52 research outputs found

    Long-Term Outcome of Patients With a Hematologic Malignancy and Multiple Organ Failure Admitted at the Intensive Care

    Get PDF
    Objectives: Historically, patients with a hematologic malignancy have one of the highest mortality rates among cancer patients admitted to the ICU. Therefore, physicians are often reluctant to admit these patients to the ICU. The aim of our study was to examine the survival of patients who have a hematologic malignancy and multiple organ failure admitted to the ICU. Design: This retrospective cohort study, part of the HEMA-ICU study group, was designed to study the survival of patients with a hematologic malignancy and organ failure after admission to the ICU. Patients were followed for at least 1 year. Setting: Five university hospitals in the Netherlands. Patients: One-thousand ninety-seven patients with a hematologic malignancy who were admitted at the ICU. Interventions: None. Measurements and Main Results: Primary outcome was 1-year survival. Organ failure was categorized as acute kidney injury, respiratory failure, hepatic failure, and hemodynamic failure; multiple organ failure was defined as failure of two or more organs. The World Health Organization performance score measured 3 months after discharge from the ICU was used as a measure of functional outcome. The 1-year survival rate among these patients was 38%. Multiple organ failure was inversely associated with long-term survival, and an absence of respiratory failure was the strongest predictor of 1-year survival. The survival rate among patients with 2, 3, and 4 failing organs was 27%, 22%, and 8%, respectively. Among all surviving patients for which World Health Organization scores were available, 39% had a World Health Organization performance score of 0–1 3 months after ICU discharge. Functional outcome was not associated with the number of failing organs. Conclusions: Our results suggest that multiple organ failure should not be used as a criterion for excluding a patient with a hematologic malignancy from admission to the ICU

    Transfusion of fresh frozen plasma in non-bleeding ICU patients -TOPIC TRIAL: study protocol for a randomized controlled trial

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Fresh frozen plasma (FFP) is an effective therapy to correct for a deficiency of multiple coagulation factors during bleeding. In past years, use of FFP has increased, in particular in patients on the Intensive Care Unit (ICU), and has expanded to include prophylactic use in patients with a coagulopathy prior to undergoing an invasive procedure. Retrospective studies suggest that prophylactic use of FFP does not prevent bleeding, but carries the risk of transfusion-related morbidity. However, up to 50% of FFP is administered to non-bleeding ICU patients. With the aim to investigate whether prophylactic FFP transfusions to critically ill patients can be safely omitted, a multi-center randomized clinical trial is conducted in ICU patients with a coagulopathy undergoing an invasive procedure.</p> <p>Methods</p> <p>A non-inferiority, prospective, multicenter randomized open-label, blinded end point evaluation (PROBE) trial. In the intervention group, a prophylactic transfusion of FFP prior to an invasive procedure is omitted compared to transfusion of a fixed dose of 12 ml/kg in the control group. Primary outcome measure is relevant bleeding. Secondary outcome measures are minor bleeding, correction of International Normalized Ratio, onset of acute lung injury, length of ventilation days and length of Intensive Care Unit stay.</p> <p>Discussion</p> <p>The Transfusion of Fresh Frozen Plasma in non-bleeding ICU patients (TOPIC) trial is the first multi-center randomized controlled trial powered to investigate whether it is safe to withhold FFP transfusion to coagulopathic critically ill patients undergoing an invasive procedure.</p> <p>Trial Registration</p> <p>Trial registration: Dutch Trial Register NTR2262 and ClinicalTrials.gov: <a href="http://www.clinicaltrials.gov/ct2/show/NCT01143909">NCT01143909</a></p

    Development and Validation of a Prediction Model for 1-Year Mortality in Patients With a Hematologic Malignancy Admitted to the ICU

