Multicenter outcome study of cancer patients admitted to the intensive care unit: a probability of mortality model.

1998 ◽  
Vol 16 (2) ◽  
pp. 761-770 ◽  
Author(s):  
J S Groeger ◽  
S Lemeshow ◽  
K Price ◽  
D M Nierman ◽  
P White ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Logistic Regression ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Cancer Patients ◽  
The United States ◽  
Categorical Variables ◽  
Allogeneic Bone ◽  
Icu Admission ◽  
Hospital Survival

PURPOSE To develop prospectively and validate a model for probability of hospital survival at admission to the intensive care unit (ICU) of patients with malignancy. PATIENTS AND METHODS This was an inception cohort study in the setting of four ICUs of academic medical centers in the United States. Defined continuous and categorical variables were collected on consecutive patients with cancer admitted to the ICU. A preliminary model was developed from 1,483 patients and then validated on an additional 230 patients. Multiple logistic regression modeling was used to develop the models and subsequently evaluated by goodness-of-fit and receiver operating characteristic (ROC) analysis. The main outcome measure was hospital survival after ICU admission. RESULTS The observed hospital mortality rate was 42%. Continuous variables used in the ICU admission model are PaO2/FiO2 ratio, platelet count, respiratory rate, systolic blood pressure, and days of hospitalization pre-ICU. Categorical entries include presence of intracranial mass effect, allogeneic bone marrow transplantation, recurrent or progressive cancer, albumin less than 2.5 g/dL, bilirubin > or = 2 mg/dL, Glasgow Coma Score less than 6, prothrombin time greater than 15 seconds, blood urea nitrogen (BUN) greater than 50 mg/dL, intubation, performance status before hospitalization, and cardiopulmonary resuscitation (CPR). The P values for the fit of the preliminary and validation models are .939 and .314, respectively, and the areas under the ROC curves are .812 and .802. CONCLUSION We report a disease-specific multivariable logistic regression model to estimate the probability of hospital mortality in a cohort of critically ill cancer patients admitted to the ICU. The model consists of 16 unambiguous and readily available variables. This model should move the discussion regarding appropriate use of ICU resources forward. Additional validation in a community hospital setting is warranted.

scholarly journals Risk Factors for Intensive Care Unit Admission and In-hospital Mortality Among Hospitalized Adults Identified through the US Coronavirus Disease 2019 (COVID-19)-Associated Hospitalization Surveillance Network (COVID-NET)

2020 ◽  
Author(s):  
Lindsay Kim ◽  
Shikha Garg ◽  
Alissa O’Halloran ◽  
Michael Whitaker ◽  
Huong Pham ◽  
...  
Keyword(s):  
Risk Factors ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Invasive Mechanical Ventilation ◽  
The United States ◽  
Surveillance Network ◽  
Factors Associated ◽  
Icu Admission ◽  
Male Sex

Abstract Background Currently, the United States has the largest number of reported coronavirus disease 2019 (COVID-19) cases and deaths globally. Using a geographically diverse surveillance network, we describe risk factors for severe outcomes among adults hospitalized with COVID-19. Methods We analyzed data from 2491 adults hospitalized with laboratory-confirmed COVID-19 between 1 March–2 May 2020, as identified through the Coronavirus Disease 2019–Associated Hospitalization Surveillance Network, which comprises 154 acute-care hospitals in 74 counties in 13 states. We used multivariable analyses to assess associations between age, sex, race and ethnicity, and underlying conditions with intensive care unit (ICU) admission and in-hospital mortality. Results The data show that 92% of patients had ≥1 underlying condition; 32% required ICU admission; 19% required invasive mechanical ventilation; and 17% died. Independent factors associated with ICU admission included ages 50–64, 65–74, 75–84, and ≥85 years versus 18–39 years (adjusted risk ratios [aRRs], 1.53, 1.65, 1.84, and 1.43, respectively); male sex (aRR, 1.34); obesity (aRR, 1.31); immunosuppression (aRR, 1.29); and diabetes (aRR, 1.13). Independent factors associated with in-hospital mortality included ages 50–64, 65–74, 75–84, and ≥ 85 years versus 18–39 years (aRRs, 3.11, 5.77, 7.67, and 10.98, respectively); male sex (aRR, 1.30); immunosuppression (aRR, 1.39); renal disease (aRR, 1.33); chronic lung disease (aRR 1.31); cardiovascular disease (aRR, 1.28); neurologic disorders (aRR, 1.25); and diabetes (aRR, 1.19). Conclusions In-hospital mortality increased markedly with increasing age. Aggressive implementation of prevention strategies, including social distancing and rigorous hand hygiene, may benefit the population as a whole, as well as those at highest risk for COVID-19–related complications.

