Characteristics and outcomes of autologous hematopoietic stem cell transplant recipients admitted to intensive care units: A multicenter study.

PURPOSE: Studies of critically ill hematopoietic stem cell transplantation (HSCT) recipients have mainly been single-center and focused on allogenic HSCT recipients. We aimed to describe a cohort of autologous HSCT with an unplanned intensive care unit (ICU) admission. METHODS: This study is a retrospective cohort study of autologous HSCT performed as a treatment for a hematological malignancy, during their first unplanned ICU admission in 50 hospitals in Brazil. We assessed the hospital mortality and the association between mechanical ventilation, vasopressors, and renal replacement therapy and hospital mortality in autologous HSCT recipients, adjusted for potential confounders. RESULTS: We included 301 patients. Multiple myeloma was the most common malignancy driving to HSCT. ICU and hospital mortality were 22.9% and 37.5%, respectively. After adjustment for potential confounders, mechanical ventilation (OR = 9.10; CI 95%, 4.82-17.15) was associated with hospital mortality, but vasopressors (OR = 1.43; CI 95%, 0.77-2.64) and renal replacement therapy (OR = 1.30; CI 95%, 0.63-2.66) were not. CONCLUSIONS: In this large cohort of critically ill autologous HSCT recipients, mechanical ventilation was the only organ support-therapy associated with increased mortality in autologous HSCT recipients.

Trends in clinical profiles, organ support use and outcomes of patients with cancer requiring unplanned ICU admission: a multicenter cohort study.

PURPOSE: To describe trends in outcomes of cancer patients with unplanned admissions to intensive-care units (ICU) according to cancer type, organ support use, and performance status (PS) over an 8-year period. METHODS: We retrospectively analyzed prospectively collected data from all cancer patients admitted to 92 medical-surgical ICUs from July/2011 to June/2019. We assessed trends in mortality through a Bayesian hierarchical model adjusted for relevant clinical confounders and whether there was a reduction in ICU length-of-stay (LOS) over time using a competing risk model. RESULTS: 32,096 patients (8.7% of all ICU admissions; solid tumors, 90%; hematological malignancies, 10%) were studied. Bed/days use by cancer patients increased up to more than 30% during the period. Overall adjusted mortality decreased by 9.2% [95% credible interval (CI), 13.1-5.6%]. The largest reductions in mortality occurred in patients without need for organ support (9.6%) and in those with need for mechanical ventilation (MV) only (11%). Smallest reductions occurred in patients requiring MV, vasopressors, and dialysis (3.9%) simultaneously. Survival gains over time decreased as PS worsened. Lung cancer patients had the lowest decrease in mortality. Each year was associated with a lower sub-hazard for ICU death [SHR 0.93 (0.91-0.94)] and a higher chance of being discharged alive from the ICU earlier [SHR 1.01 (1-1.01)]. CONCLUSION: Outcomes in critically ill cancer patients improved in the past 8 years, with reductions in both mortality and ICU LOS, suggesting improvements in overall care. However, outcomes remained poor in patients with lung cancer, requiring multiple organ support and compromised PS.

Lower Respiratory Tract Infection and Short-Term Outcome in Patients With Acute Respiratory Distress Syndrome.

OBJECTIVE: To assess whether ventilator-associated lower respiratory tract infections (VA-LRTIs) are associated with mortality in critically ill patients with acute respiratory distress syndrome (ARDS). MATERIALS AND METHODS: Post hoc analysis of prospective cohort study including mechanically ventilated patients from a multicenter prospective observational study (TAVeM study); VA-LRTI was defined as either ventilator-associated tracheobronchitis (VAT) or ventilator-associated pneumonia (VAP) based on clinical criteria and microbiological confirmation. Association between intensive care unit (ICU) mortality in patients having ARDS with and without VA-LRTI was assessed through logistic regression controlling for relevant confounders. Association between VA-LRTI and duration of mechanical ventilation and ICU stay was assessed through competing risk analysis. Contribution of VA-LRTI to a mortality model over time was assessed through sequential random forest models. RESULTS: The cohort included 2960 patients of which 524 fulfilled criteria for ARDS; 21% had VA-LRTI (VAT = 10.3% and VAP = 10.7%). After controlling for illness severity and baseline health status, we could not find an association between VA-LRTI and ICU mortality (odds ratio: 1.07; 95% confidence interval: 0.62-1.83; P = .796); VA-LRTI was also not associated with prolonged ICU length of stay or duration of mechanical ventilation. The relative contribution of VA-LRTI to the random forest mortality model remained constant during time. The attributable VA-LRTI mortality for ARDS was higher than the attributable mortality for VA-LRTI alone. CONCLUSION: After controlling for relevant confounders, we could not find an association between occurrence of VA-LRTI and ICU mortality in patients with ARDS.