    Get PDF
    OBJECTIVES: To develop and validate a prediction model for 1-year mortality in patients with a hematologic malignancy acutely admitted to the ICU. DESIGN: A retrospective cohort study. SETTING: Five university hospitals in the Netherlands between 2002 and 2015. PATIENTS: A total of 1097 consecutive patients with a hematologic malignancy were acutely admitted to the ICU for at least 24 h. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We created a 13-variable model from 22 potential predictors. Key predictors included active disease, age, previous hematopoietic stem cell transplantation, mechanical ventilation, lowest platelet count, acute kidney injury, maximum heart rate, and type of malignancy. A bootstrap procedure reduced overfitting and improved the model's generalizability. This involved estimating the optimism in the initial model and shrinking the regression coefficients accordingly in the final model. We assessed performance using internal-external cross-validation by center and compared it with the Acute Physiology and Chronic Health Evaluation II model. Additionally, we evaluated clinical usefulness through decision curve analysis. The overall 1-year mortality rate observed in the study was 62% (95% CI, 59-65). Our 13-variable prediction model demonstrated acceptable calibration and discrimination at internal-external validation across centers ( C-statistic 0.70; 95% CI, 0.63-0.77), outperforming the Acute Physiology and Chronic Health Evaluation II model ( C-statistic 0.61; 95% CI, 0.57-0.65). Decision curve analysis indicated overall net benefit within a clinically relevant threshold probability range of 60-100% predicted 1-year mortality. CONCLUSIONS: Our newly developed 13-variable prediction model predicts 1-year mortality in hematologic malignancy patients admitted to the ICU more accurately than the Acute Physiology and Chronic Health Evaluation II model. This model may aid in shared decision-making regarding the continuation of ICU care and end-of-life considerations

    Effectiveness of classroom based crew resource management training in the intensive care unit: study design of a controlled trial

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Crew resource management (CRM) has the potential to enhance patient safety in intensive care units (ICU) by improving the use of non-technical skills. However, CRM evaluation studies in health care are inconclusive with regard to the effect of this training on behaviour and organizational outcomes, due to weak study designs and the scarce use of direct observations. Therefore, the aim of this study is to determine the effectiveness and cost-effectiveness of CRM training on attitude, behaviour and organization after one year, using a multi-method approach and matched control units. The purpose of the present article is to describe the study protocol and the underlying choices of this evaluation study of CRM in the ICU in detail.</p> <p>Methods/Design</p> <p>Six ICUs participated in a paired controlled trial, with one pre-test and two post test measurements (respectively three months and one year after the training). Three ICUs were trained and compared to matched control ICUs. The 2-day classroom-based training was delivered to multidisciplinary groups. Typical CRM topics on the individual, team and organizational level were discussed, such as situational awareness, leadership and communication. All levels of Kirkpatrick's evaluation framework (reaction, learning, behaviour and organisation) were assessed using questionnaires, direct observations, interviews and routine ICU administration data.</p> <p>Discussion</p> <p>It is expected that the CRM training acts as a generic intervention that stimulates specific interventions. Besides effectiveness and cost-effectiveness, the assessment of the barriers and facilitators will provide insight in the implementation process of CRM.</p> <p>Trial registration</p> <p>Netherlands Trial Register (NTR): <a href="http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=1976">NTR1976</a></p

    Large-scale ICU data sharing for global collaboration: the first 1633 critically ill COVID-19 patients in the Dutch Data Warehouse

    Get PDF

    The laboratory parameters-derived CoLab score as an indicator of the host response in ICU COVID-19 patients decreases over time: a prospective cohort study

    Get PDF
    The CoLab score was developed and externally validated to rule out COVID-19 among suspected patients presenting at the emergency department. We hypothesized a within-patient decrease in the CoLab score over time in an intensive care unit (ICU) cohort. Such a decrease would create the opportunity to potentially rule out the need for isolation when the infection is overcome. Using linear mixed-effects models, data from the Maastricht Intensive Care COVID (MaastrICCht) cohort were used to investigate the association between time and the CoLab score. Models were adjusted for sex, APACHE II score, ICU mortality, and daily SOFA score. The CoLab score decreased by 0.30 points per day (95% CI − 0.33 to − 0.27), independent of sex, APACHE II, and Mortality. With increasing SOFA score over time, the CoLab score decreased more strongly (− 0.01 (95% CI − 0.01 to − 0.01) additional decrease per one-point increase in SOFA score.) The CoLab score decreased in ICU patients on mechanical ventilation for COVID-19, with a one-point reduction per three days, independent of sex, APACHE II, and ICU mortality, and somewhat stronger with increasing multi-organ failure over time. This suggests that the CoLab score would decrease below a threshold where COVID-19 can be excluded. Afdeling Klinische Chemie en Laboratoriumgeneeskunde (AKCL

