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Objectives: Telecritical care (TCC) refers to the delivery of critical care using telehealth technologies. Despite increasing utilization, significant practice variation exists and literature regarding efficacy remains sparse. The Telecritical Care Collaborative Network sought to provide expert, consensus-based best practice recommendations for the design and delivery of TCC., Design: We used a modified Delphi methodology. Following literature review, an oversight panel identified core domains and developed declarative statements for review by an expert voting panel. During three voting rounds, voters agreed or disagreed with statements and provided open-ended feedback, which the oversight panel used to revise statements. Statements met criteria for consensus when accepted by greater than or equal to 85% of voters., Setting/subjects: The oversight panel included 18 multidisciplinary members of the TCC Collaborative Network, and the voting panel included 32 invited experts in TCC, emphasizing diversity of discipline, care delivery models, and geography., Interventions: None., Measurements and Main Results: We identified ten core domains: definitions/terminology; care delivery models; staffing and coverage models; technological considerations; ergonomics and workplace safety; licensing, credentialing, and certification; trust and relationship building; quality, safety, and efficiency, research agenda; and advocacy, leading to 79 practice statements. Of 79 original statements, 67 were accepted in round 1. After revision, nine were accepted in round 2 and two in round 3 (two statements were merged). In total, 78 practice statements achieved expert consensus., Conclusions: These expert consensus recommendations cover a broad range of topics relevant to delivery of TCC. Experts agreed that TCC is most effective when delivered by care teams with specific expertise and by programs with explicit protocols focusing on effective communication, technical reliability, and real-time availability. Interventions should be tailored to local conditions. Although further research is needed to guide future best practice statements, these results provide valuable and actionable recommendations for the delivery of high-quality TCC., Competing Interests: Dr. Singh received funding from Intuitive Surgical. Dr. Laudanski’s institution received funding from the National Institutes of Health. Dr. Rincon received funding from Blue Cirrus Consulting, Baxter Healthcare, Phillips Health, and Viven Health. Dr. Villanueva received funding from Intercept Telemed, Banner Health, Pasadena Law Center; he disclosed that he is the Chief Medical Officer of Intercept Telemed, a telecritical care medicine physician for Banner Health; and he owns stock in Omnicure and Fruit Street Health, Public Benefit Corporation, and owns stock in Google, Amazon, Apple, Edwards Lifesciences, Eli Lilly, Johnson and Johnson, Microsoft, Oracle, Palantir, UnitedHealth Group, Berkshire Hathaway, Proctor and Gamble, and Walmart. The remaining authors have disclosed that they do not have any potential conflicts of interest., (Copyright © 2024 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.)

Objectives: To assess the incidence, risk factors, and outcomes of atrial fibrillation (AF) in the ICU and to describe current practice in the management of AF., Design: Multicenter, prospective, inception cohort study., Setting: Forty-four ICUs in 12 countries in four geographical regions., Subjects: Adult, acutely admitted ICU patients without a history of persistent/permanent AF or recent cardiac surgery were enrolled; inception periods were from October 2020 to June 2021., Interventions: None., Measurements and Main Results: We included 1,423 ICU patients and analyzed 1,415 (99.4%), among whom 221 patients had 539 episodes of AF. Most (59%) episodes were diagnosed with continuous electrocardiogram monitoring. The incidence of AF was 15.6% (95% CI, 13.8-17.6), of which newly developed AF was 13.3% (11.5-15.1). A history of arterial hypertension, paroxysmal AF, sepsis, or high disease severity at ICU admission was associated with AF. Used interventions to manage AF were fluid bolus 19% (95% CI 16-23), magnesium 16% (13-20), potassium 15% (12-19), amiodarone 51% (47-55), beta-1 selective blockers 34% (30-38), calcium channel blockers 4% (2-6), digoxin 16% (12-19), and direct current cardioversion in 4% (2-6). Patients with AF had more ischemic, thromboembolic (13.6% vs 7.9%), and severe bleeding events (5.9% vs 2.1%), and higher mortality (41.2% vs 25.2%) than those without AF. The adjusted cause-specific hazard ratio for 90-day mortality by AF was 1.38 (95% CI, 0.95-1.99)., Conclusions: In ICU patients, AF occurred in one of six and was associated with different conditions. AF was associated with worse outcomes while not statistically significantly associated with 90-day mortality in the adjusted analyses. We observed variations in the diagnostic and management strategies for AF., Competing Interests: The Department of Intensive Care, Rigshospitalet, has received funds for other research projects from the Novo Nordisk Foundation, Sygeforsikringen “danmark,” Pfizer, and Fresenius Kabi, and does contract research for AM-Pharma. The Department of Intensive Care, Copenhagen University Hospital—North Zealand, has received funds for other research projects from the Novo Nordisk Foundation, Sygeforsikringen “danmark,” and other foundations and does contract research for AM-Pharma and Inotrem. Dr. Bestle has received consultancy fee from AM-Pharma. Dr. Wetterslev received funding from The Research Council of Rigshospitalet, The Ehrenreich’s Foundation, and The Danish Society of Anesthesiology and Intensive Care Medicine; he received support for article research from The Research Council of Rigshospitalet, Copenhagen, Denmark. Drs. Granholm’s and Bestle’s institutions received funding from Sygeforsikringen. Dr. Granholm’s institution received funding from The Ehrenreich’s Foundation, the Novo Nordisk Foundation, Pfizer, Fresenius Kabi, and AM-Pharma. Drs. Shen, Gao, and Yang disclosed work for hire. Dr. Bestle received funding from AM-Pharma. Dr. Haranath received funding from Medvarsity. The remaining authors have disclosed that they do not have any potential conflicts of interest., (Copyright © 2023 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.)

