Presenting Symptoms in the Emergency Department as Predictors of Intensive Care Unit Admissions and Hospital Mortality in a Comprehensive Cancer Center

Purpose: The identification of patients at high risk for poor outcomes may allow for earlier palliative care and prevent futile interventions. We examined the association of presenting symptoms on risk of intensive care unit (ICU) admission and hospital death among patients with cancer admitted through an emergency department (ED). Methods: We queried MD Anderson Cancer Center databases for all patients who visited the ED in 2010. Presenting symptoms, ICU admissions, and hospital deaths were reviewed; patient data analyzed; and risk factors for ICU admission and hospital mortality identified. Results: The main presenting symptoms were pain, fever, and respiratory distress. Of the patients with cancer who visited the ED, 5,362 (58%) were admitted to the hospital at least once (range, 1 to 13 admissions), 697 (13%) were admitted to the ICU at least once, and 587 (11%) died during hospitalization (31% of 233 patients with hematologic malignancies and 27% of 354 patients with solid tumors died in the ICU; P < .001). In multivariable logistic regression, presenting symptoms of respiratory distress or altered mental status; lung cancer, leukemia, or lymphoma; and nonwhite race were independent predictors of hospital death. Patients who died had a longer median length of hospital stay than patients discharged alive (14 v 6 days for hematologic malignancies and 7 v 5 days for solid tumors; P < .001). Conclusion: Patients with cancer admitted through an ED experience high ICU admission and hospital mortality rates. Patients with advanced cancer and respiratory distress or altered mental status may benefit from palliative care that avoids unnecessary interventions.

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Outcome of cancer patients admitted through the emergency department (ED) of a comprehensive cancer center: A call for ED-based palliative care.

Journal of Clinical Oncology ◽

10.1200/jco.2014.32.31_suppl.194 ◽

2014 ◽

Vol 32 (31_suppl) ◽

pp. 194-194

Author(s):

Ahmed F. Elsayem ◽

Julio Silvestre ◽

Kelly W. Merriman ◽

Patrick S. Chaftari ◽

Carmen E. Gonzalez ◽

...

Keyword(s):

Risk Factors ◽

Emergency Department ◽

Palliative Care ◽

Hospital Mortality ◽

Respiratory Distress ◽

Cancer Patients ◽

Altered Mental Status ◽

Cancer Center ◽

Hospital Death ◽

Icu Admission

194 Background: The National Cancer Policy Forum advocated for improving quality of end life care, and reducing cost for cancer patients. Identifying those at high risk for Intensive Care Unit (ICU) admission, and hospital death may allow earlier palliative care and avoid futile interventions. The purpose of this study is to examine risk factors for ICU admission, and hospital death among cancer patients admitted through the emergency department (ED). Methods: We queried MD Anderson Cancer Center databases for all patients who visited our ED in 2010. ICU admission and hospital deaths of these patients were reviewed, and individual patients’ data were analyzed. Results: In 2010, 16,038 ED visits were made by 9,246 unique cancer patients. Of these patients, 5,362 (58%) were admitted to the hospital at least once (range 1-13 admits). Of all patients admitted through the ED, 697 (13%) were admitted at least once to ICU. Of all patients admitted, 11% died during hospitalization; of those, 29% died in ICU. Among patients who died in ICU, 73/233 (31.3%) had hematologic malignancies and 96/354 (27.1%) had solid tumors (P<0.001). Patients admitted to ICU had median lengths of hospital stay (MLOS) of 13 days for hematologic and 8 days for solid tumors (P<0.001; using means); patients without ICU admission had MLOS of 6 and 5 days, respectively (P<0.001). In a multivariate logistic regression model for predicting in-hospital mortality, we found that ED presenting symptoms of respiratory distress or altered mental status; primary tumor of lung cancer, leukemia, unknown primary, or lymphoma; and nonwhite ethnicities were independent predictors of death. Insignificant factors included age, gender, residence, fever and pain. Conclusions: Cancer patients admitted through the ED experience high ICU admission rate, and hospital mortality. Lung and certain other cancers; race; and symptoms of respiratory distress and altered mental status were associated with increased risk of in-hospital death. Patients with these risk factors may benefit from efforts to improve palliative care and prevent futile interventions.

