mixed intensive care unit in Poland: a cohort study

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Szymon Czajka ◽  
Katarzyna Ziębińska ◽  
Konstanty Marczenko ◽  
Barbara Posmyk ◽  
Anna J. Szczepańska ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Diagnostic Accuracy ◽  
Mortality Prediction ◽  
Apache Ii ◽  
Post Discharge ◽  
Saps Ii ◽  
Apache Iii

Abstract Background There are several scores used for in-hospital mortality prediction in critical illness. Their application in a local scenario requires validation to ensure appropriate diagnostic accuracy. Moreover, their use in assessing post-discharge mortality in intensive care unit (ICU) survivors has not been extensively studied. We aimed to validate APACHE II, APACHE III and SAPS II scores in short- and long-term mortality prediction in a mixed adult ICU in Poland. APACHE II, APACHE III and SAPS II scores, with corresponding predicted mortality ratios, were calculated for 303 consecutive patients admitted to a 10-bed ICU in 2016. Short-term (in-hospital) and long-term (12-month post-discharge) mortality was assessed. Results Median APACHE II, APACHE III and SAPS II scores were 19 (IQR 12–24), 67 (36.5–88) and 44 (27–56) points, with corresponding in-hospital mortality ratios of 25.8% (IQR 12.1–46.0), 18.5% (IQR 3.8–41.8) and 34.8% (IQR 7.9–59.8). Observed in-hospital mortality was 35.6%. Moreover, 12-month post-discharge mortality reached 17.4%. All the scores predicted in-hospital mortality (p < 0.05): APACHE II (AUC = 0.78; 95%CI 0.73–0.83), APACHE III (AUC = 0.79; 95%CI 0.74–0.84) and SAPS II (AUC = 0.79; 95%CI 0.74–0.84); as well as mortality after hospital discharge (p < 0.05): APACHE II (AUC = 0.71; 95%CI 0.64–0.78), APACHE III (AUC = 0.72; 95%CI 0.65–0.78) and SAPS II (AUC = 0.69; 95%CI 0.62–0.76), with no statistically significant difference between the scores (p > 0.05). The calibration of the scores was good. Conclusions All the scores are acceptable predictors of in-hospital mortality. In the case of post-discharge mortality, their diagnostic accuracy is lower and of borderline clinical relevance. Further studies are needed to create scores estimating the long-term prognosis of subjects successfully discharged from the ICU.

Long-Stay Pediatric Intensive Care Unit Patients: Outcome and Resource Utilization

PEDIATRICS ◽  
1987 ◽  
Vol 80 (6) ◽  
pp. 855-860
Author(s):  
Murray M. Pollack ◽  
James D. Wilkinson ◽  
Nancy L. Glass
Keyword(s):  
Health Care ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Pediatric Intensive Care Unit ◽  
Resource Utilization ◽  
Pediatric Intensive Care ◽  
Mortality Rates ◽  
Short Stay ◽  
One Year ◽  
Short Stay Patients

Outcome, resource utilization, and health care characteristics of patients staying in a multidisciplinary pediatric intensive care unit (PICU) for more than 13 days (long-stay patients) were analyzed. Of 647 children admitted consecutively, 46 were long-stay patients. Compared with short-stay patients, long-stay patients were significantly younger and sicker and had a higher incidence of chronic disease. Most important, long-stay patients had significantly higher PICU mortality rates (17.4% v 7.3%, P &lt; .05) and hospital mortality rates (23.9% v 8.7%, P &lt; .01) than short-stay PICU patients. Although only 7.1% of the patient sample, long-stay patients consumed approximately 50% of all PICU resources. One-year follow-up on those long-stay patients surviving their hospitalization revealed that 58% had died or were severely disabled. Long-stay patients had relatively poor prognoses and consumed health care resources in excess of their numeric proportions.

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