ICU staffing feature phenotypes and their relationship with patients' outcomes: an unsupervised machine learning analysis.

PURPOSE: To study whether ICU staffing features are associated with improved hospital mortality, ICU length of stay (LOS) and duration of mechanical ventilation (MV) using cluster analysis directed by machine learning. METHODS: The following variables were included in the analysis: average bed to nurse, physiotherapist and physician ratios, presence of 24/7 board-certified intensivists and dedicated pharmacists in the ICU, and nurse and physiotherapist autonomy scores. Clusters were defined using the partition around medoids method. We assessed the association between clusters and hospital mortality using logistic regression and with ICU LOS and MV duration using competing risk regression. RESULTS: Analysis included data from 129,680 patients admitted to 93 ICUs (2014-2015). Three clusters were identified. The features distinguishing between the clusters were: the presence of board-certified intensivists in the ICU 24/7 (present in Cluster 3), dedicated pharmacists (present in Clusters 2 and 3) and the extent of nurse autonomy (which increased from Clusters 1 to 3). The patients in Cluster 3 exhibited the best outcomes, with lower adjusted hospital mortality [odds ratio 0.92 (95% confidence interval (CI), 0.87-0.98)], shorter ICU LOS [subhazard ratio (SHR) for patients surviving to ICU discharge 1.24 (95% CI 1.22-1.26)] and shorter durations of MV [SHR for undergoing extubation 1.61(95% CI 1.54-1.69)]. Cluster 1 had the worst outcomes. CONCLUSION: Patients treated in ICUs combining 24/7 expert intensivist coverage, a dedicated pharmacist and nurses with greater autonomy had the best outcomes. All of these features represent achievable targets that should be considered by policy makers with an interest in promoting equal and optimal ICU care.

Association of frailty with short-term outcomes, organ support and resource use in critically ill patients.

PURPOSE: Frail patients are known to experience poor outcomes. Nevertheless, we know less about how frailty manifests itself in patients' physiology during critical illness and how it affects resource use in intensive care units (ICU). We aimed to assess the association of frailty with short-term outcomes and organ support used by critically ill patients. METHODS: Retrospective analysis of prospective collected data from 93 ICUs in Brazil from 2014 to 2015. We assessed frailty using the modified frailty index (MFI). The primary outcome was in-hospital mortality. Secondary outcomes were discharge home without need for nursing care, ICU and hospital length of stay (LOS), and utilization of ICU organ support and transfusion. We used mixed logistic regression and competing risk models accounting for relevant confounders in outcome analyses. RESULTS: The analysis consisted of 129,680 eligible patients. There were 40,779 (31.4%) non-frail (MFI = 0), 64,407 (49.7%) pre-frail (MFI = 1-2) and 24,494 (18.9%) frail (MFI ≥ 3) patients. After adjusted analysis, frailty was associated with higher in-hospital mortality (OR 2.42, 95% CI 1.89-3.08), particularly in patients admitted with lower SOFA scores. Frail patients were less likely to be discharged home (OR 0.36, 95% CI 0.54-0.79) and had higher hospital and ICU LOS than non-frail patients. Use of all forms of organ support (mechanical ventilation, non-invasive ventilation, vasopressors, dialysis and transfusions) were more common in frail patients and increased as MFI increased. CONCLUSIONS: Frailty, as assessed by MFI, was associated with several patient-centered endpoints including not only survival, but also ICU LOS and organ support.

Role of organisational factors on the 'weekend effect' in critically ill patients in Brazil: a retrospective cohort analysis.

