Early determinants of death due to multiple organ failure after noncardiac surgery in high-risk patients.

BACKGROUND: Prediction of perioperative cardiac complications is important in the medical management of patients undergoing noncardiac surgery. However, these patients frequently die as a consequence of primary or secondary multiple organ failure (MOF), often as a result of sepsis. We investigated the early perioperative risk factors for in-hospital death due to MOF in surgical patients. METHODS: This was a prospective, multicenter, observational cohort study performed in 21 Brazilian intensive care units (ICUs). Adult patients undergoing noncardiac surgery who were admitted to the ICU within 24 hours after operation were evaluated. MOF was characterized by the presence of at least 2 organ failures. To determine the relative risk (RR) of in-hospital death due to MOF, we performed a logistic regression multivariate analysis. RESULTS: A total of 587 patients were included (mean age, 62.4 ± 17 years). ICU and hospital mortality rates were 15% and 20.6%, respectively. The main cause of death was MOF (53%). Peritonitis (RR 4.17, 95% confidence interval [CI] 1.38-12.6), diabetes (RR 3.63, 95% CI 1.17-11.2), unplanned surgery (RR 3.62, 95% CI 1.18-11.0), age (RR 1.04, 95% CI 1 0.01-1.08), and elevated serum lactate concentrations (RR 1.52, 95% CI 1.14-2.02), a high central venous pressure (RR 1.12, 95% CI 1.04-1.22), a fast heart rate (RR 3.63, 95% CI 1.17-11.2) and pH (RR 0.04, 95% CI 0.0005-0.38) on the day of admission were independent predictors of death due to MOF. CONCLUSIONS: MOF is the main cause of death after surgery in high-risk patients. Awareness of the risk factors for death due to MOF may be important in risk stratification and can suggest routes for therapy.

Characteristics and outcomes of patients with cancer requiring admission to intensive care units: a prospective multicenter study.

OBJECTIVE: To evaluate the characteristics and outcomes of patients with cancer admitted to several intensive care units. Knowledge on patients with cancer requiring intensive care is mostly restricted to single-center studies. DESIGN: : Prospective, multicenter, cohort study. SETTING: Intensive care units from 28 hospitals in Brazil. PATIENTS: A total of 717 consecutive patients included over a 2-mo period. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: There were 667 (93%) patients with solid tumors and 50 (7%) patients had hematologic malignancies. The main reasons for intensive care unit admission were postoperative care (57%), sepsis (15%), and respiratory failure (10%). Overall hospital mortality rate was 30% and was higher in patients admitted because of medical complications (58%) than in emergency (37%) and scheduled (11%) surgical patients (p < .001). Adjusting for covariates other than the type of admission, the number of hospital days before intensive care unit admission (odds ratio [OR], 1.18; 95% confidence interval [CI], 1.01-1.37), higher Sequential Organ Failure Assessment scores (OR, 1.25; 95% CI, 1.17-1.34), poor performance status (OR, 3.40; 95% CI, 2.19 -5.26), the need for mechanical ventilation (OR, 2.42; 95% CI, 1.51-3.87), and active underlying malignancy in recurrence or progression (OR, 2.42; 95% CI, 1.51-3.87) were associated with increased hospital mortality in multivariate analysis. CONCLUSIONS: This large multicenter study reports encouraging survival rates for patients with cancer requiring intensive care. In these patients, mortality was mostly dependent on the severity of organ failures, performance status, and need for mechanical ventilation rather than cancer-related characteristics, such as the type of malignancy or the presence of neutropenia.

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.

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.

Outcomes for patients with cancer admitted to the ICU requiring ventilatory support: results from a prospective multicenter study.

BACKGROUND: This study was undertaken to evaluate the clinical characteristics and outcomes of patients with cancer requiring nonpalliative ventilatory support. METHODS: This was a secondary analysis of a prospective cohort study conducted in 28 Brazilian ICUs evaluating adult patients with cancer requiring invasive mechanical ventilation (MV) or noninvasive ventilation (NIV) during the first 48 h of their ICU stay. We used logistic regression to identify the variables associated with hospital mortality. RESULTS: Of 717 patients, 263 (37%) (solid tumors = 227; hematologic malignancies = 36) received ventilatory support. NIV was initially used in 85 patients (32%), and 178 (68%) received MV. Additionally, NIV followed by MV occurred in 45 patients (53%). Hospital mortality rates were 67% in all patients, 40% in patients receiving NIV only, 69% when NIV was followed by MV, and 73% in patients receiving MV only (P < .001). Adjusting for the type of admission, newly diagnosed malignancy (OR, 3.59; 95% CI, 1.28-10.10), recurrent or progressive malignancy (OR, 3.67; 95% CI, 1.25-10.81), tumoral airway involvement (OR, 4.04; 95% CI, 1.30-12.56), performance status (PS) 2 to 4 (OR, 2.39; 95% CI, 1.24-4.59), NIV followed by MV (OR, 3.00; 95% CI, 1.09-8.18), MV as initial ventilatory strategy (OR, 3.53; 95% CI, 1.45-8.60), and Sequential Organ Failure Assessment score (each point except the respiratory domain) (OR, 1.15; 95% CI, 1.03-1.29) were associated with hospital mortality. Hospital survival in patients with good PS and nonprogressive malignancy and without tumoral airway involvement was 53%. Conversely, patients with poor functional capacity and cancer progression had unfavorable outcomes. CONCLUSIONS: Patients with cancer with good PS and nonprogressive disease requiring ventilatory support should receive full intensive care, because one-half of these patients survive. On the other hand, provision of palliative care should be considered the main goal for patients with poor PS and progressive underlying malignancy.