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Contemporary outcomes for adults with AML requiring ICU admission.

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.7025 ◽

2021 ◽

Vol 39 (15_suppl) ◽

pp. 7025-7025

Author(s):

Danielle Hammond ◽

Koji Sasaki ◽

Alexis Geppner ◽

Fadi Haddad ◽

Shehab Mohamed ◽

...

Keyword(s):

Hospital Mortality ◽

Cancer Center ◽

Hospital Death ◽

Entire Cohort ◽

Morbidity Burden ◽

Icu Admission ◽

Poor Risk ◽

Line Therapy ◽

Co Morbidity ◽

Life Threatening

7025 Background: Patients (pts) with AML frequently encounter life-threatening complications requiring transfer to an intensive care unit (ICU). Methods: Retrospective analysis of 145 adults with AML requiring ICU admission at our tertiary cancer center 2018-19. Use of life-sustaining therapies (LSTs) and overall survival (OS) were reported using descriptive statistics. Logistic regression was used to identify risk factors for in-hospital death. Results: Median age was 64 yrs (range 18-86). 47% of pts had an ECOG status of ≥ 2 with a median of at least 1 comorbidity (Table). 117 pts (81%) had active leukemia at admission. 68 pts (47%) had poor-risk cytogenetics (CG) and 32 (22%) had TP53-mutated disease. 61 (42%), 27 (19%) and 57 pts (39%) were receiving 1st, 2nd and ≥ 3rd line therapy. 33 (23%) and 70 pts (48%) were receiving intensive and lower-intensity chemotherapy, respectively, and 77 pts (53%) were concurrently on venetoclax. Most common indications for admission were sepsis (32%), respiratory failure (24%) and leukocytosis (12%); Table outlines additional ICU admission details. Median OS from the date of ICU admission was 2.0 months (mo) for the entire cohort and 6.9, 1.6 and 1.2 mo in pts with favorable-, intermediate- and poor-risk CG. Median OS of pts receiving frontline vs. ≥ 2nd line therapy was 4.2 vs. 1.4 mo (P<0.001). Median OS in pts requiring 0-1 vs. 2-3 LSTs was 4.1 vs. 0.4 mo (P<0.001). OS was not different by age, co-morbidity burden nor therapy intensity. In a multivariate analysis that included SOFA scores, only adverse CG (OR 0.35, P = 0.028), and need for intubation with mechanical ventilation (IMV; OR 0.19, P = 0.009) were associated with increased odds of in-hospital mortality. Conclusions: A substantial portion of pts with AML survive their ICU admission with sufficient functionality to return home and receive subsequent therapy. In contrast to general medical populations, age, co-morbidities, and SOFA scores were not independently predictive of in-hospital mortality. Disease CG risk and the need for IMV were the strongest predictors of ICU survival. This suggests that many pts with AML can benefit from ICU care.[Table: see text]

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Analysis of Intent and Reason for Oncologic Therapy Administration in Cancer Patients Admitted to the Intensive Care Unit

Journal of Intensive Care Medicine ◽

10.1177/08850666211065993 ◽

2021 ◽

pp. 088506662110659

Author(s):

David Shaz ◽

Stephen M. Pastores ◽

Lokesh Dayal ◽

Justin Berkowitz ◽

Natalie Kostelecky ◽

...

