Kashyap, Rahul

Objective To provide insights into the nature, risk factors, impact and existing measures for reporting and preventing violence in the healthcare system. The under-reporting of violence against healthcare workers (HCWs) globally highlights the need for increased public awareness and education. Methods The Violence Study of Healthcare Workers and Systems study used a survey questionnaire created using Research Electronic Data Capture (REDCap) forms and distributed from 6 June to 9 August 2022. Logistic regression analysis evaluated violence predictors, including gender, age, years of experience, institution type, respondent profession and night shift frequency. A χ 2 test was performed to determine the association between gender and different violence forms. Results A total of 5405 responses from 79 countries were analysed. India, the USA and Venezuela were the top three contributors. Female respondents comprised 53%. The majority (45%) fell within the 26–35 age group. Medical students (21%), consultants (20%), residents/fellows (15%) and nurses (10%) constituted highest responders. Nearly 55% HCWs reported firsthand violence experience, and 16% reported violence against their colleagues. Perpetrators were identified as patients or family members in over 50% of cases, while supervisor-incited violence accounted for 16%. Around 80% stated that violence incidence either remained constant or increased during the COVID-19 pandemic. Among HCWs who experienced violence, 55% felt less motivated or more dissatisfied with their jobs afterward, and 25% expressed willingness to quit. Univariate analysis revealed that HCWs aged 26–65 years, nurses, physicians, ancillary staff, those working in public settings, with >1 year of experience, and frequent night shift workers were at significantly higher risk of experiencing violence. These results remained significant in multivariate analysis, except for the 55–65 age group, which lost statistical significance. Conclusion This global cross-sectional study highlights that a majority of HCWs have experienced violence, and the incidence either increased or remained the same during the COVID-19 pandemic. This has resulted in decreased job satisfaction.

Background and Objectives: Bartter syndrome (BS) is a rare group of autosomal-recessive disorders that usually presents with hypokalemic metabolic alkalosis, occasionally with hyponatremia and hypochloremia. The clinical presentation of BS is heterogeneous, with a wide variety of genetic variants. The aim of this systematic review was to examine the available literature and provide an overview of the case reports and case series on BS. Materials and Methods: Case reports/series published from April 2012 to April 2022 were searched through Pubmed, JSTOR, Cochrane, ScienceDirect, and DOAJ. Subsequently, the information was extracted in order to characterize the clinical presentation, laboratory results, treatment options, and follow-up of the patients with BS. Results: Overall, 118 patients, 48 case reports, and 9 case series (n = 70) were identified. Out of these, the majority of patients were male (n = 68). A total of 21 patients were born from consanguineous marriages. Most cases were reported from Asia (73.72%) and Europe (15.25%). In total, 100 BS patients displayed the genetic variants, with most of these being reported as Type III (n = 59), followed by Type II (n = 19), Type I (n = 14), Type IV (n = 7), and only 1 as Type V. The most common symptoms included polyuria, polydipsia, vomiting, and dehydration. Some of the commonly used treatments were indomethacin, potassium chloride supplements, and spironolactone. The length of the follow-up time varied from 1 month to 14 years. Conclusions: Our systematic review was able to summarize the clinical characteristics, presentation, and treatment plans of BS patients. The findings from this review can be effectively applied in the diagnosis and patient management of individuals with BS, rendering it a valuable resource for nephrologists in their routine clinical practice.

Abstract Background Structural valve dysfunction in bioprosthetic heart valves necessitates redo replacement procedure that are associated with high mortality and morbidity. The transcatheter valve-in-valve (VIV) approach has emerged as a preferred option for patients requiring redo procedures due to structural valve degeneration. We report from India the first case of the simultaneous transcatheter dual VIV implantation (mitral valve and tricuspid valves) in a high-surgical-risk patient. Case summary A 57-year-old female was presented with a history of rheumatic heart disease, post-mitral valve as well as tricuspid valve replacement (perimount 33 mm) 11 years back. Bioprosthetic heart valve was chosen probably due to limited life expectancy and compliance issues with monitoring of international normalised ratio (INR). She now presented with progressive dyspnoea, oedema, and palpitations (New York Heart Association Class III) for the last 6 months. The patient was scheduled for transcatheter dual valve replacement simultaneously. The procedure was successful with a favourable outcome, short hospital stays, and early recovery. Discussion This is the first case of simultaneous transcatheter dual valve replacement reported from India, which is fluoroscopically guided and supported by TEE. It is a valuable and considerable option for patients with failing bioprosthesis valves who are at increased peri-operative risk.