INTRODUCTION: Higher mortality for patients admitted to intensive care units (ICUs) during the weekends has been occasionally reported with conflicting results that could be related to organisational factors. We investigated the effects of ICU organisational and staffing patterns on the potential association between weekend admission and outcomes in critically ill patients. METHODS: We included 59 614 patients admitted to 78 ICUs participating during 2013. We defined 'weekend admission' as any ICU admission from Friday 19:00 until Monday 07:00. We assessed the association between weekend admission with hospital mortality using a mixed logistic regression model controlling for both patient-level (illness severity, age, comorbidities, performance status and admission type) and ICU-level (decrease in nurse/bed ratio on weekend, full-time intensivist coverage, use of checklists on weekends and number of institutional protocols) confounders. We performed secondary analyses in the subgroup of scheduled surgical admissions. RESULTS: A total of 41 894 patients (70.3%) were admitted on weekdays and 17 720 patients (29.7%) on weekends. In univariable analysis, weekend admitted patients had higher ICU (10.9% vs 9.0%, P<0.001) and hospital (16.5% vs 13.5%, P<0.001) mortality. After adjusting for confounders, weekend admission was not associated with higher hospital mortality (OR 1.05, 95% CI 0.99 to 1.12, P=0.095). However, a 'weekend effect' was still observed in scheduled surgical admissions, as well as in ICUs not using checklists during the weekends. For unscheduled admissions, no 'weekend effect' was observed regardless of ICU's characteristics. For scheduled surgical admissions, a 'weekend effect' was present only in ICUs with a low number of implemented protocols and those with a reduction in the nurse/bed ratio and not applying checklists during weekends. CONCLUSIONS: ICU organisational factors, such as decreased nurse-to-patient ratio, absence of checklists and fewer standardised protocols, may explain, in part, increases in mortality in patients admitted to the ICU mortality on weekends.

Effects of Organizational Characteristics on Outcomes and Resource Use in Patients With Cancer Admitted to Intensive Care Units.

PURPOSE: To investigate the impact of organizational characteristics and processes of care on hospital mortality and resource use in patients with cancer admitted to intensive care units (ICUs). PATIENTS AND METHODS: We performed a retrospective cohort study of 9,946 patients with cancer (solid, n = 8,956; hematologic, n = 990) admitted to 70 ICUs (51 located in general hospitals and 19 in cancer centers) during 2013. We retrieved patients' clinical and outcome data from an electronic ICU quality registry. We surveyed ICUs regarding structure, organization, staffing patterns, and processes of care. We used mixed multivariable logistic regression analysis to identify characteristics associated with hospital mortality and efficient resource use in the ICU. RESULTS: Median number of patients with cancer per center was 110 (interquartile range, 58 to 154), corresponding to 17.9% of all ICU admissions. ICU and hospital mortality rates were 15.9% and 25.4%, respectively. After adjusting for relevant patient characteristics, presence of clinical pharmacists in the ICU (odds ratio [OR], 0.67; 95% CI, 0.49 to 0.90), number of protocols (OR, 0.92; 95% CI, 0.87 to 0.98), and daily meetings between oncologists and intensivists for care planning (OR, 0.69; 95% CI, 0.52 to 0.91) were associated with lower mortality. Implementation of protocols (OR, 1.52; 95% CI, 1.11 to 2.07) and meetings between oncologists and intensivists (OR, 4.70; 95% CI, 1.15 to 19.22) were also independently associated with more efficient resource use. Neither admission to ICUs in cancer centers compared with general hospitals nor annual case volume had an impact on mortality or resource use. CONCLUSION: Organizational aspects, namely the implementation of protocols and presence of clinical pharmacists in the ICU, and close collaboration between oncologists and ICU teams are targets to improve mortality and resource use in critically ill patients with cancer.

Organizational characteristics, outcomes, and resource use in 78 Brazilian intensive care units: the ORCHESTRA study.

PURPOSE: Detailed information on organization and process of care in intensive care units (ICU) in emerging countries is scarce. Here, we investigated the impact of organizational factors on the outcomes and resource use in a large sample of Brazilian ICUs. METHODS: Retrospective cohort study of 59,693 patients (medical admissions, 67 %) admitted to 78 ICUs during 2013. We retrieved patients' data from an ICU quality registry and surveyed ICUs regarding structure, organization, staffing patterns, and process of care. We used multilevel logistic regression analysis to identify factors associated with hospital mortality. Efficient resource use was assessed by estimating standardized resource use and mortality rates adjusted for the SAPS 3 score. RESULTS: ICUs were mostly medical-surgical (79 %) and located at private hospitals (86 %). Median nurse to bed ratio was 0.20 (IQR, 0.15-0.28) and board-certified intensivists were present 24/7 in 16 (21 %) of ICUs. Multidisciplinary rounds occurred in 67 (86 %) and daily checklists were used in 36 (46 %) ICUs. Most frequent protocols focused on sepsis management and prevention of healthcare-associated infections. Hospital mortality was 14.4 %. In multivariable analysis, the number of protocols was the only organizational characteristic associated with mortality [odds ratio = 0.944 (95 % CI 0.904-0.987)]. The effects of protocols were consistent across subgroups including surgical and medical patients as well as the SAPS 3 tertiles. We also observed a significant trend toward efficient resource use as the number of protocols increased. CONCLUSIONS: In emerging countries such as Brazil, organizational factors, including the implementation of protocols, are potential targets to improve patient outcomes and resource use in ICUs.