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Hematologic Malignancies ◽

Cancer Center ◽

Curative Intent ◽

Palliative Intent ◽

Patients With Cancer ◽

Continuation Therapy ◽

Oncologic Therapy ◽

Tertiary Cancer Center

Purpose To investigate the intent of, and reason for, administration of oncologic therapies in the intensive care unit (ICU). Methods Single center, retrospective, cohort study of patients with cancer who received oncologic therapies at a tertiary cancer center ICU between April 1, 2019 and March 31, 2020. Oncologic therapies included traditional cytotoxic chemotherapy, targeted therapy, immunotherapy, hormonal or biologic therapy directed at a malignancy and were characterized as initiation (initial administration) or continuation (part of an ongoing regimen). Results 84 unique patients (6.8% of total ICU admissions) received oncologic therapies in the ICU; 43 (51%) had hematologic malignancies and 41 (49%) had solid tumors. The intent of oncologic therapy was palliative in 63% and curative in 27%. Twenty-two (26%) patients received initiation and 62 (74%) received continuation oncologic therapies. The intent of oncologic therapy was significantly different by regimen type (initiation vs. continuation, p = <0.0001). Initiation therapy was more commonly prescribed with curative intent and continuation therapy was more commonly administered with palliative intent (p = <0.0001). Oncologic therapies were given in the ICU mainly for an oncologic emergency (56%) and because the patients happened to be in the ICU for a non-oncologic critical illness when their oncologic therapy was due (34.5%). Conclusion Our study provides intensivists with a better understanding of the context and intent of oncologic therapies and why these therapies are administered in the ICU.

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Use of multiple anticholinergic medications can predispose patients to severe non-exertional hyperthermia

BMJ Case Reports ◽

10.1136/bcr-2020-239873 ◽

2021 ◽

Vol 14 (3) ◽

pp. e239873

Author(s):

Ahila Manivannan ◽

Dana Kabbani ◽

Diane Levine

Keyword(s):

Intensive Care Unit ◽

Altered Mental Status ◽

Blood Cultures ◽

Oral Temperature ◽

Anticholinergic Effects ◽

Quick Recovery ◽

Presenting Symptoms ◽

Anticholinergic Medications ◽

Cooling Mechanism ◽

Staphylococcus Hominis

We present a case of a 64-year-old woman who developed severe non-exertional hyperthermia (NEHT) due to excessive anticholinergic effects from her psychiatric medications. The patient was found unresponsive in a non-air-conditioned room where the outside temperature was over 33°C. She presented with altered mental status, hypotension and an oral temperature of 42°C. Drug–drug interactions from her home medications for depression, bipolar disorder and seizures (amitriptyline, cyclobenzaprine, benztropine, topiramate, clonazepam, trazodone) were suspected. Blood cultures grew Staphylococcus hominis. The patient quickly returned to baseline with supportive care in the intensive care unit. She was treated for the Staph hominis bacteraemia with a 7-day course of vancomycin. Due to her quick recovery and lack of neurological findings, severe NEHT with associated bacteraemia was determined to have caused her presenting symptoms. This patient’s multiple anticholinergic medications increased her susceptibility to develop NEHT by inhibited sweating, this patient’s natural cooling mechanism.

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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 ◽

10.1371/journal.pone.0181808 ◽

2017 ◽

Vol 12 (7) ◽

pp. e0181808 ◽

Cited By ~ 5

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

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COVID outcome prediction in the emergency department (COPE): using retrospective Dutch hospital data to develop simple and valid models for predicting mortality and need for intensive care unit admission in patients who present at the emergency department with suspected COVID-19

BMJ Open ◽

10.1136/bmjopen-2021-051468 ◽

2021 ◽

Vol 11 (9) ◽

pp. e051468

Author(s):

David van Klaveren ◽

Alexandros Rekkas ◽

Jelmer Alsma ◽

Rob J C G Verdonschot ◽

Dick T J J Koning ◽

...

Keyword(s):

