PURPOSE: We investigated changes in ARDS severity and associations with outcome in COVID-19 ARDS patients.METHODS: We compared outcomes in patients with ARDS classified as 'mild', 'moderate' or 'severe' at calendar day 1, and after reclassification at calendar day 2. The primary endpoint was 28-day mortality. We also identified which ventilatory parameters had an association with presence of severe ARDS at day 2. We repeated the analysis for reclassification at calendar day 4.RESULTS: Of 895 patients, 8.5%, 60.1% and 31.4% had mild, moderate and severe ARDS at day 1. These proportions were 13.5%, 72.6% and 13.9% at day 2. 28-day mortality was 25.3%, 31.3% and 32.0% in patients with mild, moderate and severe ARDS at day 1 (p = 0.537), compared to 28.6%, 29.2% and 44.3% in patients reclassified at day 2 (p = 0.005). No ventilatory parameter had an independent association with presence of severe ARDS at day 2. Findings were not different reclassifying at day 4.CONCLUSIONS: In this cohort of COVID-19 patients, ARDS severity and mortality between severity classes changed substantially over the first 4 days of ventilation. These findings are important, as reclassification could help identify target patients that may benefit from alternative approaches.
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BackgroundEarly identification of older cardiac patients at high risk of readmission or mortality facilitates targeted deployment of preventive interventions. In the Netherlands, the frailty tool of the Dutch Safety Management System (DSMS-tool) consists of (the risk of) delirium, falling, functional impairment, and malnutrition and is currently used in all older hospitalised patients. However, its predictive performance in older cardiac patients is unknown.AimTo estimate the performance of the DSMS-tool alone and combined with other predictors in predicting hospital readmission or mortality within 6 months in acutely hospitalised older cardiac patients.MethodsAn individual patient data meta-analysis was performed on 529 acutely hospitalised cardiac patients ≥70 years from four prospective cohorts. Missing values for predictor and outcome variables were multiply imputed. We explored discrimination and calibration of: (1) the DSMS-tool alone; (2) the four components of the DSMS-tool and adding easily obtainable clinical predictors; (3) the four components of the DSMS-tool and more difficult to obtain predictors. Predictors in model 2 and 3 were selected using backward selection using a threshold of p = 0.157. We used shrunk c-statistics, calibration plots, regression slopes and Hosmer-Lemeshow p-values (PHL) to describe predictive performance in terms of discrimination and calibration.ResultsThe population mean age was 82 years, 52% were males and 51% were admitted for heart failure. DSMS-tool was positive in 45% for delirium, 41% for falling, 37% for functional impairments and 29% for malnutrition. The incidence of hospital readmission or mortality gradually increased from 37 to 60% with increasing DSMS scores. Overall, the DSMS-tool discriminated limited (c-statistic 0.61, 95% 0.56–0.66). The final model included the DSMS-tool, diagnosis at admission and Charlson Comorbidity Index and had a c-statistic of 0.69 (95% 0.63–0.73; PHL was 0.658).DiscussionThe DSMS-tool alone has limited capacity to accurately estimate the risk of readmission or mortality in hospitalised older cardiac patients. Adding disease-specific risk factor information to the DSMS-tool resulted in a moderately performing model. To optimise the early identification of older hospitalised cardiac patients at high risk, the combination of geriatric and disease-specific predictors should be further explored.
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Nursing Leadership is an important competence to develop in order to provide quality of care and prevent attrition of nurses. This research program looked into the perceptions and experiences of nurses on practising leadership. Next to that supporting the development of nursing leadership was addressed. The program has a mixed-method, action research design in which 75 in-depth interviews and 24 focus group interviews and quantitative data of 435 nurses form the backbone. According to hospital nurses, nursing leadership is related to proactiveness and voicing expertise in order to deliver good nursing care. Nevertheless, they do not feel fully competent and knowledge deficits were detected on aspects of the bachelor nursing profile, such as evidence based practice. Working-culture factors can either inhibit or encourage nursing leadership. The further awareness of unconsciously using expertise and knowledge deficits as well as team development towards a continuous safe learning environment are necessary steps for the enhancement of nursing leadership. A Nursing Leadership model was developed in which generic personal leadership competencies combined with expertise of the nurses' level of education and degrees form the essence of shared leadership in teams focussed on the realisation of good nursing care.
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