Antonio Paulo Nassar

Constipation in intensive care unit: Incidence and risk factors

PURPOSE Although gastrointestinal motility disorders are common in critically ill patients, constipation and its implications have received very little attention. We aimed to determine the incidence of constipation to find risk factors and its implications in critically ill patients MATERIALS AND METHODS During a 6-month period, we enrolled all patients admitted to an intensive care unit from an universitary hospital who stayed 3 or more days. Patients submitted to bowel surgery were excluded. RESULTS Constipation occurred in 69.9% of the patients. There was no difference between constipated and not constipated in terms of sex, age, Acute Physiology and Chronic Health Evaluation II, type of admission (surgical, clinical, or trauma), opiate use, antibiotic therapy, and mechanical ventilation. Early (<24 hours) enteral nutrition was associated with less constipation, a finding that persisted at multivariable analysis (P < .01). Constipation was not associated with greater intensive care unit or mortality, length of stay, or days free from mechanical ventilation. CONCLUSIONS Constipation is very common among critically ill patients. Early enteral nutrition is associated with earlier return of bowel function.

Clinical outcomes of patients requiring ventilatory support in Brazilian intensive care units: a multicenter, prospective, cohort study

IntroductionContemporary information on mechanical ventilation (MV) use in emerging countries is limited. Moreover, most epidemiological studies on ventilatory support were carried out before significant developments, such as lung protective ventilation or broader application of non-invasive ventilation (NIV). We aimed to evaluate the clinical characteristics, outcomes and risk factors for hospital mortality and failure of NIV in patients requiring ventilatory support in Brazilian intensive care units (ICU).MethodsIn a multicenter, prospective, cohort study, a total of 773 adult patients admitted to 45 ICUs over a two-month period requiring invasive ventilation or NIV for more than 24 hours were evaluated. Causes of ventilatory support, prior chronic health status and physiological data were assessed. Multivariate analysis was used to identifiy variables associated with hospital mortality and NIV failure.ResultsInvasive MV and NIV were used as initial ventilatory support in 622 (80%) and 151 (20%) patients. Failure with subsequent intubation occurred in 54% of NIV patients. The main reasons for ventilatory support were pneumonia (27%), neurologic disorders (19%) and non-pulmonary sepsis (12%). ICU and hospital mortality rates were 34% and 42%. Using the Berlin definition, acute respiratory distress syndrome (ARDS) was diagnosed in 31% of the patients with a hospital mortality of 52%. In the multivariate analysis, age (odds ratio (OR), 1.03; 95% confidence interval (CI), 1.01 to 1.03), comorbidities (OR, 2.30; 95% CI, 1.28 to 3.17), associated organ failures (OR, 1.12; 95% CI, 1.05 to 1.20), moderate (OR, 1.92; 95% CI, 1.10 to 3.35) to severe ARDS (OR, 2.12; 95% CI, 1.01 to 4.41), cumulative fluid balance over the first 72 h of ICU (OR, 2.44; 95% CI, 1.39 to 4.28), higher lactate (OR, 1.78; 95% CI, 1.27 to 2.50), invasive MV (OR, 2.67; 95% CI, 1.32 to 5.39) and NIV failure (OR, 3.95; 95% CI, 1.74 to 8.99) were independently associated with hospital mortality. The predictors of NIV failure were the severity of associated organ dysfunctions (OR, 1.20; 95% CI, 1.05 to 1.34), ARDS (OR, 2.31; 95% CI, 1.10 to 4.82) and positive fluid balance (OR, 2.09; 95% CI, 1.02 to 4.30).ConclusionsCurrent mortality of ventilated patients in Brazil is elevated. Implementation of judicious fluid therapy and a watchful use and monitoring of NIV patients are potential targets to improve outcomes in this setting.Trial registrationClinicalTrials.gov NCT01268410.

