Type 2 Diabetes and COVID-19-Related Mortality in the Critical Care Setting: A National Cohort Study in England, March-July 2020

Asthma and Coronavirus Disease 2019 Risk: a systematic review and meta-analysis

Background

Individual case series and cohort studies have reported conflicting results in people with asthma on the vulnerability to and risk of mortality from coronavirus disease 2019 (COVID-19).

Research question

Are people with asthma at a higher risk of being infected or hospitalised or poorer clinical outcomes from COVID-19?

Methods

A systematic review and meta-analysis based on five main databases including the World Health Organization COVID-19 database between 1 December 2019 and 11 July 2021 on studies with a control (non-asthma) group was conducted. Prevalence and risk ratios were pooled using Sidik–Jonkman random-effects meta-analyses.

Findings

51 studies with an 8.08% (95% CI 6.87–9.30%) pooled prevalence of people with asthma among COVID-19 positive cases. The risk ratios were 0.83 (95% CI 0.73–0.95, p=0.01) for acquiring COVID-19; 1.18 (95% CI 0.98–1.42, p=0.08) for hospitalisation; 1.21 (95% CI 0.97–1.51, p=0.09) for intensive care unit (ICU) admission; 1.06 (95% CI 0.82–1.36, p=0.65) for ventilator use; and 0.94 (95% CI 0.76–1.17, p=0.58) for mortality for people with asthma. Subgroup analyses by continent revealed a significant difference in risk of acquiring COVID-19, ICU admission, ventilator use and death between the continents.

Interpretation

The risk of being infected with severe acute respiratory syndrome coronavirus 2 was reduced compared to the non-asthma group. No statistically significant differences in hospitalisation, ICU admission and ventilator use were found between groups. Subgroup analyses showed significant differences in outcomes from COVID-19 between America, Europe and Asia. Additional studies are required to confirm this risk profile, particularly in Africa and South America, where few studies originate.

The risk of being infected with SARS-CoV-2 was reduced in patients with asthma compared to the non-asthma group. No significant differences in hospitalisation, ICU admission, ventilator use and mortality were found between groups.https://bit.ly/3izKB9h

COVID-19 and Diabetes

The prevalence of diabetes in people with coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has varied worldwide. Most of the available evidence suggests a significant increase in severity and mortality of COVID-19 in people with either type 1 (T1DM) or type 2 diabetes mellitus (T2DM), especially in association with poor glycemic control. While new-onset hyperglycemia and new-onset diabetes (both T1DM and T2DM) have been increasingly recognized in the context of COVID-19 and have been associated with worse outcome, no conclusive evidence yet suggests direct tropism of SARS-CoV-2 on the β cells of pancreatic islets. While all approved oral antidiabetic agents appear to be safe in people with T2DM having COVID-19, no conclusive data are yet available to indicate a mortality benefit with any class of these drugs, in the absence of large randomized controlled trials. Expected final online publication date for the Annual Review of Medicine, Volume 73 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Evaluation of Factors Related to the Survival of Hospitalized Patients With COVID-19: Survival Analysis With Frailty Approach

OBJECTIVE

Considering that coronavirus disease 2019 (COVID-19) is an emerging disease and results in very different outcomes, from complete recovery to death, it is important to determine the factors affecting the survival of patients. Given the lack of knowledge about effective factors and the existence of differences in the outcome of individuals with similar values of the observed covariates, this study aimed to investigate the factors affecting the survival of patients with COVID-19 by the parametric survival model with the frailty approach.

METHODS

The data of 139 patients with COVID-19 hospitalized in Imam Reza Hospital in Tabriz were analyzed by the Gompertz survival model with gamma frailty effect. At first, variables with P < 0.1 in univariable analysis were included in the multivariable analysis, and then the stepwise method was used for variable selection.

RESULTS

Diabetes mellitus was significantly related to the survival of hospitalized patients (P = 0.021). The rest of the investigated variables were not significant. The frailty effect was significant (P = 0.019).

CONCLUSIONS

In the investigated sample of patients with COVID-19, diabetes was an important variable related to patient survival. Also, the significant frailty effect indicates the existence of unobserved heterogeneity that causes individuals with a similar value of the observed covariates to have different survival distributions.

Is diabetes mellitus a wrongdoer to COVID-19 severity?