This multiauthored communication gives a state-of-the-art global perspective on the increasing adoption of tele-critical care. Exponentially increasing sophistication in the deployment of Computers, Information, and Communication Technology has ensured extending the reach of limited intensivists virtually and reaching the unreached. Natural disasters, COVID-19 pandemic, and wars have made tele-intensive care a reality. Concerns and regulatory issues are being sorted out, cross-border cost-effective tele-critical care is steadily increasing Components to set up a tele-intensive care unit, and overcoming barriers is discussed. Importance of developing best practice guidelines and retraining is emphasized., Competing Interests: Disclosure The authors confirm that no competing financial interests exist and there are nil source(s) of support in the form of grants, equipment, etc., (Copyright © 2022 Elsevier Inc. All rights reserved.)

In Coronavirus disease 2019 (COVID-19), early identification of patients with a high risk of mortality can significantly improve triage, bed allocation, timely management, and possibly, outcome. The study objective is to develop and validate individualized mortality risk scores based on the anonymized clinical and laboratory data at admission and determine the probability of Deaths at 7 and 28 days. Data of 1393 admitted patients (Expired-8.54%) was collected from six Apollo Hospital centers (from April to July 2020) using a standardized template and electronic medical records. 63 Clinical and Laboratory parameters were studied based on the patient's initial clinical state at admission and laboratory parameters within the first 24 h. The Machine Learning (ML) modelling was performed using eXtreme Gradient Boosting (XGB) Algorithm. 'Time to event' using Cox Proportional Hazard Model was used and combined with XGB Algorithm. The prospective validation cohort was selected of 977 patients (Expired-8.3%) from six centers from July to October 2020. The Clinical API for the Algorithm is  http://20.44.39.47/covid19v2/page1.php being used prospectively. Out of the 63 clinical and laboratory parameters, Age [adjusted hazard ratio (HR) 2.31; 95% CI 1.52-3.53], Male Gender (HR 1.72, 95% CI 1.06-2.85), Respiratory Distress (HR 1.79, 95% CI 1.32-2.53), Diabetes Mellitus (HR 1.21, 95% CI 0.83-1.77), Chronic Kidney Disease (HR 3.04, 95% CI 1.72-5.38), Coronary Artery Disease (HR 1.56, 95% CI - 0.91 to 2.69), respiratory rate > 24/min (HR 1.54, 95% CI 1.03-2.3), oxygen saturation below 90% (HR 2.84, 95% CI 1.87-4.3), Lymphocyte% in DLC (HR 1.99, 95% CI 1.23-2.32), INR (HR 1.71, 95% CI 1.31-2.13), LDH (HR 4.02, 95% CI 2.66-6.07) and Ferritin (HR 2.48, 95% CI 1.32-4.74) were found to be significant. The performance parameters of the current model is at AUC ROC Score of 0.8685 and Accuracy Score of 96.89. The validation cohort had the AUC of 0.782 and Accuracy of 0.93. The model for Mortality Risk Prediction provides insight into the COVID Clinical and Laboratory Parameters at admission. It is one of the early studies, reflecting on 'time to event' at the admission, accurately predicting patient outcomes.

Background: As ICU consultants in smaller hospitals may not be familiar with neurocritical care and with current travel restrictions due to the COVID-19 pandemic, one needs to relook at how neurocritical care can be provided., Objective: This article reviews the authors' experience of providing remote neurointensive care, from a non-specialist ICU over a 16-month period., Material and Methods: 61 neuro consultations were provided for 56 patients admitted in remote ICU's, including five repeat consultations. Most teleconsultations were from three rural hospitals. The central command center has monitored remote patients with neurological conditions, in 23 ICUs., Results and Conclusions: Providing real-time virtual neuro intensive advice to ICU's in smaller cities even without dedicated neuro-intensive units is feasible in India. eNeuroIntensive care is particularly necessary in the current "New Normal" era., Competing Interests: None

Competing Interests: There are no conflicts of interest.