Background and Objective: The association of non-alcoholic fatty liver disease (NAFLD) and metabolic-associated fatty liver disease (MAFLD) with intensive care unit (ICU) admissions and the need for mechanical ventilation and disease severity in COVID-19 patients. Material and Methods: A systematic literature review was conducted on the databases: Cochrane, Embase, PubMed, ScienceDirect, and the Web of Science from January 2019 to June 2022. Studies evaluating MAFLD using laboratory methods, non-invasive imaging, or liver biopsy were included. The study protocol was registered in PROSPERO (ID CRD42022313259), and PRISMA guidelines were followed. The NIH quality assessment tool was used for quality assessment. RevMan version 5.3 software was used for pooled analysis. A sensitivity analysis was performed to assess the result’s stability. Results: A total of 37,974 patients from 17 studies were assessed for the association between MAFLD and ICU admission. A total of 3396 COVID-19 patients required ICU admission: 1236 (20.41%) in the MAFLD group and 2160 (6.77%) in the non-MAFLD group. The odds ratio was 1.86 for ICU admission, p = 0.007, and a (95% CI) of [1.18–2.91]. A total of 37,166 patients from 13 studies were included in the need for invasive mechanical ventilation analysis. A total of 1676 patients required mechanical ventilation: 805 in the MAFLD group (14.20% of all MAFLD patients) and 871 patients in the non-MAFLD group (2.76% of all non-MAFLD patients). The odds ratio was 2.05, p = 0.02, and a (95% CI) of [1.12–3.74]. A total of 5286 patients from 14 studies were included in the COVID-19 disease severity analysis. Severe COVID-19 was seen in 1623 patients, with 33.17% (901/2716) of MAFLD patients and 28.09% (722/2570) of non-MAFLD patients having severe disease. The odds ratio was 1.59 for disease severity, p = 0.010, and a (95% CI) of [1.12–2.26]. Conclusions: Our meta-analysis suggests that there are significantly increased odds of ICU admissions, a need for invasive mechanical ventilation, and disease severity in MAFLD patients who acquire COVID-19.

IMPORTANCE: Initial Society of Critical Care Medicine Discovery Viral Infection and Respiratory illness Universal Study (VIRUS) Registry analysis suggested that improvements in critical care processes offered the greatest modifiable opportunity to improve critically ill COVID-19 patient outcomes. OBJECTIVES: The Structured Team-based Optimal Patient-Centered Care for Virus COVID-19 ICU Collaborative was created to identify and speed implementation of best evidence based COVID-19 practices. DESIGN, SETTING, AND PARTICIPANTS: This 6-month project included volunteer interprofessional teams from VIRUS Registry sites, who received online training on the Checklist for Early Recognition and Treatment of Acute Illness and iNjury approach, a structured and systematic method for delivering evidence based critical care. Collaborators participated in weekly 1-hour videoconference sessions on high impact topics, monthly quality improvement (QI) coaching sessions, and received extensive additional resources for asynchronous learning. MAIN OUTCOMES AND MEASURES: Outcomes included learner engagement, satisfaction, and number of QI projects initiated by participating teams. RESULTS: Eleven of 13 initial sites participated in the Collaborative from March 2, 2021, to September 29, 2021. A total of 67 learners participated in the Collaborative, including 23 nurses, 22 physicians, 10 pharmacists, nine respiratory therapists, and three nonclinicians. Site attendance among the 11 sites in the 25 videoconference sessions ranged between 82% and 100%, with three sites providing at least one team member for 100% of sessions. The majority reported that topics matched their scope of practice (69%) and would highly recommend the program to colleagues (77%). A total of nine QI projects were initiated across three clinical domains and focused on improving adherence to established critical care practice bundles, reducing nosocomial complications, and strengthening patient- and family-centered care in the ICU. Major factors impacting successful Collaborative engagement included an engaged interprofessional team; an established culture of engagement; opportunities to benchmark performance and accelerate institutional innovation, networking, and acclaim; and ready access to data that could be leveraged for QI purposes. CONCLUSIONS AND RELEVANCE: Use of a virtual platform to establish a learning collaborative to accelerate the identification, dissemination, and implementation of critical care best practices for COVID-19 is feasible. Our experience offers important lessons for future collaborative efforts focused on improving ICU processes of care.

Background Although corticosteroids have become the standard of care for patients with coronavirus disease-2019 (COVID-19) on supplemental oxygen, there is growing evidence of differential treatment response. This study aimed to evaluate if there was an association between biomarker-concordant corticosteroid treatment and COVID-19 outcomes. Methods This registry-based cohort study included adult COVID-19 hospitalized patients between January 2020 and December 2021 from 109 institutions. Patients with available C-reactive protein (CRP) levels within 48 h of admission were evaluated. Those on steroids before admission, stayed in the hospital for <48 h, or were not on oxygen support were excluded. Corticosteroid treatment was biomarker-concordant if given with high baseline CRP ≥150 mg/L or withheld with low CRP (<150 mg/L) and vice-versa was considered discordant (low CRP with steroids, high CRP without steroids). Hospital mortality was the primary outcome. Sensitivity analyses were conducted using varying CRP level thresholds. The model interaction was tested to determine steroid effectiveness with increasing CRP levels. Results Corticosteroid treatment was biomarker-concordant in 1778 (49%) patients and discordant in 1835 (51%). The concordant group consisted of higher-risk patients than the discordant group. After adjusting for covariates, the odds of in-hospital mortality were significantly lower in the concordant group than the discordant (odds ratio [95% confidence interval (C.I.)] = 0.71 [0.51, 0.98]). Similarly, adjusted mortality difference was significant at the CRP thresholds of 100 and 200 mg/L (odds ratio [95% C.I.] = 0.70 [0.52, 0.95] and 0.57 [0.38, 0.85], respectively), and concordant steroid use was associated with lower need for invasive ventilation for 200 mg/L threshold (odds ratio [95% C.I.] = 0.52 [0.30, 0.91]). In contrast, no outcome benefit was observed at CRP threshold of 50. When the model interaction was tested, steroids were more effective at reducing mortality as CRP levels increased. Conclusion Biomarker-concordant corticosteroid treatment was associated with lower odds of in-hospital mortality in severe COVID-19.