The coronavirus disease 19 (COVID-19) has turned out to be a pandemic in short period of time due to the high transmissibility of its causative agent, severe acute respiratory syndrome coronavirus 2. Various reports have suggested the promising link between overexpression of angiotensin converting enzyme 2 (ACE2) and COVID-19 pathogenesis. The severity of COVID-19 pathophysiology is greatly depended on several comorbidities, like hypertension, diabetes mellitus (DM), respiratory and cardiovascular disease, out of which DM has emerged as a major risk factor. The current review focuses on the link among the expression of ACE2, use of ACE inhibitors (ACEIs) and angiotensin II type 1 receptor blockers (ARBs), and risk of COVID-19 pathogenesis in DM. The review also emphasizes on synergistic detrimental effect of DM and COVID-19 on the immune system in provoking uncontrolled cytokine storm which eventually leads to lethal consequences. Finally, several possible therapeutic strategies have been highlighted to reduce the excess of risk associated with COVID-19 in people with DM.

Diabetes and COVID-19: The past, the present, and the future

Diabetes, one of the most prevalent chronic diseases in the world, is strongly associated with a poor prognosis in COVID-19. Scrupulous blood sugar management is crucial, since the worse outcomes are closely associated with higher blood sugar levels in COVID-19 infection. Although recent observational studies showed that insulin was associated with mortality, it should not deter insulin use in hospitalized patients requiring tight glucose control. Back and forth dilemma in the past with regards to continue/discontinue certain medications used in diabetes have been mostly resolved. The initial fears of consequences related to continuing certain medications have been largely dispelled. COVID-19 also necessitates the transformation in diabetes care through the integration of technologies. Recent advances in health-related technologies, notably telemedicine and remote continuous glucose monitoring, have become essential in the management of diabetes during the pandemic. Today, these technologies have changed the landscape of medicine and become more important than ever. Being a high-risk population, patients with type 1 or type 2 diabetes, should be prioritized for vaccination. In the future, as the pandemic fades, the prevalence of non-communicable diseases is expected to rise due to lifestyle changes and medical issues/dilemma encountered during the pandemic.

A national retrospective study of the association between serious operational problems and COVID-19 specific intensive care mortality risk

OBJECTIVES

To describe the relationship between reported serious operational problems (SOPs), and mortality for patients with COVID-19 admitted to intensive care units (ICUs).

DESIGN

English national retrospective cohort study.

SETTING

89 English hospital trusts (i.e. small groups of hospitals functioning as single operational units).

PATIENTS

All adults with COVID-19 admitted to ICU between 2nd April and 1st December, 2020 (n = 6,737).

INTERVENTIONS

N/A.

MAIN OUTCOMES AND MEASURES

Hospital trusts routinely submit declarations of whether they have experienced 'serious operational problems' in the last 24 hours (e.g. due to staffing issues, adverse weather conditions, etc.). Bayesian hierarchical models were used to estimate the association between in-hospital mortality (binary outcome) and: 1) an indicator for whether a SOP occurred on the date of a patient's admission, and; 2) the proportion of the days in a patient's stay that had a SOP occur within their trust. These models were adjusted for individual demographic characteristics (age, sex, ethnicity), and recorded comorbidities.

RESULTS

Serious operational problems (SOPs) were common; reported in 47 trusts (52.8%) and were present for 2,701 (of 21,716; 12.4%) trust days. Overall mortality was 37.7% (2,539 deaths). Admission during a period of SOPs was associated with a substantially increased mortality; adjusted odds ratio (OR) 1.34 (95% posterior credible interval (PCI): 1.07 to 1.68). Mortality was also associated with the proportion of a patient's admission duration that had concurrent SOPs; OR 1.47 (95% PCI: 1.10 to 1.96) for mortality where SOPs were present for 100% compared to 0% of the stay.

CONCLUSION AND RELEVANCE

Serious operational problems at the trust-level are associated with a significant increase in mortality in patients with COVID-19 admitted to critical care. The link isn't necessarily causal, but this observation justifies further research to determine if a binary indicator might be a valid prognostic marker for deteriorating quality of care.

Online Interactive Platform for COVID-19 Literature Visual Analytics: Platform Development Study

BACKGROUND

Papers on COVID-19 are being published at a high rate and concern many different topics. Innovative tools are needed to aid researchers to find patterns in this vast amount of literature to identify subsets of interest in an automated fashion.

OBJECTIVE

We present a new online software resource with a friendly user interface that allows users to query and interact with visual representations of relationships between publications.

