Dharmanand Ramnarain

Background: Delirium is a pathobiological brain process that is frequently observed in Intensive Care Unit (ICU) patients, and is associated with longer hospitalization as well as long-term cognitive impairment. In neurological ICU patients, delirium may be more treatment-resistant due to the initial brain injury. This study examined the effects of a multicomponent non-pharmacological nursing intervention program on delirium in neurological ICU patients. Methods: A single-center interrupted time series trial was conducted in adult neurological ICU patients at high risk for developing delirium who were non-delirious at admission. A multicomponent nursing intervention program focusing on modifiable risk factors for delirium, including the optimalization of vision, hearing, orientation and cognition, sleep and mobilization, was implemented as the standard of care, and its effects were studied. The primary outcome was the number of delirium-free and coma-free days alive at 28 days after ICU admission. The secondary outcomes included delirium incidence and duration, ICU and hospital length-of-stay and duration of mechanical ventilation. Results: Of 289 eligible patients admitted to the ICU, 130 patients were included, with a mean age of 68 ± 11 years, a mean APACHE-IV score of 79 ± 25 and a median predicted delirium risk (E-PRE-DELIRIC) score of 42 [IQR 38–50]). Of these, 73 were included in the intervention period and 57 in the control period. The median delirium- and coma-free days alive were 15 days [IQR 0–26] in the intervention group and 10 days [IQR 0–24] in the control group (level change −0.48 days, 95% confidence interval (95%CI) −7 to 6 days, p = 0.87; slope change −0.95 days, 95%CI −2.41 to 0.52 days, p = 0.18). Conclusions: In neurological ICU patients, our multicomponent non-pharmacological nursing intervention program did not change the number of delirium-free and coma-free days alive after 28 days.

Predatory journals and conferences are an emerging problem in scientific literature as they have financial motives, without guaranteeing scientific quality and exposure. The main objective of the ASGLOS project is to investigate the predatory e‐email characteristics, management, and possible consequences and to analyse the extent of the current problem at each academic level. To collect the personal experiences of physicians’ mailboxes on predatory publishing, a Google Form® survey was designed and disseminated from September 2021 to April 2022. A total of 978 responses were analysed from 58 countries around the world. A total of 64.8% of participants indicated the need for 3 or fewer emails to acquire a criticality view in distinguishing a real invitation from a spam, while 11.5% still have doubt regardless of how many emails they get. The AGLOS Study clearly highlights the problem of academic e‐mail spam by predatory journals and conferences. Our findings signify the importance of providing academic career‐oriented advice and organising training sessions to increase awareness of predatory publishing for those conducting scientific research.

Introduction: Delirium is common among patients admitted to the intensive care unit (ICU) and its impact on the neurocognitive and psychiatric state of survivors is of great interest. These new‐onset or worsening conditions, together with physical alterations, are called post‐intensive care syndrome (PICS). Our aim is to update on the latest screening and follow‐up options for psychological and cognitive sequelae of PICS.Method: This narrative review discusses the occurrence of delirium in ICU settings and the relatively new concept of PICS. Psychiatric and neurocognitive morbidities that may occur in survivors of critical illness following delirium are addressed. Future perspectives for practice and research are discussed.Results: There is no “gold standard” for diagnosing delirium in the ICU, but two extensively validated tools, the confusion assessment method for the ICU and the intensive care delirium screening checklist, are often used. PICS complaints are frequent in ICU survivors who have suffered delirium and have been recognized as an important public health and socio‐economic problem worldwide. Depression, anxiety, post‐traumatic stress disorder, and long‐term cognitive impairment are recurrently exhibited. Screening tools for these deficits are discussed, as well as the suggestion of early assessment after discharge and at 3 and 12 months.Conclusions: Delirium is a complex but common phenomenon in the ICU and a risk factor for PICS. Its diagnosis is challenging with potential long‐term adverse outcomes, including psychiatric and cognitive difficulties. The implementation of screening and follow‐up protocols for PICS sequelae is warranted to ensure early detection and appropriate management.