Objectives To describe incidence and risk factors of loss of previous independent living through nonhome discharge or discharge home with health assistance in survivors of intensive care unit (ICU) admission for coronavirus disease 2019 (COVID-19). Design Multicenter observational study including patients admitted to the ICU from January 2020 till June 30, 2021. Hypothesis We hypothesized that there is a high risk of nonhome discharge in patients surviving ICU admission due to COVID-19. Setting Data were included from 306 hospitals in 28 countries participating in the SCCM Discovery Viral Infection and Respiratory Illness Universal Study COVID-19 registry. Patients Previously independently living adult ICU survivors of COVID-19. Interventions None. Measurements and Main Results The primary outcome was nonhome discharge. Secondary outcome was the requirement of health assistance among patients who were discharged home. Out of 10 820 patients, 7101 (66%) were discharged alive; 3791 (53%) of these survivors lost their previous independent living status, out of those 2071 (29%) through nonhome discharge, and 1720 (24%) through discharge home requiring health assistance. In adjusted analyses, loss of independence on discharge among survivors was predicted by patient age ≥ 65 years (adjusted odds ratio [aOR] 2.78, 95% confidence interval [CI] 2.47-3.14, P < .0001), former and current smoking status (aOR 1.25, 95% CI 1.08-1.46, P = .003 and 1.60 (95% CI 1.18-2.16), P = .003, respectively), substance use disorder (aOR 1.52, 95% CI 1.12-2.06, P = .007), requirement for mechanical ventilation (aOR 4.17, 95% CI 3.69-4.71, P < .0001), prone positioning (aOR 1.19, 95% CI 1.03-1.38, P = .02), and requirement for extracorporeal membrane oxygenation (aOR 2.28, 95% CI 1.55-3.34, P < .0001). Conclusions More than half of ICU survivors hospitalized for COVID-19 are unable to return to independent living status, thereby imposing a significant secondary strain on health care systems worldwide.

Background Machine learning (ML) is pervasive in all fields of research, from automating tasks to complex decision‐making. However, applications in different specialities are variable and generally limited. Like other conditions, the number of studies employing ML in hypertension research is growing rapidly. In this study, we aimed to survey hypertension research using ML, evaluate the reporting quality, and identify barriers to ML's potential to transform hypertension care. Methods and Results The Harmonious Understanding of Machine Learning Analytics Network survey questionnaire was applied to 63 hypertension‐related ML research articles published between January 2019 and September 2021. The most common research topics were blood pressure prediction (38%), hypertension (22%), cardiovascular outcomes (6%), blood pressure variability (5%), treatment response (5%), and real‐time blood pressure estimation (5%). The reporting quality of the articles was variable. Only 46% of articles described the study population or derivation cohort. Most articles (81%) reported at least 1 performance measure, but only 40% presented any measures of calibration. Compliance with ethics, patient privacy, and data security regulations were mentioned in 30 (48%) of the articles. Only 14% used geographically or temporally distinct validation data sets. Algorithmic bias was not addressed in any of the articles, with only 6 of them acknowledging risk of bias. Conclusions Recent ML research on hypertension is limited to exploratory research and has significant shortcomings in reporting quality, model validation, and algorithmic bias. Our analysis identifies areas for improvement that will help pave the way for the realization of the potential of ML in hypertension and facilitate its adoption.

COVID-19 highlighted the need for use of real-world data (RWD) in critical care as a near real-time resource for clinical, research, and policy efforts. Analysis of RWD is gaining momentum and can generate important evidence for policy makers and regulators. Extracting high quality RWD from electronic health records (EHRs) requires sophisticated infrastructure and dedicated resources. We sought to customize freely available public tools, supporting all phases of data harmonization, from data quality assessments to de-identification procedures, and generation of robust, data science ready RWD from EHRs. These data are made available to clinicians and researchers through CURE ID, a free platform which facilitates access to case reports of challenging clinical cases and repurposed treatments hosted by the National Center for Advancing Translational Sciences/National Institutes of Health in partnership with the Food and Drug Administration. This commentary describes the partnership, rationale, process, use case, impact in critical care, and future directions for this collaborative effort.