Economic and Humanistic Burden in Paediatric Patients with Atopic Dermatitis

Data concerning the economic and humanistic burden in patients with paediatric atopic dermatitis (AD) and their families are scarce. This retrospective study investigated these burdens in paediatric patients with AD using maintenance treatment with topical corticosteroids and/or conventional systemic immunosuppressants. Patient-reported outcomes regarding quality of life, AD severity, and parental work-related impairment were completed at inclusion. Data on healthcare resource utilization and medication prescription were collected retrospectively over the previous 12 months. Patients were categorized into mild, moderate or severe AD, based on Eczema Area and Severity Index score and medication use. Costs per patient per year per AD severity category were calculated. A total of 101 patients (median age 11.0 years (interquartile range 7.5-14.0), 47.5% men) were included, of whom 38 had mild AD, 37 moderate AD, and 26 severe AD. Mean ± standard deviation (SD) total costs patient per year for mild, moderate and severe AD were €1,812 ± €1,280, €2,680 ± €3,127, and €5,861 ±  €3,993, respectively. Highest total direct and indirect costs were found in patients with severe AD, mainly due to higher healthcare and medication costs. Highest humanistic burden was found in patients with moderate AD. For example, the median (interquartile range) Patient-Oriented Eczema Measure score was significantly higher in these patients compared with mild and severe AD (19.0 (15.0-24.0) vs 12.0 (8.8-15.0) and 17.0 (9.5-22.0), respectively). AD in paediatric patients incurs considerable direct and indirect costs, especially in patients with severe AD. The high humanistic burden in patients with moderate AD underlines the need for effective and safe new treatment options for children with AD

High dissolved organic carbon release by benthic cyanobacterial mats in a Caribbean reef ecosystem

International audienceBenthic cyanobacterial mats (BCMs) are increasing in abundance on coral reefs worldwide. However, their impacts on biogeochemical cycling in the surrounding water and sediment are virtually unknown. By measuring chemical fluxes in benthic chambers placed over sediment covered by BCMs and sediment with BCMs removed on coral reefs in Curaçao, Southern Caribbean, we found that sediment covered by BCMs released 1.4 and 3.5 mmol C m 22 h 21 of dissolved organic carbon (DOC) during day and night, respectively. Conversely, sediment with BCMs removed took up DOC, with day and night uptake rates of 0.9 and 0.6 mmol C m 22 h 21. DOC release by BCMs was higher than reported rates for benthic algae (turf and macroalgae) and was estimated to represent 79% of the total DOC released over a 24 h diel cycle at our study site. The high nocturnal release of DOC by BCMs is most likely the result of anaerobic metabolism and degradation processes, as shown by high respiration rates at the mat surface during nighttime. We conclude that BCMs are significant sources of DOC. Their increased abundance on coral reefs will lead to increased DOC release into the water column, which is likely to have negative implications for reef health.

Caribbean reef ecosystem

dissolved organic carbon releas

The impact of postoperative complications on health-related quality of life in older patients with rectal cancer : a prospective cohort study

Objectives: As result of the aging population and increasing rectal cancer incidence, more older patients undergo treatment for rectal cancer. This study compares treatment course, postoperative complications, and quality of life (QOL) between older and younger patients with rectal cancer and evaluates the impact of postoperative complications on QOL in the elderly. Materials and Methods: Patients with rectal cancer participating in a prospective colorectal cancer cohort and referred for radiotherapy between 2013 and 2016 were included. QOL was assessed with the cancer questionnaire of the European Organisation for Research and Treatment of Cancer (EORTC QLQ-C30) before treatment and at three, six, and twelve months. Outcomes were compared between older patients (≥ 70 years) and younger patients (< 70 years) and stratified by presence of postoperative complications. Results: In total, 115 (33%) older patients and 230 (67%) younger patients were included. Compared to younger patients, older patients underwent significantly more often short-course radiation with delayed surgery (6.1% and 19.1% respectively) and less often chemoradiation (62.6% and 39.1% respectively), and were more likely to undergo a Hartmann procedure with permanent stoma (3.5% and 13.0% respectively) instead of sphincter-sparing surgery (43.9% and 29.6% respectively). Postoperative complication rates were similar (38.5% in older patients versus 34.7% in younger patients). Older patients had worse physical functioning at six and twelve months after diagnosis compared to younger patients. Presence of postoperative complications had a significant stronger impact on physical- and role functioning in older patients. Conclusion: Older patients undergo more often a tailored treatment approach for rectal cancer than younger patients. With this tailored approach, similar postoperative complication rates and QOL are achieved. However, postoperative complications have a larger negative impact on physical- and role functioning in older patients which indicates a need for better prediction of postoperative complications in the elderly

