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  • Original Articles

    Anion gap corrected for albumin, phosphate and lactate is a good predictor of strong ion gap in critically ill patients: a nested cohort study

    Rev Bras Ter Intensiva. 2013;25(3):205-211

    Abstract

    Original Articles

    Anion gap corrected for albumin, phosphate and lactate is a good predictor of strong ion gap in critically ill patients: a nested cohort study

    Rev Bras Ter Intensiva. 2013;25(3):205-211

    DOI 10.5935/0103-507X.20130036

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    OBJECTIVE:

    Corrected anion gap and strong ion gap are commonly used to estimate unmeasured anions. We evaluated the performance of the anion gap corrected for albumin, phosphate and lactate in predicting strong ion gap in a mixed population of critically ill patients. We hypothesized that anion gap corrected for albumin, phosphate and lactate would be a good predictor of strong ion gap, independent of the presence of metabolic acidosis. In addition, we evaluated the impact of strong ion gap at admission on hospital mortality.

    METHODS:

    We included 84 critically ill patients. Correlation and agreement between the anion gap corrected for albumin, phosphate and lactate and strong ion gap was evaluated by the Pearson correlation test, linear regression, a Bland-Altman plot and calculating interclass correlation coefficient. Two subgroup analyses were performed: one in patients with base-excess <-2mEq/L (low BE group - lBE) and the other in patients with base-excess >-2mEq/L (high BE group - hBE). A logistic regression was performed to evaluate the association between admission strong ion gap levels and hospital mortality.

    RESULTS:

    There was a very strong correlation and a good agreement between anion gap corrected for albumin, phosphate and lactate and strong ion gap in the general population (r2=0.94; bias 1.40; limits of agreement -0.75 to 3.57). Correlation was also high in the lBE group (r2=0.94) and in the hBE group (r2=0.92). High levels of strong ion gap were present in 66% of the whole population and 42% of the cases in the hBE group. Strong ion gap was not associated with hospital mortality by logistic regression.

    CONCLUSION:

    Anion gap corrected for albumin, phosphate and lactate and strong ion gap have an excellent correlation. Unmeasured anions are frequently elevated in critically ill patients with normal base-excess. However, there was no association between unmeasured anions and hospital mortality.

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    Anion gap corrected for albumin, phosphate and lactate is a
               good predictor of strong ion gap in critically ill patients: a nested cohort
               study
  • Original Article

    Progression of confirmed COVID-19 cases after the implementation of control measures

    Rev Bras Ter Intensiva. 2020;32(2):213-223

    Abstract

    Original Article

    Progression of confirmed COVID-19 cases after the implementation of control measures

    Rev Bras Ter Intensiva. 2020;32(2):213-223

    DOI 10.5935/0103-507X.20200028

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    ABSTRACT

    Objective:

    To analyse the measures adopted by countries that have shown control over the transmission of coronavirus disease 2019 (COVID-19) and how each curve of accumulated cases behaved after the implementation of those measures.

    Methods:

    The methodology adopted for this study comprises three phases: systemizing control measures adopted by different countries, identifying structural breaks in the growth of the number of cases for those countries, and analyzing Brazilian data in particular.

    Results:

    We noted that China (excluding Hubei Province), Hubei Province, and South Korea have been effective in their deceleration of the growth rates of COVID-19 cases. The effectiveness of the measures taken by these countries could be seen after 1 to 2 weeks of their application. In Italy and Spain, control measures at the national level were taken at a late stage of the epidemic, which could have contributed to the high propagation of COVID-19. In Brazil, Rio de Janeiro and São Paulo adopted measures that could be effective in slowing the propagation of the virus. However, we only expect to see their effects on the growth of the curve in the coming days.

    Conclusion:

    Our results may help decisionmakers in countries in relatively early stages of the epidemic, especially Brazil, understand the importance of control measures in decelerating the growth curve of confirmed cases.

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    Progression of confirmed COVID-19 cases after the implementation of control measures
  • Original Article

    Impact of nonclinical factors on intensive care unit admission decisions: a vignette-based randomized trial (V-TRIAGE)

    Rev Bras Ter Intensiva. 2021;33(2):219-230

    Abstract

    Original Article

    Impact of nonclinical factors on intensive care unit admission decisions: a vignette-based randomized trial (V-TRIAGE)

    Rev Bras Ter Intensiva. 2021;33(2):219-230

    DOI 10.5935/0103-507X.20210029

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    Abstract

    Objective:

    To assess the impact of intensive care unit bed availability, distractors and choice framing on intensive care unit admission decisions.

    Methods:

    This study was a randomized factorial trial using patient-based vignettes. The vignettes were deemed archetypical for intensive care unit admission or refusal, as judged by a group of experts. Intensive care unit physicians were randomized to 1) an increased distraction (intervention) or a control group, 2) an intensive care unit bed scarcity or nonscarcity (availability) setting, and 3) a multiple-choice or omission (status quo) vignette scenario. The primary outcome was the proportion of appropriate intensive care unit allocations, defined as concordance with the allocation decision made by the group of experts.