Predictors of survival in patients with gastrointestinal malignancies admitted to the intensive care unit.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e18050-e18050
Author(s):  
Heidi Chwan Ko ◽  
Melissa Yan ◽  
Rohan Gupta ◽  
Juhee Song ◽  
Kayla Kebbel ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Cancer Patients ◽  
Sofa Score ◽  
Icu Mortality ◽  
Gastrointestinal Malignancies ◽  
Icu Admission ◽  
Risk Of Death ◽  
Gi Cancer

e18050 Background: Cancer patients have a high use of healthcare utilization at the end of life which can frequently involve admissions to the intensive care unit (ICU). We sought to evaluate the predictors for outcome in gastrointestinal (GI) cancer patients admitted to the ICU for non-surgical conditions. Methods: The objective of this study was to determine the factors associated with ICU mortality, hospital mortality and overall survival (OS). A total of 200 patients with GI cancer admitted to the ICU at The University of Texas MD Anderson Cancer Center between November 2012 and February 2015 were retrospectively analyzed. Cancer characteristics, treatment characteristics, and Sequential Organ Failure Assessment (SOFA) scores defining severity based on 6 organ systems with scores ranging from 0 to 24 were analyzed for their effects on survival endpoints using multivariate logistic regression models and a multivariate Cox proportional hazards regression model. Results: The characteristics of the 200 patients were: 64.5% male, mean age of 60 years, median admission SOFA score of 6.0, and tumor types of primary intestinal (37.5%), hepatobiliary/pancreatic (36%), and gastroesophageal (GE) (24%). The ICU mortality was 26%, hospital mortality was 41%, and 6-month OS estimate was 25%. In multivariate analysis, ICU admission SOFA score > 10 (odds ratio (OR) 17.1, p < 0.0001), poorly differentiated tumor grade (OR 3.2, p = 0.02), and shorter duration of metastatic disease (OR 2.3, p = 0.07) were associated with increased odds of ICU mortality. These same variables were associated with increased odds of hospital mortality. In multivariate OS analysis, SOFA score 6-10 (hazard ratio (HR) 2.1, p = 0.0006) and SOFA score > 10 (HR 4.4, p < 0.0001), patients with GE primary (HR 2.2, p = 0.002) and patients with a poor outpatient performance status that precluded active chemotherapy (HR 2.2, p = 0.01) were associated with increased risk of death. Conclusions: The SOFA score was the most predictive factor for ICU mortality, hospital mortality, and OS for GI cancer patients admitted to the ICU. It should be utilized in all GI cancer patients upon ICU admission to improve both acute and longer-term prognostication.

Hyperoxia is associated with adverse outcomes in the cardiac intensive care unit: insights from the Medical Information Mart for Intensive Care (MIMI-III) database

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
A.Y Lui ◽  
L Garber ◽  
M Vincent ◽  
L Celi ◽  
J Masip ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Logistic Regression ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Adverse Outcomes ◽  
Rank Test ◽  
Positive Pressure ◽  
Cardiac Intensive Care Unit ◽  
Multivariable Logistic Regression ◽  
Cardiac Intensive Care

