Clinical Characteristics and In-Hospital Mortality of Cardiac Arrest Survivors in Brazil: A Large Retrospective Multicenter Cohort Study.

OBJECTIVES: Data on cardiac arrest survivors from developing countries are scarce. This study investigated clinical characteristics associated with in-hospital mortality in resuscitated patients following cardiac arrest in Brazil. DESIGN: Retrospective analysis of prospectively collected data. SETTING: Ninety-two general ICUs from 55 hospitals in Brazil between 2014 and 2015. PATIENTS: Adult patients with cardiac arrest admitted to the ICU. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We analyzed 2,296 patients (53% men; median 67 yr (interquartile range, 54-79 yr]). Eight-hundred patients (35%) had a primary admission diagnosis of cardiac arrest suggesting an out-of-hospital cardiac arrest; the remainder occurred after admission, comprising an in-hospital cardiac arrest cohort. Overall, in-hospital mortality was 83%, with only 6% undergoing withholding/withdrawal-of-life support. Random-effects multivariable Cox regression was used to assess associations with survival. After adjusting for age, sex, and severity scores, mortality was associated with shock (adjusted odds ratio, 1.25 [95% CI, 1.11-1.39]; p < 0.001), temperature dysregulation (adjusted odds ratio for normothermia, 0.85 [95% CI, 0.76-0.95]; p = 0.007), increased lactate levels above 4 mmol/L (adjusted odds ratio, 1.33 [95% CI, 1.1-1.6; p = 0.009), and surgical or cardiac cases (adjusted odds ratio, 0.72 [95% CI, 0.6-0.86]; p = 0.002). In addition, survival was better in patients with probable out-of-hospital cardiac arrest, unless ICU admission was delayed (adjusted odds ratio for interaction, 1.63 [95% CI, 1.21-2.21]; p = 004). CONCLUSIONS: In a large multicenter cardiac arrest cohort from Brazil, we found a high mortality rate and infrequent withholding/withdrawal of life support. We also identified patient profiles associated with worse survival, such as those with shock/hypoperfusion and arrest secondary to nonsurgical admission diagnoses. Our findings unveil opportunities to improve postarrest care in developing countries, such as prompt ICU admission, expansion of the use of targeted temperature management, and implementation of shock reversal strategies (i.e., early coronary angiography), according to modern guidelines recommendations.

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.

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.

The effects of performance status one week before hospital admission on the outcomes of critically ill patients.

PURPOSE: To assess the impact of performance status (PS) impairment 1 week before hospital admission on the outcomes in patients admitted to intensive care units (ICU). METHODS: Retrospective cohort study in 59,693 patients (medical admissions, 67 %) admitted to 78 ICUs during 2013. We classified PS impairment according to the Eastern Cooperative Oncology Group (ECOG) scale in absent/minor (PS = 0-1), moderate (PS = 2) or severe (PS = 3-4). We used univariate and multivariate logistic regression analyses to investigate the association between PS impairment and hospital mortality. RESULTS: PS impairment was moderate in 17.3 % and severe in 6.9 % of patients. The hospital mortality was 14.4 %. Overall, the worse the PS, the higher the ICU and hospital mortality and length of stay. In addition, patients with worse PS were less frequently discharged home. PS impairment was associated with worse outcomes in all SAPS 3, Charlson Comorbidity Index and age quartiles as well as according to the admission type. Adjusting for other relevant clinical characteristics, PS impairment was associated with higher hospital mortality (odds-ratio (OR) = 1.96 (95 % CI 1.63-2.35), for moderate and OR = 4.22 (3.32-5.35), for severe impairment). The effects of PS on the outcome were particularly relevant in the medium range of severity-of-illness. These results were consistent in the subgroup analyses. However, adding PS impairment to the SAPS 3 score improved only slightly its discriminative capability. CONCLUSION: PS impairment was associated with worse outcomes independently of other markers of chronic health status, particularly for patients in the medium range of severity of illness.