Caring for Hospitalized Patients with Diabetes Mellitus, Hyperglycemia, and COVID-19: Bridging the Remaining Knowledge Gaps

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Abstract

Purpose of Review

This review discusses the interplay between coronavirus disease 2019 (COVID-19, caused by SARS-CoV-2 infection), diabetes mellitus, and hyperglycemia in the hospital setting. There are data emerging about diabetes and hyperglycemia, their prevalence, and potential risks in the setting of SARS-CoV-2 infection and COVID-19.

Recent Findings

It is known that viral infections exert effects on beta cell function and insulin resistance. Therefore, much can be learned about SARS-CoV-2/COVID-19 from examining these known relationships. Such pathophysiological underpinnings may unlock greater understanding as we navigate atypical cases of hyperglycemia, severe insulin resistance, and diabetic ketoacidosis amidst COVID-19. Glycemic outcomes likely have beneficial effects on morbidity and mortality, but this needs to be studied.

Summary

Changes in diabetes-related protocols and new technology can be deployed in the inpatient setting to potentially improve healthcare worker and patient safety; however, one must weigh the risks and benefits of implementation during a pandemic. Ultimately, knowledge and research must be shared at record speed to combat this global crisis.

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Most cited references 86

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Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

Chaolin Huang, Yeming Wang, Xingwang Li … (2020)

Summary Background A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients. Methods All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by WHO and the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not. Findings By Jan 2, 2020, 41 admitted hospital patients had been identified as having laboratory-confirmed 2019-nCoV infection. Most of the infected patients were men (30 [73%] of 41); less than half had underlying diseases (13 [32%]), including diabetes (eight [20%]), hypertension (six [15%]), and cardiovascular disease (six [15%]). Median age was 49·0 years (IQR 41·0–58·0). 27 (66%) of 41 patients had been exposed to Huanan seafood market. One family cluster was found. Common symptoms at onset of illness were fever (40 [98%] of 41 patients), cough (31 [76%]), and myalgia or fatigue (18 [44%]); less common symptoms were sputum production (11 [28%] of 39), headache (three [8%] of 38), haemoptysis (two [5%] of 39), and diarrhoea (one [3%] of 38). Dyspnoea developed in 22 (55%) of 40 patients (median time from illness onset to dyspnoea 8·0 days [IQR 5·0–13·0]). 26 (63%) of 41 patients had lymphopenia. All 41 patients had pneumonia with abnormal findings on chest CT. Complications included acute respiratory distress syndrome (12 [29%]), RNAaemia (six [15%]), acute cardiac injury (five [12%]) and secondary infection (four [10%]). 13 (32%) patients were admitted to an ICU and six (15%) died. Compared with non-ICU patients, ICU patients had higher plasma levels of IL2, IL7, IL10, GSCF, IP10, MCP1, MIP1A, and TNFα. Interpretation The 2019-nCoV infection caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and was associated with ICU admission and high mortality. Major gaps in our knowledge of the origin, epidemiology, duration of human transmission, and clinical spectrum of disease need fulfilment by future studies. Funding Ministry of Science and Technology, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, and Beijing Municipal Science and Technology Commission.

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SARS-CoV-2 Cell Entry Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor

Markus Hoffmann, Hannah Kleine-Weber, Simon Schroeder … (2020)

Summary The recent emergence of the novel, pathogenic SARS-coronavirus 2 (SARS-CoV-2) in China and its rapid national and international spread pose a global health emergency. Cell entry of coronaviruses depends on binding of the viral spike (S) proteins to cellular receptors and on S protein priming by host cell proteases. Unravelling which cellular factors are used by SARS-CoV-2 for entry might provide insights into viral transmission and reveal therapeutic targets. Here, we demonstrate that SARS-CoV-2 uses the SARS-CoV receptor ACE2 for entry and the serine protease TMPRSS2 for S protein priming. A TMPRSS2 inhibitor approved for clinical use blocked entry and might constitute a treatment option. Finally, we show that the sera from convalescent SARS patients cross-neutralized SARS-2-S-driven entry. Our results reveal important commonalities between SARS-CoV-2 and SARS-CoV infection and identify a potential target for antiviral intervention.