The impact of postoperative complications on health-related quality of life in older patients with rectal cancer; a prospective cohort study

Objectives: As result of the aging population and increasing rectal cancer incidence, more older patients undergo treatment for rectal cancer. This study compares treatment course, postoperative complications, and quality of life (QOL) between older and younger patients with rectal cancer and evaluates the impact of postoperative complications on QOL in the elderly. Materials and Methods: Patients with rectal cancer participating in a prospective colorectal cancer cohort and referred for radiotherapy between 2013 and 2016 were included. QOL was assessed with the cancer questionnaire of the European Organisation for Research and Treatment of Cancer (EORTC QLQ-C30) before treatment and at three, six, and twelve months. Outcomes were compared between older patients (2.70 years) and younger patients ( Results: In total, 115 (33%) older patients and 230 (67%) younger patients were induded. Compared to younger patients, older patients underwent significantly more often short-course radiation with delayed surgery (6.1% and 19.1% respectively) and less often chemoradiation (62.6% and 39.1% respectively), and were more likely to undergo a Hartmann procedure with permanent stoma (3.5% and 13.0% respectively) instead of sphincter-sparing surgery (43.9% and 29.6% respectively). Postoperative complication rates were similar (38.5% in older patients versus 34.7% in younger patients). Older patients had worse physical functioning at six and twelve months after diagnosis compared to younger patients. Presence of postoperative complications had a significant stronger impact on physical- and role functioning in older patients. Conclusion: Older patients undergo more often a tailored treatment approach for rectal cancer than younger patients. With this tailored approach, similar postoperative complication rates and QOL are achieved. However, postoperative complications have a larger negative impact on physical- and role functioning in older patients which indicates a need for better prediction of postoperative complications in the elderly. (C) 2017 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license

Predictors for extubation failure in COVID-19 patients using a machine learning approach

INTRODUCTION: Determining the optimal timing for extubation can be challenging in the intensive care. In this study, we aim to identify predictors for extubation failure in critically ill patients with COVID-19. METHODS: We used highly granular data from 3464 adult critically ill COVID patients in the multicenter Dutch Data Warehouse, including demographics, clinical observations, medications, fluid balance, laboratory values, vital signs, and data from life support devices. All intubated patients with at least one extubation attempt were eligible for analysis. Transferred patients, patients admitted for less than 24 h, and patients still admitted at the time of data extraction were excluded. Potential predictors were selected by a team of intensive care physicians. The primary and secondary outcomes were extubation without reintubation or death within the next 7 days and within 48 h, respectively. We trained and validated multiple machine learning algorithms using fivefold nested cross-validation. Predictor importance was estimated using Shapley additive explanations, while cutoff values for the relative probability of failed extubation were estimated through partial dependence plots. RESULTS: A total of 883 patients were included in the model derivation. The reintubation rate was 13.4% within 48 h and 18.9% at day 7, with a mortality rate of 0.6% and 1.0% respectively. The grandient-boost model performed best (area under the curve of 0.70) and was used to calculate predictor importance. Ventilatory characteristics and settings were the most important predictors. More specifically, a controlled mode duration longer than 4 days, a last fraction of inspired oxygen higher than 35%, a mean tidal volume per kg ideal body weight above 8 ml/kg in the day before extubation, and a shorter duration in assisted mode (< 2 days) compared to their median values. Additionally, a higher C-reactive protein and leukocyte count, a lower thrombocyte count, a lower Glasgow coma scale and a lower body mass index compared to their medians were associated with extubation failure. CONCLUSION: The most important predictors for extubation failure in critically ill COVID-19 patients include ventilatory settings, inflammatory parameters, neurological status, and body mass index. These predictors should therefore be routinely captured in electronic health records