Abstract Background Hyperoxia produces reactive oxygen species, apoptosis, and vasoconstriction, and is associated with adverse outcomes in patients with heart failure and cardiac arrest. Our aim was to evaluate the association between hyperoxia and mortality in patients (pts) receiving positive pressure ventilation (PPV) in the cardiac intensive care unit (CICU). Methods Patients admitted to our medical center CICU who received any PPV (invasive or non-invasive) from 2001 through 2012 were included. Hyperoxia was defined as time-weighted mean of PaO2 &gt;120mmHg and non-hyperoxia as PaO2 ≤120mmHg during CICU admission. Primary outcome was in-hospital mortality. Multivariable logistic regression was used to assess the association between hyperoxia and in-hospital mortality adjusted for age, female sex, Oxford Acute Severity of Illness Score, creatinine, lactate, pH, PaO2/FiO2 ratio, PCO2, PEEP, and estimated time spent on PEEP. Results Among 1493 patients, hyperoxia (median PaO2 147mmHg) during the CICU admission was observed in 702 (47.0%) pts. In-hospital mortality was 29.7% in the non-hyperoxia group and 33.9% in the hyperoxia group ((log rank test, p=0.0282, see figure). Using multivariable logistic regression, hyperoxia was independently associated with in-hospital mortality (OR 1.507, 95% CI 1.311–2.001, p=0.00508). Post-hoc analysis with PaO2 as a continuous variable was consistent with the primary analysis (OR 1.053 per 10mmHg increase in PaO2, 95% CI 1.024–1.082, p=0.0002). Conclusions In a large CICU cohort, hyperoxia was associated with increased mortality. Trials of titration of supplemental oxygen across the full spectrum of critically ill cardiac patients are warranted. Funding Acknowledgement Type of funding source: None

scholarly journals Respiratory events in ward are associated with later intensive care unit (ICU) admission and hospital mortality in onco-hematology patients not admitted to ICU after a first request

PLoS ONE ◽  
2017 ◽  
Vol 12 (7) ◽  
pp. e0181808 ◽  
Author(s):  
Laure Doukhan ◽  
Magali Bisbal ◽  
Laurent Chow-Chine ◽  
Antoine Sannini ◽  
Jean Paul Brun ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Icu Admission ◽  
Respiratory Events

scholarly journals P012: Mortality rate of cancer patients by type presenting to the intensive care unit with sepsis.

CJEM ◽  
2019 ◽  
Vol 21 (S1) ◽  
pp. S67
Author(s):  
S. Beckett ◽  
E. Karreman ◽  
R. Hughes
Keyword(s):  
Logistic Regression ◽  
Intensive Care ◽  
Mortality Rate ◽  
Cancer Patients ◽  
Solid Tumors ◽  
Predictive Factors ◽  
Poor Prognosis ◽  
Solid Tumours ◽  
Icu Mortality ◽  
Icu Admission

Introduction: Sepsis in cancer patients is associated with higher mortality rates than non-cancer patients. As a whole, hematological or solid tumor cancers have not demonstrated a prognostic link to sepsis survival rates in intensive care units (ICU), however poor-prognosis solid tumours (less than 25% 5-year survival) have not been investigated. This study examined ICU mortality rate and its predictive factors of patients with sepsis and poor-prognosis solid tumors in comparison to patients with higher prognosis solid tumours. Methods: A 6-year retrospective chart review of 79 patients with sepsis and solid tumour cancers and/or metastatic cancers admitted to the ICU was conducted. Information regarding mortality rate within 14 days, length of ICU stay, incidence of intubation, and other primary reasons for ICU admission was collected. Data was analysed using logistic regression. Results: Logistic regression results showed intubation as the only significant factor contributing to patient mortality (p &lt; .001), with the odds of mortality being 12.3 times higher for intubated than non-intubated patients. Five-year cancer survival rate was the second best predictor (p = .082), while age, sex, and metastasis were also not significant predictive factors for survival. Intubated patients with poor prognosis cancers had the lowest survival chance as further indicated by the 16 patients who met this criterion, of which 14 died within two weeks of ICU admission. Conclusion: The fact that poor prognosis cancers in sepsis were not significantly predictive of ICU mortality supports current literature regarding solid tumors in general, while intubation being a significant predictor for mortality in patients with sepsis and cancer regardless of type builds on previous research. A limitation of this study is the relative low number of included cases with poor-prognosis cancer types. Further evaluation is needed to understand the implications of our results for end-of-life care and ICU admission for patients with these characteristics.