    The Dutch Data Warehouse, a multicenter and full-admission electronic health records database for critically ill COVID-19 patients

    Get PDF
    Background The Coronavirus disease 2019 (COVID-19) pandemic has underlined the urgent need for reliable, multicenter, and full-admission intensive care data to advance our understanding of the course of the disease and investigate potential treatment strategies. In this study, we present the Dutch Data Warehouse (DDW), the first multicenter electronic health record (EHR) database with full-admission data from critically ill COVID-19 patients. Methods A nation-wide data sharing collaboration was launched at the beginning of the pandemic in March 2020. All hospitals in the Netherlands were asked to participate and share pseudonymized EHR data from adult critically ill COVID-19 patients. Data included patient demographics, clinical observations, administered medication, laboratory determinations, and data from vital sign monitors and life support devices. Data sharing agreements were signed with participating hospitals before any data transfers took place. Data were extracted from the local EHRs with prespecified queries and combined into a staging dataset through an extract-transform-load (ETL) pipeline. In the consecutive processing pipeline, data were mapped to a common concept vocabulary and enriched with derived concepts. Data validation was a continuous process throughout the project. All participating hospitals have access to the DDW. Within legal and ethical boundaries, data are available to clinicians and researchers. Results Out of the 81 intensive care units in the Netherlands, 66 participated in the collaboration, 47 have signed the data sharing agreement, and 35 have shared their data. Data from 25 hospitals have passed through the ETL and processing pipeline. Currently, 3464 patients are included in the DDW, both from wave 1 and wave 2 in the Netherlands. More than 200 million clinical data points are available. Overall ICU mortality was 24.4%. Respiratory and hemodynamic parameters were most frequently measured throughout a patient's stay. For each patient, all administered medication and their daily fluid balance were available. Missing data are reported for each descriptive. Conclusions In this study, we show that EHR data from critically ill COVID-19 patients may be lawfully collected and can be combined into a data warehouse. These initiatives are indispensable to advance medical data science in the field of intensive care medicine.Perioperative Medicine: Efficacy, Safety and Outcome (Anesthesiology/Intensive Care

    Personalization of medicine requires better observational evidence

    Get PDF
    Evidence-based medicine has become associated with a preference for randomized trials. Randomization is a powerful tool against both known and unknown confounding. However, due to cost-induced constraints in size, randomized trials are seldom able to provide the subgroup analyses needed to gain much insight into effect modification. To apply results to an individual patient, effect modification needs to be considered. Results from randomized trials are therefore often difficult to apply in daily clinical practice. Confounding by indication, which randomization aims to prevent, is caused by more severely ill patients being less or more likely to be treated. Therefore, the prognostic indicators that physicians use to make treatment decisions become confounders. However, these same prognostic indicators a

    Variation in red cell transfusion practice in the intensive care unit - An international survey

    No full text
    PURPOSE: Unclear recommendations in transfusion guidelines may possibly lead to inconsistency in treatment of patients admitted to the intensive care unit. This study aimed to uncover variation in red blood cell (RBC) transfusion decisions in the ICU worldwide. METHODS: Members of the European Society of Intensive Care Medicine (ESICM) were requested to complete an online questionnaire which included four different hypothetical clinical scenarios. The scenarios represented patients with acute myocardial infarction (AMI), abdominal sepsis, traumatic brain injury (TBI) and post-surgical complications. Hemoglobin level was 7∙3 g/dL in all scenarios. The questionnaire explored the physicians' transfusion decision in each clinical scenario and identified patient characteristics that were most influential in the transfusion decision. RESULTS: In total 211 members participated in the study, of whom 142 (67%) completed the entire survey. Most variation was observed in the clinical scenario of sepsis, in which 49% decided to transfuse and 51% decided not to. In the clinical scenarios of AMI, TBI and post-surgical complications this was respectively; 75/25%, 35/65% and 66/34%. CONCLUSIONS: Critical care physicians differed in outcome of RBC transfusion decisions and weighed patient characteristics differently. These findings indicate that variation in transfusion practice amongst critical care physicians exists
    corecore