    Results:

    We analyzed 125 physicians. Overall, distractors had no impact on the outcome; however, there was a differential drop-out rate, with fewer physicians in the intervention arm completing the questionnaire. Intensive care unit bed availability was associated with an inappropriate allocation of vignettes deemed inappropriate for intensive care unit admission (OR = 2.47; 95%CI 1.19 - 5.11) but not of vignettes appropriate for intensive care unit admission. There was a significant interaction with the presence of distractors (p = 0.007), with intensive care unit bed availability being associated with increased intensive care unit admission of vignettes inappropriate for intensive care unit admission in the distractor (intervention) arm (OR = 9.82; 95%CI 2.68 - 25.93) but not in the control group (OR = 1.02; 95%CI 0.38 - 2.72). Multiple choices were associated with increased inappropriate allocation in comparison to the omission group (OR = 5.18; 95%CI 1.37 - 19.61).

    Conclusion:

    Intensive care unit bed availability and cognitive biases were associated with inappropriate intensive care unit allocation decisions. These findings may have implications for intensive care unit admission policies.

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    Impact of nonclinical factors on intensive care unit admission decisions: a vignette-based randomized trial (V-TRIAGE)
  • Original Articles

    Reclassifying the spectrum of septic patients using lactate: severe sepsis, cryptic shock, vasoplegic shock and dysoxic shock

    Rev Bras Ter Intensiva. 2013;25(4):270-278

    Abstract

    Original Articles

    Reclassifying the spectrum of septic patients using lactate: severe sepsis, cryptic shock, vasoplegic shock and dysoxic shock

    Rev Bras Ter Intensiva. 2013;25(4):270-278

    DOI 10.5935/0103-507X.20130047

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    Objective:

    The current definition of severe sepsis and septic shock includes a heterogeneous profile of patients. Although the prognostic value of hyperlactatemia is well established, hyperlactatemia is observed in patients with and without shock. The present study aimed to compare the prognosis of septic patients by stratifying them according to two factors: hyperlactatemia and persistent hypotension.

    Methods:

    The present study is a secondary analysis of an observational study conducted in ten hospitals in Brazil (Rede Amil - SP). Septic patients with initial lactate measurements in the first 6 hours of diagnosis were included and divided into 4 groups according to hyperlactatemia (lactate >4mmol/L) and persistent hypotension: (1) severe sepsis (without both criteria); (2) cryptic shock (hyperlactatemia without persistent hypotension); (3) vasoplegic shock (persistent hypotension without hyperlactatemia); and (4) dysoxic shock (both criteria).

    Results:

    In total, 1,948 patients were analyzed, and the sepsis group represented 52% of the patients, followed by 28% with vasoplegic shock, 12% with dysoxic shock and 8% with cryptic shock. Survival at 28 days differed among the groups (p<0.001). Survival was highest among the severe sepsis group (69%, p<0.001 versus others), similar in the cryptic and vasoplegic shock groups (53%, p=0.39), and lowest in the dysoxic shock group (38%, p<0.001 versus others). In the adjusted analysis, the survival at 28 days remained different among the groups (p<0.001) and the dysoxic shock group exhibited the highest hazard ratio (HR=2.99, 95%CI 2.21-4.05).

    Conclusion:

    The definition of sepsis includes four different profiles if we consider the presence of hyperlactatemia. Further studies are needed to better characterize septic patients, to understand the etiology and to design adequate targeted treatments.

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    Reclassifying the spectrum of septic patients using
               lactate: severe sepsis, cryptic shock, vasoplegic shock and dysoxic
               shock
  • Original Articles

    The Epimed Monitor ICU Database®: a cloud-based national registry for adult intensive care unit patients in Brazil

    Rev Bras Ter Intensiva. 2017;29(4):418-426

    Abstract

    Original Articles

    The Epimed Monitor ICU Database®: a cloud-based national registry for adult intensive care unit patients in Brazil

    Rev Bras Ter Intensiva. 2017;29(4):418-426

    DOI 10.5935/0103-507X.20170062

    Views20

    ABSTRACT

    Objective:

    To describe the Epimed Monitor Database®, a Brazilian intensive care unit quality improvement database.

    Methods:

    We described the Epimed Monitor® Database, including its structure and core data. We presented aggregated informative data from intensive care unit admissions from 2010 to 2016 using descriptive statistics. We also described the expansion and growth of the database along with the geographical distribution of participating units in Brazil.

    Results:

    The core data from the database includes demographic, administrative and physiological parameters, as well as specific report forms used to gather detailed data regarding the use of intensive care unit resources, infectious episodes, adverse events and checklists for adherence to best clinical practices. As of the end of 2016, 598 adult intensive care units in 318 hospitals totaling 8,160 intensive care unit beds were participating in the database. Most units were located at private hospitals in the southeastern region of the country. The number of yearly admissions rose during this period and included a predominance of medical admissions. The proportion of admissions due to cardiovascular disease declined, while admissions due to sepsis or infections became more common. Illness severity (Simplified Acute Physiology Score - SAPS 3 - 62 points), patient age (mean = 62 years) and hospital mortality (approximately 17%) remained reasonably stable during this time period.

    Conclusion:

    A large private database of critically ill patients is feasible and may provide relevant nationwide epidemiological data for quality improvement and benchmarking purposes among the participating intensive care units. This database is useful not only for administrative reasons but also for the improvement of daily care by facilitating the adoption of best practices and use for clinical research.

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    The Epimed Monitor ICU Database®: a cloud-based national registry for adult intensive care unit patients in Brazil

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