scholarly journals Selection criteria for intensive care unit referral of lung cancer patients: a pilot study

2014 ◽  
Vol 45 (2) ◽  
pp. 491-500 ◽  
Author(s):  
Anne-Claire Toffart ◽  
Carola Alegria Pizarro ◽  
Carole Schwebel ◽  
Linda Sakhri ◽  
Clemence Minet ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Cancer Patients ◽  
Selection Criteria ◽  
Performance Status ◽  
Lung Cancer Patients ◽  
Icu Admission ◽  
Organ Failures ◽  
Intensity Of Care

The decision-making process for the intensity of care delivered to patients with lung cancer and organ failure is poorly understood, and does not always involve intensivists. Our objective was to describe the potential suitability for intensive care unit (ICU) referral of lung cancer in-patients with organ failures.We prospectively included consecutive lung cancer patients with failure of at least one organ admitted to the teaching hospital in Grenoble, France, between December 2010 and October 2012.Of 140 patients, 121 (86%) were evaluated by an oncologist and 49 (35%) were referred for ICU admission, with subsequent admission for 36 (73%) out of those 49. Factors independently associated with ICU referral were performance status ⩽2 (OR 10.07, 95% CI 3.85–26.32), nonprogressive malignancy (OR 7.00, 95% CI 2.24–21.80), and no explicit refusal of ICU admission by the patient and/or family (OR 7.95, 95% CI 2.39–26.37). Factors independently associated with ICU admission were the initial ward being other than the lung cancer unit (OR 6.02, 95% CI 1.11–32.80) and an available medical ICU bed (OR 8.19, 95% CI 1.48–45.35).Only one-third of lung cancer patients with organ failures were referred for ICU admission. The decision not to consider ICU admission was often taken by a non-intensivist, with advice from an oncologist rather than an intensivist.

An Analysis of Arguments for and Against Euthanasia and Assisted Suicide: Part One

1996 ◽  
Vol 5 (1) ◽  
pp. 62-76 ◽  
Author(s):  
David C. Thomasma
Keyword(s):  
United States ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Cancer Patients ◽  
Critically Ill ◽  
Assisted Suicide ◽  
The United States ◽  
Hospital Intensive Care Unit ◽  
Return Home ◽  
Life Prolongation

In advanced technological societies there is growing concern about the prospect of protracted deaths marked by incapacitation, intolerable pain and indignity, and invasion by machines and tubing. Life prolongation for critically ill cancer patients in the United States, for example, literally costs a fortune for very little benefit, typically from $82,845 to $189,339 for an additional year of life. Those who return home after major interventions live on average only 3 more months; the others live out their days in a hospital intensive care unit.

scholarly journals SAPS 3—From evaluation of the patient to evaluation of the intensive care unit. Part 2: Development of a prognostic model for hospital mortality at ICU admission

2005 ◽  
Vol 31 (10) ◽  
pp. 1345-1355 ◽  
Author(s):  
Rui P. Moreno ◽  
Philipp G. H. Metnitz ◽  
Eduardo Almeida ◽  
Barbara Jordan ◽  
Peter Bauer ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Prognostic Model ◽  
Saps 3 ◽  
Icu Admission

An Analysis of Patients Transferred to a Tertiary Oncological Intensive Care Unit for Defined Procedures

2015 ◽  
Vol 24 (3) ◽  
pp. 241-247 ◽  
Author(s):  
Sunil Kamat ◽  
Sanjay Chawla ◽  
Prabalini Rajendram ◽  
Stephen M. Pastores ◽  
Natalie Kostelecky ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Cancer Patients ◽  
Signs And Symptoms ◽  
The United States ◽  
Outcome Data ◽  
Lengths Of Stay ◽  
Intensive Care Unit Transfer ◽  
Tumor Bleeding ◽  
Oncological Center

