scholarly journals Cardiac Troponin Is a Predictor of Septic Shock Mortality in Cancer Patients in an Emergency Department: A Retrospective Cohort Study

PLoS ONE ◽  
2016 ◽  
Vol 11 (4) ◽  
pp. e0153492
Author(s):  
Zhi Yang ◽  
Aiham Qdaisat ◽  
Zhihuang Hu ◽  
Elizabeth A. Wagar ◽  
Cielito Reyes-Gibby ◽  
...  
Keyword(s):  
Emergency Department ◽  
Septic Shock ◽  
Cohort Study ◽  
Cancer Patients ◽  
Retrospective Cohort Study ◽  
Cardiac Troponin ◽  
Retrospective Cohort

scholarly journals Sepsis in patients with haematological versus solid cancer: a retrospective cohort study

BMJ Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. e038349
Author(s):  
Ralphe Bou Chebl ◽  
Rawan Safa ◽  
Mohammad Sabra ◽  
Ali Chami ◽  
Iskandar Berbari ◽  
...  
Keyword(s):  
Emergency Department ◽  
Septic Shock ◽  
Cohort Study ◽  
Hospital Mortality ◽  
Cancer Patients ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Haematological Malignancy ◽  
Solid Cancer ◽  
Solid Malignancy

ObjectivesThis study aims to examine the outcome of haematological and patients with solid cancer presenting with sepsis to the emergency department (ED).DesignSingle-centred, retrospective cohort study. Setting conducted at an academic emergency department of a tertiary hospital.ParticipantsAll patients >18 years of age admitted with sepsis were included.InterventionsPatients were stratified into two groups: haematological and solid malignancy.Primary and secondary outcomeThe primary outcome of the study was in-hospital mortality. Secondary outcomes included intensive care unit (ICU) mortality, ICU and hospital lengths of stay and mechanical ventilation duration.Results442 sepsis cancer patients were included in the study, of which 305 patients (69%) had solid tumours and 137 patients (31%) had a haematological malignancy. The mean age at presentation was 67.92 (±13.32) and 55.37 (±20.85) (p<0.001) for solid and liquid tumours, respectively. Among patients with solid malignancies, lung cancer was the most common source (15.6%). As for the laboratory workup, septic solid cancer patients were found to have a higher white blood count (12 576.90 vs 9137.23; p=0.026). During their hospital stay, a total of 158 (51.8%) patients with a solid malignancy died compared with 57 (41.6%) patients with a haematological malignancy (p=0.047). There was no statistically significant association between cancer type and hospital mortality (OR 1.15 for liquid cancer p 0.58). There was also no statistically significant difference regarding intravenous fluid administration, vasopressor use, steroid use or intubation.ConclusionSolid tumour patients with sepsis or septic shock are at the same risk of mortality as patients with haematological tumours. However, haematological malignancy patients admitted with sepsis or septic shock have higher rates of bacteraemia.

Using a chatbot to reduce emergency department visits and unscheduled hospitalizations among patients with gynecologic malignancies during chemotherapy: a retrospective cohort study (Preprint)

2021 ◽  
Author(s):  
Ming-Yuan Huang ◽  
Chia-Sui Weng ◽  
Hsiao-Li Kuo ◽  
Yung-Cheng Su
Keyword(s):  
Emergency Department ◽  
Cohort Study ◽  
Usual Care ◽  
Cancer Patients ◽  
Retrospective Cohort Study ◽  
Text Messaging ◽  
Retrospective Cohort ◽  
Emergency Department Visits ◽  
Gynecologic Malignancies ◽  
Ed Visits

BACKGROUND A chatbot is an automatic text-messaging tool that creates a dynamic interaction and simulates a human conversation through text or voice via smartphones or computers. A chatbot could be an effective solution for cancer patients’ follow-up during treatment, and could save time for healthcare providers. OBJECTIVE We conducted a retrospective cohort study to evaluate whether a chatbot-based collection of patient-reported symptoms during chemotherapy, with automated alerts to clinicians, could decrease emergency department (ED) visits and hospitalizations. A control group received usual care. METHODS Self-reporting symptoms were communicated via the chatbot, a Facebook Messenger-based interface for patients with gynecologic malignancies. The chatbot included questions about common symptoms experienced during chemotherapy. Patients could also use the text-messaging feature to speak directly to the chatbot, and all reported outcomes were monitored by a cancer manager. The primary and secondary outcomes of the study were emergency department visits and unscheduled hospitalizations after initiation of chemotherapy after diagnosis of gynecologic malignancies. Multivariate Poisson regression models were applied to assess the adjusted incidence rate ratios (aIRRs) for chatbot use for ED visits and unscheduled hospitalizations after controlling for age, cancer stage, type of malignancy, diabetes, hypertension, chronic renal insufficiency, and coronary heart disease. RESULTS Twenty patients were included in the chatbot group, and 43 in the usual-care group. Significantly lower aIRRs for chatbot use for ED visits (0.27; 95% CI 0.11–0.65; p=0.003) and unscheduled hospitalizations (0.31; 95% CI 0.11–0.88; p=0.028) were noted. Patients using the chatbot approach had lower aIRRs of ED visits and unscheduled hospitalizations compared to usual-care patients. CONCLUSIONS The chatbot was helpful for reducing ED visits and unscheduled hospitalizations in patients with gynecologic malignancies who were receiving chemotherapy. These findings are valuable for inspiring the future design of digital health interventions for cancer patients.

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