Objectives: Lipoprotein(a) [LP(a)] has been reported to be an independent risk factor for coronary artery disease (CAD). However, its relationship with other vascular complications is not clear. The aim of the study was to determine the relation of lipoprotein(a) with micro- and macrovascular complications seen in type 2 diabetic patients., Methods: We studied 725 type 2 diabetic patients with and without diabetic complications at the MV Diabetes Specialities Centre, Chennai. The mean age of the study group was 54 +/- 10 years and 70% were males. Diabetic complications viz retinopathy, proteinuria, peripheral vascular disease and coronary artery disease were diagnosed using standardized definitions. Lipoprotein(a) levels were measured using enzyme linked immunosorbant assay (ELISA). Since the frequency distribution of Lp(a) was skewed Lp(a) values were log transformed and geometric mean was used for statistical analysis., Results: The mean Lp(a) level of patients with any vascular complication was significantly higher compared to the subjects without any complications. Multiple logistic regression analysis revealed that lipoprotein(a) had as independent association with CAD (Odds Ratio -1.16, p=0.04) and proteinuria (Odds Ratio -1.69, p < 0.001). The association of Lp(a) with retinopathy and PVD turned out to be non-significant when CAD and proteinuria was introduced as cofactors in the regression model., Conclusion: Lp(a) concentrations are found to be higher in those with CAD and proteinuria. There appears to be no association between Lp(a) and retinopathy or PVD in South Indian type 2 diabetic patients.

Study Objectives: We previously reported eight patients who developed Churg-Strauss syndrome in association with zafirlukast treatment for asthma and postulated that the syndrome resulted from unmasking of a previously existing condition due to corticosteroid withdrawal and not from a direct drug effect. The availability of montelukast, a new leukotriene receptor antagonist with a different molecular structure, permitted us to test this hypothesis. Our goals were to ascertain whether the Churg-Strauss syndrome developed in patients taking montelukast and other novel asthma medications, and to describe potential mechanisms for the syndrome., Design: Case series., Setting: Outpatient and hospital practices of pulmonologists in the United States and Belgium., Patients: Four adults (one man, three women) who received montelukast as treatment for asthma; two women who received salmeterol/fluticasone therapy, but not montelukast., Results: Churg-Strauss syndrome developed in the four asthmatic patients who received montelukast. In each case, there was a long history of difficult-to-control asthma characterized by multiple exacerbations that had required frequent courses of oral systemic corticosteroids or high doses of inhaled corticosteroids for control. Two other asthmatics who received fluticasone and salmeterol but not montelukast therapy developed the same syndrome with tapering doses of oral or high doses of inhaled corticosteroids., Conclusions: The occurrence of Churg-Strauss syndrome in asthmatic patients receiving leukotriene modifiers appears to be related to unmasking of an underlying vasculitic syndrome that is initially clinically recognized as moderate to severe asthma and treated with corticosteroids. Montelukast does not appear to directly cause the syndrome in these patients.

Objective: Asian Indians have been reported to have very high prevalence rates of coronary artery disease (CAD) in the absence of traditional risk factors. Recently, elevated levels of lipoprotein(a) [Lp(a)] have been reported to be associated with premature CAD in migrant Asian Indians. However, there are very little data regarding Lp(a) in CAD patients from the Indian subcontinent and virtually none in individuals with NIDDM. The objective of this study was to assess the role of Lp(a) as a marker for CAD in South Indian NIDDM patients., Research Design and Methods: We estimated serum Lp(a) in 100 control subjects, 100 NIDDM patients without CAD, and 100 NIDDM patients with CAD. Lp(a) values were transformed into natural logarithms. Statistical analysis included Student's t test, one-way analysis of variance, and chi2 test. Multiple logistic regression analysis was used to identify associations with CAD., Results: Lp(a) levels were significantly higher in NIDDM patients with CAD compared with NIDDM patients without CAD and control subjects (geometric mean 24.6, 15.1, and 19.4 mg/dl, respectively, P < 0.05). Results of logistic regression analysis showed that Lp(a), age, and HDL were associated with CAD. In NIDDM patients with CAD, there was no correlation between Lp(a) and serum cholesterol, triglyceride, or HDL cholesterol levels, but there was a weak association with LDL cholesterol and systolic blood pressure., Conclusions: The data suggests that serum Lp(a) is an independent risk factor for CAD in NIDDM patients in South India.