Intensive Care Unit ◽

Emergency Department ◽

Intensive Care ◽

Outcome Prediction ◽

Characteristic Curve ◽

Hospital Death ◽

Hospital Data ◽

Dutch Hospital ◽

Icu Admission ◽

Second Wave

ObjectivesDevelop simple and valid models for predicting mortality and need for intensive care unit (ICU) admission in patients who present at the emergency department (ED) with suspected COVID-19.DesignRetrospective.SettingSecondary care in four large Dutch hospitals.ParticipantsPatients who presented at the ED and were admitted to hospital with suspected COVID-19. We used 5831 first-wave patients who presented between March and August 2020 for model development and 3252 second-wave patients who presented between September and December 2020 for model validation.Outcome measuresWe developed separate logistic regression models for in-hospital death and for need for ICU admission, both within 28 days after hospital admission. Based on prior literature, we considered quickly and objectively obtainable patient characteristics, vital parameters and blood test values as predictors. We assessed model performance by the area under the receiver operating characteristic curve (AUC) and by calibration plots.ResultsOf 5831 first-wave patients, 629 (10.8%) died within 28 days after admission. ICU admission was fully recorded for 2633 first-wave patients in 2 hospitals, with 214 (8.1%) ICU admissions within 28 days. A simple model—COVID outcome prediction in the emergency department (COPE)—with age, respiratory rate, C reactive protein, lactate dehydrogenase, albumin and urea captured most of the ability to predict death. COPE was well calibrated and showed good discrimination for mortality in second-wave patients (AUC in four hospitals: 0.82 (95% CI 0.78 to 0.86); 0.82 (95% CI 0.74 to 0.90); 0.79 (95% CI 0.70 to 0.88); 0.83 (95% CI 0.79 to 0.86)). COPE was also able to identify patients at high risk of needing ICU admission in second-wave patients (AUC in two hospitals: 0.84 (95% CI 0.78 to 0.90); 0.81 (95% CI 0.66 to 0.95)).ConclusionsCOPE is a simple tool that is well able to predict mortality and need for ICU admission in patients who present to the ED with suspected COVID-19 and may help patients and doctors in decision making.

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

Journal of Clinical Oncology ◽

10.1200/jco.1998.16.2.761 ◽

1998 ◽

Vol 16 (2) ◽

pp. 761-770 ◽

Cited By ~ 162

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.

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Active Mycobacterium tuberculosis infection at a comprehensive cancer center, 2006–2014

BMC Infectious Diseases ◽

10.1186/s12879-019-4586-y ◽

2019 ◽

Vol 19 (1) ◽

Cited By ~ 1

Author(s):

Joumana Kmeid ◽

Prathit A. Kulkarni ◽

Marjorie V. Batista ◽

Firas El Chaer ◽

Amrita Prayag ◽

...

Keyword(s):

Mycobacterium Tuberculosis ◽

Cancer Patients ◽

Hematopoietic Cell Transplantation ◽

Average Rate ◽

Hematologic Malignancies ◽

Comprehensive Cancer Center ◽

Cancer Center ◽

Mycobacterium Tuberculosis Infection ◽

Patients With Cancer ◽

Disseminated Disease

Abstract Background Morbidity and mortality from Mycobacterium tuberculosis (Mtb) infection remain significant in cancer patients. We evaluated clinical characteristics, management, and outcomes in patients with active Mtb infection at our institution who had cancer or suspicion of cancer. Methods We retrospectively examined medical records of all patients with laboratory-confirmed active Mtb infection diagnosed between 2006 and 2014. Results A total of 52 patients with laboratory-confirmed active Mtb infection were identified during the study period, resulting in an average rate of 6 new cases per year. Thirty-two (62%) patients had underlying cancer, while 20 (38%) patients did not have cancer but were referred to the institution because of suspicion of underlying malignancy. Among patients with cancer, 18 (56%) had solid tumors; 8 (25%) had active hematologic malignancies; and 6 (19%) had undergone hematopoietic-cell transplantation (HCT). Patients with and without cancer were overall similar with the exception of median age (61 years in cancer patients compared to 53 years in noncancer patients). Pulmonary disease was identified in 32 (62%) patients, extrapulmonary disease in 10 (19%) patients, and disseminated disease in 10 (19%) patients. Chemotherapy was delayed in 53% of patients who were to receive such treatment. Eleven patients (all of whom had cancer) died; 3 of these deaths were attributable to Mtb infection. Conclusions Although not common, tuberculosis remains an important infection in patients with cancer. Approximately one-third of patients were referred to our institution for suspicion of cancer but were ultimately diagnosed with active Mtb infection rather than malignancy.

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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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