Mortality of Diabetes-related Acute Metabolic Emergencies in COVID-19 patients: a systematic review and meta-analysis

Papadopoulos, Vassilios; Avramidou, Peny; Bakola, Stefania-Aspasia; Zikoudi, Dimitra-Georgia; Touzlatzi, Ntilara; Koutroulos, Marios-Vasileios; Filippou, Dimitrios

doi:10.1101/2021.01.12.21249697

Cited by 2 publications

(1 citation statement)

References 25 publications

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“…This has been confirmed in previous studies that immunosenescence and inflamm-aging may be an explanation (25,26). For the comorbidities, patients with chronic diseases, such as diabetes were more likely to show symptoms of Group 4, which has been confirmed (27). In addition, the results showed that for the imported cases and the clustered cases, the odds of symptoms of Group 2, Group 3, and Group 4 were all lower than indigenous cases or non-clustered cases, respectively.…”

Section: Discussionsupporting

confidence: 82%

Symptom Clustering Patterns and Population Characteristics of COVID-19 Based on Text Clustering Method

Cheng

Wan

et al. 2022

Front. Public Health

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BackgroundDescriptions of single clinical symptoms of coronavirus disease 2019 (COVID-19) have been widely reported. However, evidence of symptoms associations was still limited. We sought to explore the potential symptom clustering patterns and high-frequency symptom combinations of COVID-19 to enhance the understanding of people of this disease.MethodsIn this retrospective cohort study, a total of 1,067 COVID-19 cases were enrolled. Symptom clustering patterns were first explored by a text clustering method. Then, a multinomial logistic regression was applied to reveal the population characteristics of different symptom groups. In addition, time intervals between symptoms onset and the first visit were analyzed to consider the effect of time interval extension on the progression of symptoms.ResultsBased on text clustering, the symptoms were summarized into four groups. Group 1: no-obvious symptoms; Group 2: mainly fever and/or dry cough; Group 3: mainly upper respiratory tract infection symptoms; Group 4: mainly cardiopulmonary, systemic, and/or gastrointestinal symptoms. Apart from Group 1 with no obvious symptoms, the most frequent symptom combinations were fever only (64 cases, 47.8%), followed by dry cough only (42 cases, 31.3%) in Group 2; expectoration only (21 cases, 19.8%), followed by expectoration complicated with fever (10 cases, 9.4%) in Group 3; fatigue complicated with fever (12 cases, 4.2%), followed by headache complicated with fever was also high (11 cases, 3.8%) in Group 4. People aged 45–64 years were more likely to have symptoms of Group 4 than those aged 65 years or older (odds ratio [OR] = 2.66, 95% CI: 1.21–5.85) and at the same time had longer time intervals.ConclusionsSymptoms of COVID-19 could be divided into four clustering groups with different symptom combinations. The Group 4 symptoms (i.e., mainly cardiopulmonary, systemic, and/or gastrointestinal symptoms) happened more frequently in COVID-19 than in influenza. This distinction could help deepen the understanding of this disease. The middle-aged people have a longer time interval for medical visit and was a group that deserve more attention, from the perspective of medical delays.

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Section: Discussionsupporting

confidence: 82%

Symptom Clustering Patterns and Population Characteristics of COVID-19 Based on Text Clustering Method

Cheng

Wan

et al. 2022

Front. Public Health

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Kidney health in the COVID-19 pandemic: An umbrella review of meta-analyses and systematic reviews

Yang

Wei

et al. 2022

Front. Public Health

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BackgroundThis umbrella review aims to consolidate evidence from systematic reviews and meta-analyses investigating the impact of the coronavirus disease−2019 (COVID-19) on kidney health, and the associations between kidney diseases and clinical outcomes in COVID-19 patients.MethodsFive databases, namely, EMBASE, PubMed, Web of Science, the Cochrane Database of Systematic Reviews and Ovid Medline, were searched for meta-analyses and systematic reviews from January 1, 2020 to June 2, 2022. Two reviewers independently selected reviews, identified reviews for inclusion and extracted data. Disagreements were resolved by group discussions. Two reviewers independently assessed the methodological quality of all included reviews using ROBIS tool. A narrative synthesis was conducted. The characteristics and major findings of the included reviews are presented using tables and forest plots. The included meta-analyses were updated when necessary. The review protocol was prospectively registered in PROSPERO (CRD42021266300).ResultsA total of 103 reviews were identified. Using ROBIS, 30 reviews were rated as low risk of bias. Data from these 30 reviews were included in the narrative synthesis. Ten meta-analyses were updated by incorporating 119 newly available cohort studies. Hospitalized COVID-19 patients had a notable acute kidney injury (AKI) incidence of 27.17%. AKI was significantly associated with mortality (pooled OR: 5.24) and severe conditions in COVID-19 patients (OR: 14.94). The pooled prevalence of CKD in COVID-19 patients was 5.7%. Pre-existing CKD was associated with a higher risk of death (pooled OR: 2.21) and disease severity (pooled OR: 1.87). Kidney transplant recipients were susceptible to SARS-CoV-2 infection (incidence: 23 per 10,000 person-weeks) with a pooled mortality of 18%.ConclusionKidney disease such as CKD or recipients of kidney transplants were at increased risk of contracting COVID-19. Persons with COVID-19 also had a notable AKI incidence. AKI, the need for RRT, pre-existing CKD and a history of kidney transplantation are associated with adverse outcomes in COVID-19.Systematic review registrationwww.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021266300, identifier: CRD42021266300.

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Mortality of Diabetes-related Acute Metabolic Emergencies in COVID-19 patients: a systematic review and meta-analysis

Cited by 2 publications

References 25 publications

Symptom Clustering Patterns and Population Characteristics of COVID-19 Based on Text Clustering Method

Symptom Clustering Patterns and Population Characteristics of COVID-19 Based on Text Clustering Method

Kidney health in the COVID-19 pandemic: An umbrella review of meta-analyses and systematic reviews

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