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Correlation of Chest CT and RT-PCR Testing in Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases

Tao Ai, Zhenlu Yang, Hongyan Hou … (2020)

Background Chest CT is used for diagnosis of 2019 novel coronavirus disease (COVID-19), as an important complement to the reverse-transcription polymerase chain reaction (RT-PCR) tests. Purpose To investigate the diagnostic value and consistency of chest CT as compared with comparison to RT-PCR assay in COVID-19. Methods From January 6 to February 6, 2020, 1014 patients in Wuhan, China who underwent both chest CT and RT-PCR tests were included. With RT-PCR as reference standard, the performance of chest CT in diagnosing COVID-19 was assessed. Besides, for patients with multiple RT-PCR assays, the dynamic conversion of RT-PCR results (negative to positive, positive to negative, respectively) was analyzed as compared with serial chest CT scans for those with time-interval of 4 days or more. Results Of 1014 patients, 59% (601/1014) had positive RT-PCR results, and 88% (888/1014) had positive chest CT scans. The sensitivity of chest CT in suggesting COVID-19 was 97% (95%CI, 95-98%, 580/601 patients) based on positive RT-PCR results. In patients with negative RT-PCR results, 75% (308/413) had positive chest CT findings; of 308, 48% were considered as highly likely cases, with 33% as probable cases. By analysis of serial RT-PCR assays and CT scans, the mean interval time between the initial negative to positive RT-PCR results was 5.1 ± 1.5 days; the initial positive to subsequent negative RT-PCR result was 6.9 ± 2.3 days). 60% to 93% of cases had initial positive CT consistent with COVID-19 prior (or parallel) to the initial positive RT-PCR results. 42% (24/57) cases showed improvement in follow-up chest CT scans before the RT-PCR results turning negative. Conclusion Chest CT has a high sensitivity for diagnosis of COVID-19. Chest CT may be considered as a primary tool for the current COVID-19 detection in epidemic areas. A translation of this abstract in Farsi is available in the supplement. - ترجمه چکیده این مقاله به فارسی، در ضمیمه موجود است.

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Author and article information

Contributors

Amisha Wallia: a-wallia@northwestern.edu

Grace Prince: grace.prince@northwestern.edu

Emilie Touma: emilie.touma@northwestern.edu

Malek El Muayed: m-muayed@northwestern.edu

Jane Jeffrie Seley: jas9067@med.cornell.edu

Journal

Journal ID (nlm-ta): Curr Diab Rep

Journal ID (iso-abbrev): Curr Diab Rep

Title: Current Diabetes Reports

Publisher: Springer US (New York )

ISSN (Print): 1534-4827

ISSN (Electronic): 1539-0829

Publication date (Electronic): 26 November 2020

Publication date (Print): 2020

Volume: 20

Issue: 12

Electronic Location Identifier: 77

Affiliations

[1 ]GRID grid.16753.36, ISNI 0000 0001 2299 3507, Division of Endocrinology, Metabolism and Molecular Medicine, , Feinberg School of Medicine, Northwestern University, ; Chicago, IL USA

[2 ]GRID grid.16753.36, ISNI 0000 0001 2299 3507, Institute of Public Health, , Feinberg School of Medicine, Northwestern University, ; Chicago, IL USA

[3 ]GRID grid.5386.8, ISNI 000000041936877X, Division of Endocrinology, Diabetes, and Metabolism, , Weill Cornell Medicine, ; New York, NY USA

Article

Publisher ID: 1366

DOI: 10.1007/s11892-020-01366-0

PMC ID: 7690847

PubMed ID: 33244614

SO-VID: 2a0fed9b-a13e-4a32-acae-a7445669d446

License:

This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

History

Date accepted : 26 October 2020

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ScienceOpen disciplines: Endocrinology & Diabetes

Keywords: diabetes,covid-19,sars-cov2,inpatient management,hyperglycemia

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ScienceOpen disciplines: Endocrinology & Diabetes

Keywords: diabetes, covid-19, sars-cov2, inpatient management, hyperglycemia

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Caring for Hospitalized Patients with Diabetes Mellitus, Hyperglycemia, and COVID-19: Bridging the Remaining Knowledge Gaps

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Abstract

Purpose of Review

Recent Findings

Summary

Related collections

Novel Coronavirus Disease COVID-19

Most cited references 86

Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

SARS-CoV-2 Cell Entry Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor

Correlation of Chest CT and RT-PCR Testing in Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases

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Cited by 10

Most referenced authors 3,181