Caution when using prognostic models: A prospective comparison of 3 recent prognostic models

PURPOSE Prognostic models have been developed to estimate mortality and to compare outcomes in different intensive care units. However, these models need to be validated before their use in different populations. In this study, we assessed the performance of 3 recently developed general prognostic models (Acute Physiologic and Chronic Health Evaluation [APACHE] IV, Simplified Acute Physiology Score [SAPS] 3 and Mortality Probability Model III [MPM(0)-III]) in a population admitted at 3 medical-surgical Brazilian intensive care units. MATERIALS AND METHODS All patients admitted from July 2008 to December 2009 were evaluated for inclusion in the study. Standardized mortality ratios were calculated for all models. Calibration was assessed by the Hosmer-Lemeshow goodness-of-fit test. Discrimination was evaluated using the area under the receiver operator curve. RESULTS A total of 5780 patients were included. Inhospital mortality was 9.1%. Discrimination was very good for all models (area under the receiver operator curve for APACHE IV, SAPS 3 and MPM(0)-III was 0.883, 0.855 and 0.840, respectively). APACHE IV showed better discrimination than SAPS 3 and MPM(0)-III (P < .001 for both comparisons). All models calibrated poorly and overestimated hospital mortality (Hosmer-Lemeshow statistic was 53.7, 134.2, 226.6 for APACHE IV, MPM(0)-III, and SAPS 3, respectively; P < .001 for all). CONCLUSIONS In this study, all models showed poor calibration, while discrimination was very good for all of them. As this has been a common finding in validation studies, caution is warranted when using prognostic models for benchmarking.

Evaluation of simplified acute physiology score 3 performance: a systematic review of external validation studies

IntroductionSimplified Acute Physiology Score 3 (SAPS 3) was the first critical care prognostic model developed from worldwide data. We aimed to systematically review studies that assessed the prognostic performance of SAPS 3 general and customized models for predicting hospital mortality in adult patients admitted to the ICU.MethodsMedline, Lilacs, Scielo and Google Scholar were searched to identify studies which assessed calibration and discrimination of general and customized SAPS 3 equations. Additionally, we decided to evaluate the correlation between trial size (number of included patients) and the Hosmer-Lemeshow (H-L) statistics value of the SAPS 3 models.ResultsA total of 28 studies were included. Of these, 11 studies (42.8%) did not find statistically significant mis-calibration for the SAPS 3 general equation. There was a positive correlation between number of included patients and higher H-L statistics, that is, a statistically significant mis-calibration of the model (r = 0.747, P <0.001). Customized equations for major geographic regions did not have statistically significant departures from perfect calibration in 9 of 19 studies. Five studies (17.9%) developed a regional customization and in all of them this new model was not statistically different from a perfect calibration for their populations. Discrimination was at least very good in 24 studies (85.7%).ConclusionsStatistically significant departure from perfect calibration for the SAPS 3 general equation was common in validation studies and was correlated with larger studies, as should be expected, since H-L statistics (both C and H) are strongly dependent on sample size This finding was also present when major geographic customized equations were evaluated. Local customizations, on the other hand, improved SAPS 3 calibration. Discrimination was almost always very good or excellent, which gives excellent perspectives for local customization when a precise local estimate is needed.

Protocolized sedation effect on post-ICU posttraumatic stress disorder prevalence: A systematic review and network meta-analysis

PURPOSE Strategies aiming light sedation are associated with decreased length on mechanical ventilation. However, awake or easily arousable patients may be prone to greater prevalence of posttraumatic stress disorder (PTSD). These systematic review and meta-analysis aimed to evaluate the safety of light sedation strategies regarding the prevalence of PTSD. METHODS We searched MEDLINE, Scopus, and Web of Science from inception to November 2014 for randomized controlled trials that evaluated light sedation strategies and addressed PTSD prevalence in the follow-up as a specific outcome. Because not all trials performed the same comparisons, we performed a network meta-analysis to evaluate indirect comparisons. RESULTS Five studies fulfilled our inclusion criteria and were included in the meta-analysis. Two studies compared daily sedation interruption with usual care (92 patients), 2 studies compared a light sedation protocol with daily sedation interruption (47 patients), and 1 study compared light and deep sedation (102 patients). Compared with usual sedation care/deep sedation, neither daily interruption of sedation (odds ratio=0.66; 95% confidence interval, 0.22-1.98) nor a light sedation protocol (odds ratio=0.90, 95% confidence interval, 0.27-3.05) was associated with increased risks on long-term PTSD prevalence. CONCLUSION Light sedation strategies seem to be safe in terms of PTSD prevalence. However, the small number of included trials and patients may not be sufficient to drive strong statements.