Background Up to 50 000 intensive care unit interhospital transfers occur annually in the United States. Objective To determine the prevalence, characteristics, and outcomes of cancer patients transferred from an intensive care unit in one hospital to another intensive care unit at an oncological center and to evaluate whether interventions planned before transfer were performed. Methods Data on transfers for planned interventions from January 2008 through December 2012 were identified retrospectively. Demographic and clinical variables, receipt of planned interventions, and outcome data were analyzed. Results Of 4625 admissions to an intensive care unit at the oncological center, 143 (3%) were transfers from intensive care units of other hospitals. Of these, 47 (33%) were transfers for planned interventions. Patients’ mean age was 57 years, and 68% were men. At the time of intensive care unit transfer, 20 (43%) were receiving mechanical ventilation. Interventions included management of airway (n = 19) or gastrointestinal (n = 2) obstruction, treatment of tumor bleeding (n = 12), chemotherapy (n = 10), and other (n = 4). A total of 37 patients (79%) received the planned interventions within 48 hours of intensive care unit arrival; 10 (21%) did not because their signs and symptoms abated. Median intensive care unit and hospital lengths of stay at the oncological center were 4 and 13 days, respectively. Intensive care unit and hospital mortality rates were 11% and 19%, respectively. Deaths occurred only in patients who received interventions. Conclusions Interhospital transfers of cancer patients to an intensive care unit at an oncological center are infrequent but are most commonly done for direct interventional care. Most patients received planned interventions soon after transfer.

scholarly journals Disparities in Intensive Care Unit Admission and Mortality Among Patients With Schizophrenia and COVID-19: A National Cohort Study

2020 ◽  
Author(s):  
Guillaume Fond ◽  
Vanessa Pauly ◽  
Marc Leone ◽  
Pierre-Michel Llorca ◽  
Veronica Orleans ◽  
...  
Keyword(s):  
Health Care ◽  
Intensive Care Unit ◽  
Mental Illness ◽  
Cohort Study ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Severe Mental Illness ◽  
Vulnerable Population ◽  
Icu Admission ◽  
Risk Of Death

Abstract Patients with schizophrenia (SCZ) represent a vulnerable population who have been understudied in COVID-19 research. We aimed to establish whether health outcomes and care differed between patients with SCZ and patients without a diagnosis of severe mental illness. We conducted a population-based cohort study of all patients with identified COVID-19 and respiratory symptoms who were hospitalized in France between February and June 2020. Cases were patients who had a diagnosis of SCZ. Controls were patients who did not have a diagnosis of severe mental illness. The outcomes were in-hospital mortality and intensive care unit (ICU) admission. A total of 50 750 patients were included, of whom 823 were SCZ patients (1.6%). The SCZ patients had an increased in-hospital mortality (25.6% vs 21.7%; adjusted OR 1.30 [95% CI, 1.08–1.56], P = .0093) and a decreased ICU admission rate (23.7% vs 28.4%; adjusted OR, 0.75 [95% CI, 0.62–0.91], P = .0062) compared with controls. Significant interactions between SCZ and age for mortality and ICU admission were observed (P = .0006 and P &lt; .0001). SCZ patients between 65 and 80 years had a significantly higher risk of death than controls of the same age (+7.89%). SCZ patients younger than 55 years had more ICU admissions (+13.93%) and SCZ patients between 65 and 80 years and older than 80 years had less ICU admissions than controls of the same age (−15.44% and −5.93%, respectively). Our findings report the existence of disparities in health and health care between SCZ patients and patients without a diagnosis of severe mental illness. These disparities differed according to the age and clinical profile of SCZ patients, suggesting the importance of personalized COVID-19 clinical management and health care strategies before, during, and after hospitalization for reducing health disparities in this vulnerable population.

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