Clinical profile of hospitalised moderate category COVID-19 patients: Short study from a Tertiary Care Centre in Delhi

Background

The clinical profile of hospitalized moderate-category COVID-19 patients has been understudied globally and in India.

Aim

The present study was conducted to study the clinical profile and assess the proportions of patients who progressed to severe disease and its predictors among moderate COVID-19 patients.

Materials and Methods

In this single-center observational study, 100 moderate-category COVID-19 patients as per Ministry of Health and Family Welfare (MoHFW) criteria of age ≥18 years of either sex, excluding pregnant females from February to November 2021, were studied by analyzing their clinical profiles and assessing Quick Sequential Organ Failure Assessment (qSOFA), National Early Warning Score 2 (NEWS-2), and chest computed-tomography severity score (CTSS) to predict progression to severe disease. Severe disease was defined as per MoHFW criteria.

Results

Out of 100 moderate-category COVID-19 patients, progression to severe disease was seen in 11 patients (11%), among which eight patients had expired, three patients were discharged, and the rest of the 89 patients (89%) who did not progress to severe disease were discharged. A higher age (62.2± 19.5 vs 54.8 ± 14.6 years), along with multivariate analysis revealing male sex (1.25 times), chronic kidney disease (2.86 times), leukocytosis (6.10 times), thrombocytopenia (1.04 times), anemia (9.3 times), a higher qSOFA score (3.6 times), and a higher NEWS-2 score on admission (1.56 times) had higher odds of progression to severe disease. A significant correlation (P < .05) of qSOFA score with serum LDH, ferritin, and hs-CRP levels; CT severity score with the serum ferritin, IL-6, and LDH levels; and NEWS-2 with serum LDH, hs-CRP, and ferritin levels were found. Moreover, the NEWS-2 score was found slightly better than qSOFA on receiver operating characteristic (ROC) curve analysis, with an area under the curve of 85.8% and 83.2%, respectively, predicting progression to severe disease.

Conclusion

Our study revealed male gender, chronic kidney disease, leukocytosis, anemia, thrombocytopenia, a higher qSOFA and NEWS-2 score on admission, and further, NEWS-2 score better than qSOFA on ROC curve analysis, with an area under the curve of 85.8% and 83.2%, respectively, in predicting severe disease among hospitalized moderate COVID-19 patients.

Time for a rethink in cardiogenic shock: the shock to survival framework document

Cardiogenic shock remains a time-critical, complex syndrome that continues to present challenges to clinicians and healthcare systems. Despite advances in the fields of cardiovascular and critical care medicine, mortality remains high. This article summarises the recent shock to survival document, which outlined the current and ideal future state of cardiogenic shock care nationally to improve patient outcomes. Shock to survival emphasises the need for education and training in the early recognition of the hypoperfusion that is pathognomomic of cardiogenic shock. Improved provision of focused cardiac ultrasound is essential to confirm a cardiac cause. Early identification of the patient with cardiogenic shock should be supported by access to defined pathways of care, including specialist shock centres and multiprofessional teams with domain expertise and the capability to manage the myriad of causative aetiologies. Given the absence of high-quality data to inform practice nationally, robust datasets are an unmet need to inform best practice, guide design of clinical services and pathways and drive innovation through research and clinical trials.

Impact of frailty on the performance of the National Early Warning Score 2 to predict poor outcome in patients hospitalised due to COVID-19

BACKGROUND

The National Early Warning Score 2 (NEWS2) is a scoring tool predictive of poor outcome in hospitalised patients. Older patients with COVID-19 have increased risk of poor outcome, but it is not known if frailty may impact the predictive performance of NEWS2. We aimed to investigate the impact of frailty on the performance of NEWS2 to predict in-hospital mortality in patients hospitalised due to COVID-19.

METHODS

We included all patients admitted to a non-university Norwegian hospital due to COVID-19 from 9 March 2020 until 31 December 2021. NEWS2 was scored based on the first vital signs recorded upon hospital admission. Frailty was defined as a Clinical Frailty Scale score ≥ 4. The performance of a NEWS2 score ≥ 5 to predict in-hospital mortality was assessed with sensitivity, specificity and area under the receiver operating characteristic curve (AUROC) according to frailty status.

RESULTS

Out of 412 patients, 70 were aged ≥ 65 years and with frailty. They presented less frequently with respiratory symptoms, and more often with acute functional decline or new-onset confusion. In-hospital mortality was 6% in patients without frailty, and 26% in patients with frailty. NEWS2 predicted in-hospital mortality with a sensitivity of 86%, 95% confidence interval (CI) 64%-97% and AUROC 0.73, 95% CI 0.65-0.81 in patients without frailty. In older patients with frailty, sensitivity was 61%, 95% CI 36%-83% and AUROC 0.61, 95% CI 0.48-0.75.

CONCLUSION

A single NEWS2 score at hospital admission performed poorly to predict in-hospital mortality in patients with frailty and COVID-19 and should be used with caution in this patient group. Graphical abstract summing up study design, results and conclusion.

A conceptual IoT-based early-warning architecture for remote monitoring of COVID-19 patients in wards and at home

Due to the COVID-19 pandemic, health services around the globe are struggling. An effective system for monitoring patients can improve healthcare delivery by avoiding in-person contacts, enabling early-detection of severe cases, and remotely assessing patients' status. Internet of Things (IoT) technologies have been used for monitoring patients' health with wireless wearable sensors in different scenarios and medical conditions, such as noncommunicable and infectious diseases. Combining IoT-related technologies with early-warning scores (EWS) commonly utilized in infirmaries has the potential to enhance health services delivery significantly. Specifically, the NEWS-2 has been showing remarkable results in detecting the health deterioration of COVID-19 patients. Although the literature presents several approaches for remote monitoring, none of these studies proposes a customized, complete, and integrated architecture that uses an effective early-detection mechanism for COVID-19 and that is flexible enough to be used in hospital wards and at home. Therefore, this article's objective is to present a comprehensive IoT-based conceptual architecture that addresses the key requirements of scalability, interoperability, network dynamics, context discovery, reliability, and privacy in the context of remote health monitoring of COVID-19 patients in hospitals and at home. Since remote monitoring of patients at home (essential during a pandemic) can engender trust issues regarding secure and ethical data collection, a consent management module was incorporated into our architecture to provide transparency and ensure data privacy. Further, the article details mechanisms for supporting a configurable and adaptable scoring system embedded in wearable devices to increase usefulness and flexibility for health care professions working with EWS.