Early Versus Late Initiation of Renal Replacement Therapy in Critically Ill Patients: Systematic Review and Meta-Analysis.

Objective: Early initiation of renal replacement therapy (RRT) effect on survival and renal recovery of critically ill patients is still uncertain. We aimed to systematically review current evidence comparing outcomes of early versus late initiation of RRT in critically ill patients. Methods: We searched the Medline (via Pubmed), LILACS, Science Direct, and CENTRAL databases from inception until November 2016 for randomized clinical trials (RCTs) or observational studies comparing early versus late initiation of RRT in critically ill patients. The primary outcome was mortality. Duration of mechanical ventilation, intensive care unit (ICU) length of stay (LOS), hospital LOS, and renal function recovery were secondary outcomes. Meta-analysis and trial sequential analysis (TSA) were used for the primary outcome. Results: Sixty-two studies were retrieved and analyzed, including 11 RCTs. There was no difference in mortality between early and late initiation of RRT among RCTs (odds ratio [OR] = 0.78; 95% confidence interval [CI]: 0.52-1.19; I2 = 63.1%). Trial sequential analysis of mortality across all RCTs achieved futility boundaries at both 1% and 5% type I error rates, although a subgroup analysis of studies including only acute kidney injury patients was not conclusive. There was also no difference in time on mechanical ventilation, ICU and hospital LOS, or renal recovery among studies. Early initiation of RRT was associated with reduced mortality among prospective (OR = 0.69; 95% CI: 0.49-0.96; I2 = 85.9%) and retrospective (OR = 0.61; 95% CI: 0.41-0.92; I2 = 90.9%) observational studies, both with substantial heterogeneity. However, subgroup analysis excluding low-quality observational studies did not achieve statistical significance. Conclusion: Pooled analysis of randomized trials indicates early initiation of RRT is not associated with lower mortality rates. The potential benefit of reduced mortality associated with early initiation of RRT was limited to low-quality observational studies.

Oncologists’ and Intensivists’ Attitudes Toward the Care of Critically Ill Patients with Cancer

Background: Patients with cancer represent an important proportion of intensive care unit (ICU) admissions. Oncologists and intensivists have distinct knowledge backgrounds, and conflicts about the appropriate management of these patients may emerge. Methods: We surveyed oncologists and intensivists at 2 academic cancer centers regarding their management of 2 hypothetical patients with different cancer types (metastatic pancreatic cancer and metastatic breast cancer with positive receptors for estrogen, progesterone, and HER-2) who develop septic shock and multiple organ failure. Results: Sixty intensivists and 46 oncologists responded to the survey. Oncologists and intensivists similarly favored withdrawal of life support measures for the patient with pancreatic cancer (33/46 [72%] vs 48/60 [80%], P = .45). On the other hand, intensivists favored more withdrawal of life support measures for the patient with breast cancer compared to oncologists (32/59 [54%] vs 9/44 [21%], P < .001). In the multinomial logistic regression, the oncology specialists were more likely to advocate for a full-code status for the patient with breast cancer (OR = 5.931; CI 95%, 1.762-19.956; P = .004). Conclusions: Oncologists and intensivists share different views regarding life support measures in critically ill patients with cancer. Oncologists tend to focus on the cancer characteristics, whereas intensivists focus on multiple organ failure when weighing in on the same decisions. Regular meetings between oncologists and intensivists may reduce possible conflicts regarding the critical care of patients with cancer.

