Inventory of current EU paediatric vision and hearing screening programmes

Background: We examined the diversity in paediatric vision and hearing screening programmes in Europe. Methods: Themes relevant for comparison of screening programmes were derived from literature and used to compile three questionnaires on vision, hearing and public-health screening. Tests used, professions involved, age and frequency of testing seem to influence sensitivity, specificity and costs most. Questionnaires were sent to ophthalmologists, orthoptists, otolaryngologists and audiologists involved in paediatric screening in all EU fullmember, candidate and associate states. Answers were cross-checked. Results: Thirty-nine countries participated; 35 have a vision screening programme, 33 a nation-wide neonatal hearing screening programme. Visual acuity (VA) is measured in 35 countries, in 71% more than once. First measurement of VA varies from three to seven years of age, but is usually before the age of five. At age three and four picture charts, including Lea Hyvarinen are used most, in children over four Tumbling-E and Snellen. As first hearing screening test otoacoustic emission (OAE) is used most in healthy neonates, and auditory brainstem response (ABR) in premature newborns. The majority of hearing testing programmes are staged; children are referred after one to four abnormal tests. Vision screening is performed mostly by paediatricians, ophthalmologists or nurses. Funding is mostly by health insurance or state. Coverage was reported as >95% in half of countries, but reporting was often not first-hand. Conclusion: Largest differences were found in VA charts used (12), professions involved in vision screening (10), number of hearing screening tests before referral (1-4) and funding sources (8)

What are the optimum components in a care bundle aimed at reducing post-operative pulmonary complications in high-risk patients?

Background: Post-operative pulmonary complications (POPC) are common, predictable and associated with increased morbidity and mortality, independent of pre-operative risk. Interventions to reduce the incidence of POPC have been studied individually, but the use of a care bundle has not been widely investigated. The purpose of our work was to use Delphi consensus methodology and an independently chosen expert panel to formulate a care bundle for patients identified as being at high of POPC, as preparation towards an evaluation of its effectiveness at reducing POPC.Methods: We performed a survey of members of the ESICM POIC section to inform a Delphi consensus and to share their opinions on a care bundle to reduce POPC, the POPC-CB. We formed a team of 36 experts to participate in and complete an email-based Delphi consensus over three rounds, leading to the formulation of the POPC-CB.Results: The survey had 362 respondents and informed the design of the Delphi consensus. The Delphi consensus resulted in a proposed POPC-CB that incorporates components before surgery-supervised exercise programmes and inspiratory muscle training, during surgery, low tidal volume ventilation with individualised PEEP (positive end-expiratory pressure), use of routine monitoring to avoid hyperoxia and efforts made to limit neuromuscular blockade, and post-operatively, deep breathing exercises and elevation of the head of the bed.Conclusion: A care bundle has been suggested for evaluation in surgical patients at high risk of POPC. Evaluation of feasibility of both implementation and effectiveness is now indicated

Candida bloodstream infections in intensive care units: analysis of the extended prevalence of infection in intensive care unit study

To provide a global, up-to-date picture of the prevalence, treatment, and outcomes of Candida bloodstream infections in intensive care unit patients and compare Candida with bacterial bloodstream infection. DESIGN: A retrospective analysis of the Extended Prevalence of Infection in the ICU Study (EPIC II). Demographic, physiological, infection-related and therapeutic data were collected. Patients were grouped as having Candida, Gram-positive, Gram-negative, and combined Candida/bacterial bloodstream infection. Outcome data were assessed at intensive care unit and hospital discharge. SETTING: EPIC II included 1265 intensive care units in 76 countries. PATIENTS: Patients in participating intensive care units on study day. INTERVENTIONS: None. MEASUREMENT AND MAIN RESULTS: Of the 14,414 patients in EPIC II, 99 patients had Candida bloodstream infections for a prevalence of 6.9 per 1000 patients. Sixty-one patients had candidemia alone and 38 patients had combined bloodstream infections. Candida albicans (n = 70) was the predominant species. Primary therapy included monotherapy with fluconazole (n = 39), caspofungin (n = 16), and a polyene-based product (n = 12). Combination therapy was infrequently used (n = 10). Compared with patients with Gram-positive (n = 420) and Gram-negative (n = 264) bloodstream infections, patients with candidemia were more likely to have solid tumors (p < .05) and appeared to have been in an intensive care unit longer (14 days [range, 5-25 days], 8 days [range, 3-20 days], and 10 days [range, 2-23 days], respectively), but this difference was not statistically significant. Severity of illness and organ dysfunction scores were similar between groups. Patients with Candida bloodstream infections, compared with patients with Gram-positive and Gram-negative bloodstream infections, had the greatest crude intensive care unit mortality rates (42.6%, 25.3%, and 29.1%, respectively) and longer intensive care unit lengths of stay (median [interquartile range]) (33 days [18-44], 20 days [9-43], and 21 days [8-46], respectively); however, these differences were not statistically significant. CONCLUSION: Candidemia remains a significant problem in intensive care units patients. In the EPIC II population, Candida albicans was the most common organism and fluconazole remained the predominant antifungal agent used. Candida bloodstream infections are associated with high intensive care unit and hospital mortality rates and resource use

