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INTRODUCTION:The extubation period is one of the most challenging aspects for intensive care teams. Timely recognition of the return to spontaneous ventilation is essential for reducing costs, morbidity, and mortality. Several weaning predictors were studied in an attempt to evaluate the outcome of removing ventilatory support. The purpose of this study was to analyze the predictive performance of the modified integrative weaning index (IWI) in the extubation process. METH-ODS: A prospective study was performed in an ICU in a public hospital in Porto Alegre, Brazil, with 59 adult medical-surgical beds. The final population of the study comprised 153 patients receiving mechanical ventilation for over 48 h who were extubated during the period from February to November 2011. Demographic data and clinical parameters were collected in addition to extubation predictors, including static compliance of the respiratory system, ratio of breathing frequency to tidal volume, tracheal airway-occlusion pressure 0.1 s after the start of inspiratory flow, and modified IWI. RESULTS: Extubation failure was observed in 23 of the subjects (15%). Subjects with greater positive fluid balance, lower hemoglobin levels, and lower levels of bicarbonate presented a higher rate of reintubation. The 3 modified IWI values (the first and 30th minute of the spontaneous breathing trial and the difference between them), as well as the other ventilatory parameters and extubation predictors, displayed poor extubation outcome discrimination accuracy. All indexes presented small areas under the receiver operating characteristic curve, and no accurate cutoff point was identified. CONCLUSIONS: We concluded that modified IWI, similar to other extubation predictors, does not accurately predict extubation failure.

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BackgroundThe first phase of an enterprise risk management (ERM) program is the identification of risks. Accurate identification is essential to a proactive and effective ERM function. The authors identified a lack of such risk identification in the literature and in practical cases when interviewing the chief risk officers from healthcare organizations. A risk inventory specific to healthcare organizations that includes detailed risk scenarios and risk impacts currently does not exist. Thus, the objective of this research is to develop an enterprise risk inventory for healthcare organizations to create a common understanding of how each type of risk impacts a healthcare organization.MethodERM guidelines and data from 15 interviews with chief risk officers were analyzed to create the risk inventory. The identified risks were confirmed through a survey of risk managers from a range of global healthcare organizations during the ASHRM conference in 2017. Descriptive statistics were developed and cluster analysis was performed using the survey results.ResultsThe risk inventory includes 28 risks and their specific risk scenarios. Cyberattack was ranked as the principal risk by the participants, followed by sentinel events and risks associated with human capital management (organizational culture, use of electronic medical records and physician wellness). The data analysis showed that the specific characteristics of the survey participants, such as the length of time working in risk management, the size of the organization, and the presence of a school of medicine, do not impact an individual’s opinion of the importance of the risks identified. A personal background in risk management (clinical or enterprise) was a characteristic that showed a small difference in the perceived importance of the risks from the proposed risk inventory.ConclusionsIn addition to defining specific risk scenarios, the enterprise risk inventory presented in this research can contribute to guiding the risk identification phase of an ERM program and thereby support the development of a risk culture. Patient data security in hospitals that operate with high levels of technology is fundamental to delivering high quality and safe care to patients. At the top of the risk ranking, the identification of cyberattacks reflects the importance that healthcare risk managers place on this risk by allocating time and other resources. Exploring opportunities to improve cyber risk management and evaluating the benefits of using the risk inventory at the beginning of the risk identification phase in an ERM program are suggestions for future studies.Electronic supplementary materialThe online version of this article (10.1186/s12913-018-3400-7) contains supplementary material, which is available to authorized users.

Objectives: To evaluate the effects of 2 different levels of positive end-expiratory pressure on pigs who had unilateral lung transplants. Materials and Methods: A left lung transplant was performed in 12 pigs. The animals were randomized into 2 groups based on positive end-expiratory pressure: group 1 (5 cm H 2 O) and group 2 (10 cm H 2 O). Hemodynamics, gas exchange, and respiratory mechanics were measured before and after surgery. Cytokines, oxidative stress, and histologic scores were assessed in the lung tissue of each pig. Results: Pigs in group 2 exhibited a significantly higher mean heart rate (P = .006), static compliance (P = .001), lower mean arterial pressure (P = .003), and airway resistance (P = .001) than did pigs in group 1. There were no postoperative differences between the groups in concentrations of thiobarbituric acid reactive substances, superoxide dismutase, and interleukin 8. At the end of the observation period, pigs in group 2 had higher levels of thiobarbituric acid reactive substances (P = .001) and interleukin 8 (P = .05), and pigs in group 1 had higher levels of superoxide dismutase (P = .05) than they did at baseline. Conclusions: After unilateral lung transplant, higher positive end-expiratory pressure was associated with improved respiratory mechanics, a negative effect on hemodynamics, a stronger inflammatory response, and increased production of reactive oxygen species, but no effect on gas exchange.

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risk economic assessment orientation is common among health care risk managers. Conclusion: We propose an ERM model for health care (Economic Enterprise Risk Management in Health Care) divided into four maturity levels and complemented by an implementation timeline. The model is accompanied by guidelines to orient the gradual implementation of ERM, including orientation to perform risk economic assessment.