ICU physicians are unable to accurately predict length of stay at admission: a prospective study

OBJECTIVE To evaluate the accuracy of prediction of intensive care unit length of stay made by physicians at patient admission. DESIGN Prospective cohort study. SETTING Three medical-surgical intensive care units in an oncology hospital. PATIENTS All patients admitted between January and December 2014. INTERVENTIONS None. MAIN OUTCOME MEASUREMENTS Intensive care unit (ICU) length of stay was estimated by the physicians responsible for patient admission and categorized as <48 h, 2-5 days or more than 5 days. Agreement between predicted and actual intensive care unit length of stay was calculated. RESULTS A total of 2955 patients were admitted during the study period. Physicians accurately predicted ICU length of stay in 1557 (52.7%) admissions. ICU length of stay was underestimated in 864 (29.2%) and overestimated in 534 (18.1%) cases. Agreement between predicted and actual intensive care unit length of stay was poor (Kappa = 0.22) and not associated with physician characteristics. Predictions of an intensive care unit length of stay of >5 days were significantly less accurate than those of <48 h and of 2-5 days (31.1, 59.8 and 53.1%, respectively, P < 0.001). CONCLUSIONS The intensive care unit length of stay prediction in these oncological intensive care units is inaccurate and, ideally, should not be made at admission.

Accuracy of SOFA, qSOFA, and SIRS scores for mortality in cancer patients admitted to an intensive care unit with suspected infection

Purpose: To compare the prognostic accuracy of Sequential Organ Failure Assessment (SOFA) and quick SOFA (qSOFA) with systemic inflammatory response syndrome (SIRS) criteria in critically ill cancer patients with suspected infection. Methods: Data for 450 cancer patients admitted to an intensive care unit (ICU) in 2014 with a suspected infection were retrospectively analyzed. Sensitivity, specificity, and area under the receiver operating curve (AUC) values for SOFA, qSOFA, and SIRS criteria for ICU and hospital mortalities were calculated. Mortalities according to Sepsis‐2 stratification (e.g., sepsis, severe sepsis, and septic shock) and Sepsis‐3 stratification (e.g., infection, sepsis, and septic shock) were also compared. Results: SOFA outperformed SIRS in predicting mortalities for ICU [(AUC, 0.76; 95% confidence interval (CI) 95%, 0.71–0.81) vs. (AUC, 0.62; 95% CI, 0.56–0.67), p<.01] and hospital [(AUC, 0.69; 95% CI, 0.65–0.74) vs. (AUC, 0.58; 95% CI, 0.52–0.63), p<.01)] patients. Similarly, qSOFA outperformed SIRS for both settings [(AUC, 0.71; 95% CI, 0.65–0.76, p=.02) vs. (AUC, 0.69; 95% CI, 0.64–0.74; p<.01), respectively]. Conclusions: SOFA and qSOFA were more sensitive and accurate than SIRS in predicting ICU and hospital mortality for critically ill cancer patients with suspected infection.

Nebulized Antibiotics for Ventilator-associated Pneumonia: Next Steps After the Meta-analyses

Ventilator-associated pneumonia (VAP) represents a major clinical challenge for all physicians caring for critically ill patients. Important concerns regarding the optimum treatment regimen for the management of pulmonary infections—such as the choice of antibiotic, the dosing, the duration of therapy, and drug delivery to the infected tissue—play an even more prominent role in the management of VAP. Patients with VAP are usually severely ill and have already been exposed to prolonged periods of intensive care; therefore, the safety margin for error is narrowed. Nebulized antibiotics represent a promising way to deliver high doses to the lung tissue with fewer concerns regarding systemic toxicity. In the context of multidrug-resistant VAP, where therapeutic options may be reduced to more toxic drugs, nebulized antibiotics may be a reasonable and logical choice. While most studies focused on the adjunctive role (ie, complementary to intravenous infusion) of nebulized antibiotics, some reports have suggested that nebulization may be effective even as a single therapy. Nevertheless, important differences in nebulization techniques contribute to the difficulty in obtaining robust data regarding the efficacy of nebulized therapy. Two recent meta-analyses have evaluated the role of nebulized antibiotics for VAP, one of them focusing specifically on nebulized polymyxin and the other assessing the role of nebulization therapy regardless of the drug used. Although conceptually different, both studies concluded that nebulized therapy could indeed play a significant role in the management of VAP. In this review, we reassess the evidence for nebulized antibiotics and provide guidance for future studies in this field to fill the knowledge gaps.