Validation and utility of ARDS subphenotypes identified by machine-learning models using clinical data: an observational, multicohort, retrospective analysis

International audienceTwo acute respiratory distress syndrome (ARDS) subphenotypes (hyperinflammatory and hypoinflammatory) with distinct clinical and biological features and differential treatment responses have been identified using latent class analysis (LCA) in seven individual cohorts. To facilitate bedside identification of subphenotypes, clinical classifier models using readily available clinical variables have been described in four randomised controlled trials. We aimed to assess the performance of these models in observational cohorts of ARDS. Methods: In this observational, multicohort, retrospective study, we validated two machine-learning clinical classifier models for assigning ARDS subphenotypes in two observational cohorts of patients with ARDS: Early Assessment of Renal and Lung Injury (EARLI; n=335) and Validating Acute Lung Injury Markers for Diagnosis (VALID; n=452), with LCA-derived subphenotypes as the gold standard. The primary model comprised only vital signs and laboratory variables, and the secondary model comprised all predictors in the primary model, with the addition of ventilatory variables and demographics. Model performance was assessed by calculating the area under the receiver operating characteristic curve (AUC) and calibration plots, and assigning subphenotypes using a probability cutoff value of 0·5 to determine sensitivity, specificity, and accuracy of the assignments. We also assessed the performance of the primary model in EARLI using data automatically extracted from an electronic health record (EHR; EHR-derived EARLI cohort). In Large Observational Study to Understand the Global Impact of Severe Acute Respiratory Failure (LUNG SAFE; n=2813), a multinational, observational ARDS cohort, we applied a custom classifier model (with fewer variables than the primary model) to determine the prognostic value of the subphenotypes and tested their interaction with the positive end-expiratory pressure (PEEP) strategy, with 90-day mortality as the dependent variable. Findings: The primary clinical classifier model had an area under receiver operating characteristic curve (AUC) of 0·92 (95% CI 0·90–0·95) in EARLI and 0·88 (0·84–0·91) in VALID. Performance of the primary model was similar when using exclusively EHR-derived predictors compared with manually curated predictors (AUC=0·88 [95% CI 0·81–0·94] vs 0·92 [0·88–0·97]). In LUNG SAFE, 90-day mortality was higher in patients assigned the hyperinflammatory subphenotype than in those with the hypoinflammatory phenotype (414 [57%] of 725 vs 694 [33%] of 2088; p<0·0001). There was a significant treatment interaction with PEEP strategy and ARDS subphenotype (p=0·041), with lower 90-day mortality in the high PEEP group of patients with the hyperinflammatory subphenotype (hyperinflammatory subphenotype: 169 [54%] of 313 patients in the high PEEP group vs 127 [62%] of 205 patients in the low PEEP group; hypoinflammatory subphenotype: 231 [34%] of 675 patients in the high PEEP group vs 233 [32%] of 734 patients in the low PEEP group). Interpretation: Classifier models using clinical variables alone can accurately assign ARDS subphenotypes in observational cohorts. Application of these models can provide valuable prognostic information and could inform management strategies for personalised treatment, including application of PEEP, once prospectively validated. Funding: US National Institutes of Health and European Society of Intensive Care Medicine