Background: The SARS-CoV-2 pandemic puts patients and their relatives at risk of developing post-intensive care syndrome (PICS and PICS-family). The use of an intensive care unit (ICU) diary for these patients could help fill in memory gaps and complete their fragmented illness narrative. Objectives: The aim of this study is to evaluate the effect of an ICU diary on the occurrence of impaired mental health in patients admitted with a SARS-CoV-2 infection and their relatives. Methods: An observational cohort study of SARS-CoV-2 patients treated in the ICU of Elizabeth-Tweesteden Hospital (ETZ) in Tilburg, The Netherlands will be conducted. Adult patients admitted at the ICU because of respiratory insufficiency due to SARS-CoV-2, who are mechanically ventilated, are included. During treatment in the ICU a diary is kept of the patient. Anxiety, depression and post-traumatic stress disorder, cognitive dysfunction and quality of life will be screened in patients and their relatives by using the psychosocial screening instrument for adult trauma patients (PSIT), the Cognitive Failure Questionnaire (CFQ) and the short-form health survey 36 (SF-36). The recollection of patients’ memory of the ICU stay will be evaluated by the ICU memory tool. The appreciation of the ICU diary will be assessed using a questionnaire. Results: Participants’ characteristics including how they valued the diary, and their memory of ICU treatment will be reported. Multiple logistic regression analysis will be performed for analyzing the relation between mental health outcome and the use of ICU diaries. Change in PICS symptoms over time will be analyzed using longitudinal data analysis. Missing values in questionnaires will be analyzed using missing value analysis and multiple imputations at item level will be performed if necessary. Conclusions: This study will contribute to the knowledge of mental health outcome in SARS-CoV-2 patients and the use of ICU diaries in this group.

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.

OBJECTIVES: As coronavirus disease 2019 is a novel disease, treatment strategies continue to be debated. This provides the intensive care community with a unique opportunity as the population of coronavirus disease 2019 patients requiring invasive mechanical ventilation is relatively homogeneous compared with other ICU populations. We hypothesize that the novelty of coronavirus disease 2019 and the uncertainty over its similarity with noncoronavirus disease 2019 acute respiratory distress syndrome resulted in substantial practice variation between hospitals during the first and second waves of coronavirus disease 2019 patients. DESIGN: Multicenter retrospective cohort study. SETTING: Twenty-five hospitals in the Netherlands from February 2020 to July 2020, and 14 hospitals from August 2020 to December 2020. PATIENTS: One thousand two hundred ninety-four critically ill intubated adult ICU patients with coronavirus disease 2019 were selected from the Dutch Data Warehouse. Patients intubated for less than 24 hours, transferred patients, and patients still admitted at the time of data extraction were excluded. MEASUREMENTS AND MAIN RESULTS: We aimed to estimate between-ICU practice variation in selected ventilation parameters (positive end-expiratory pressure, Fio₂, set respiratory rate, tidal volume, minute volume, and percentage of time spent in a prone position) on days 1, 2, 3, and 7 of intubation, adjusted for patient characteristics as well as severity of illness based on Pao₂/Fio₂ ratio, pH, ventilatory ratio, and dynamic respiratory system compliance during controlled ventilation. Using multilevel linear mixed-effects modeling, we found significant (p ≤ 0.001) variation between ICUs in all ventilation parameters on days 1, 2, 3, and 7 of intubation for both waves. CONCLUSIONS: This is the first study to clearly demonstrate significant practice variation between ICUs related to mechanical ventilation parameters that are under direct control by intensivists. Their effect on clinical outcomes for both coronavirus disease 2019 and other critically ill mechanically ventilated patients could have widespread implications for the practice of intensive care medicine and should be investigated further by causal inference models and clinical trials.

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.