Risk factors for adverse outcomes during mechanical ventilation of 1152 COVID-19 patients: a multicenter machine learning study with highly granular data from the Dutch Data Warehouse

Background: The identification of risk factors for adverse outcomes and prolonged intensive care unit (ICU) stay in COVID-19 patients is essential for prognostication, determining treatment intensity, and resource allocation. Previous studies have determined risk factors on admission only, and included a limited number of predictors. Therefore, using data from the highly granular and multicenter Dutch Data Warehouse, we developed machine learning models to identify risk factors for ICU mortality, ventilator-free days and ICU-free days during the course of invasive mechanical ventilation (IMV) in COVID-19 patients. Methods: The DDW is a growing electronic health record database of critically ill COVID-19 patients in the Netherlands. All adult ICU patients on IMV were eligible for inclusion. Transfers, patients admitted for less than 24 h, and patients still admitted at time of data extraction were excluded. Predictors were selected based on the literature, and included medication dosage and fluid balance. Multiple algorithms were trained and validated on up to three sets of observations per patient on day 1, 7, and 14 using fivefold nested cross-validation, keeping observations from an individual patient in the same split. Results: A total of 1152 patients were included in the model. XGBoost models performed best for all outcomes and were used to calculate predictor importance. Using Shapley additive explanations (SHAP), age was the most important demographic risk factor for the outcomes upon start of IMV and throughout its course. The relative probability of death across age values is visualized in Partial Dependence Plots (PDPs), with an increase starting at 54 years. Besides age, acidaemia, low P/F-ratios and high driving pressures demonstrated a higher probability of death. The PDP for driving pressure showed a relative probability increase starting at 12 cmH(2)O. Conclusion: Age is the most important demographic risk factor of ICU mortality, ICU-free days and ventilator-free days throughout the course of invasive mechanical ventilation in critically ill COVID-19 patients. pH, P/F ratio, and driving pressure should be monitored closely over the course of mechanical ventilation as risk factors predictive of these outcomes

The Dutch Data Warehouse, a multicenter and full-admission electronic health records database for critically ill COVID-19 patients

Background: The Coronavirus disease 2019 (COVID-19) pandemic has underlined the urgent need for reliable, multicenter, and full-admission intensive care data to advance our understanding of the course of the disease and investigate potential treatment strategies. In this study, we present the Dutch Data Warehouse (DDW), the first multicenter electronic health record (EHR) database with full-admission data from critically ill COVID-19 patients. Methods: A nation-wide data sharing collaboration was launched at the beginning of the pandemic in March 2020. All hospitals in the Netherlands were asked to participate and share pseudonymized EHR data from adult critically ill COVID-19 patients. Data included patient demographics, clinical observations, administered medication, laboratory determinations, and data from vital sign monitors and life support devices. Data sharing agreements were signed with participating hospitals before any data transfers took place. Data were extracted from the local EHRs with prespecified queries and combined into a staging dataset through an extract–transform–load (ETL) pipeline. In the consecutive processing pipeline, data were mapped to a common concept vocabulary and enriched with derived concepts. Data validation was a continuous process throughout the project. All participating hospitals have access to the DDW. Within legal and ethical boundaries, data are available to clinicians and researchers. Results: Out of the 81 intensive care units in the Netherlands, 66 participated in the collaboration, 47 have signed the data sharing agreement, and 35 have shared their data. Data from 25 hospitals have passed through the ETL and processing pipeline. Currently, 3464 patients are included in the DDW, both from wave 1 and wave 2 in the Netherlands. More than 200 million clinical data points are available. Overall ICU mortality was 24.4%. Respiratory and hemodynamic parameters were most frequently measured throughout a patient's stay. For each patient, all administered medication and their daily fluid balance were available. Missing data are reported for each descriptive. Conclusions: In this study, we show that EHR data from critically ill COVID-19 patients may be lawfully collected and can be combined into a data warehouse. These initiatives are indispensable to advance medical data science in the field of intensive care medicine.</p