METHODS

We publicly released an application called PLATIPUS (Publication Literature Analysis and Text Interaction Platform for User Studies) that allows researchers to interact with literature supplied by COVIDScholar via a visual analytics platform. This tool contains standard filtering capabilities based on authors, journals, high-level categories, and various research-specific details via natural language processing and dozens of customizable visualizations that dynamically update from a researcher's query.

RESULTS

PLATIPUS is available online and currently links to over 100,000 publications and is still growing. This application has the potential to transform how COVID-19 researchers use public literature to enable their research.

CONCLUSIONS

The PLATIPUS application provides the end user with a variety of ways to search, filter, and visualize over 100,00 COVID-19 publications.

Outcomes and risk factors for death in patients with coronavirus disease-2019 (COVID-19) pneumonia admitted to the intensive care units of an Egyptian University Hospital. A retrospective cohort study

Background

The characteristics, outcomes, and risk factors for in-hospital death of critically ill intensive care unit (ICU) patients with coronavirus disease-2019 (COVID-19) have been described in patients from Europe, North America and China, but there are few data from COVID-19 patients in Middle Eastern countries. The aim of this study was to investigate the characteristics, outcomes, and risk factors for in-hospital death of critically ill patients with COVID-19 pneumonia admitted to the ICUs of a University Hospital in Egypt.

Methods

Retrospective analysis of patients with COVID-19 pneumonia admitted between April 28 and July 29, 2020 to two ICUs dedicated to the isolation and treatment of patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in Cairo University Hospitals. Diagnosis was confirmed in all patients using real-time reverse transcription polymerase chain reaction on respiratory samples and radiologic evidence of pneumonia.

Results

Of the 177 patients admitted to the ICUs during the study period, 160 patients had COVID-19 pneumonia and were included in the analysis (mean age: 60 ± 14 years, 67.5% males); 23% of patients had no known comorbidities. The overall ICU and hospital mortality rates were both 24.4%. The ICU and hospital lengths of stay were 7 (25–75% interquartile range: 4–10) and 10 (25–75% interquartile range: 7–14) days, respectively. In a multivariable analysis with in-hospital death as the dependent variable, ischemic heart disease, history of smoking, and secondary bacterial pneumonia were independently associated with a higher risk of in-hospital death, whereas greater PaO₂/FiO₂ ratio on admission to the ICU was associated with a lower risk.

Conclusion

In this cohort of critically ill patients with COVID-19 pneumonia, ischemic heart disease, history of smoking, and secondary bacterial pneumonia were independently associated with a higher risk of in-hospital death.

Changes in COVID-19 in-hospital mortality in hospitalised adults in England over the first seven months of the pandemic: An observational study using administrative data

Background

Previous research by our team identified factors associated with in-hospital mortality in patients with a diagnosis of COVID-19 in England between March and May 2020. The aim of the current paper was to investigate the changing role of demographics and co-morbidity, with a particular focus on ethnicity, as risk factors for in-hospital mortality over an extended period.

Methods

This was a retrospective observational study using the Hospital Episode Statistics administrative dataset. All patients aged ≥ 18 years in England with a diagnosis of COVID-19 who had a hospital stay that was completed (discharged alive or died) between 1st March and 30th September 2020 were included. In-hospital mortality was the primary outcome of interest. Multilevel logistic regression was used to model the relationship between in-hospital mortality with adjustment for the covariates: age, sex, deprivation, ethnicity, date of discharge and a number of comorbidities.

Findings

Compared to patients in March-May (n = 93,379), patients in June-September (n = 24,059) were younger, more likely to be female and of Asian ethnicity, but less likely to be of Black ethnicity. In-hospital mortality rates, adjusted for covariates, declined from 33–34% in March to 11–12% in September. Compared to the March-May period, Bangladeshi, Indian and Other Asian ethnicity patients had a lower relative odds of death (compared to White ethnicity patients) during June-September. For Pakistani patients, the decline in-hospital mortality rates was more modest across the same time periods with the relative odds of death increasing slightly (odds ratio (95% confidence interval)) 1.24 (1.10 to 1.40) and 1.35 (1.08 to 1.69) respectively. From March-May to June-September the relative odds of death in patients with a diagnosis of metastatic carcinoma increased (1.90 (1.73 to 2.08) vs 3.01 (2.55 to 3.54)) but decreased for male patients (1.44 (1.39 to 1.49) vs 1.27 (1.17 to 1.38)) and patients with obesity (1.42 (1.34 to 1.52) vs 0.97 (0.83 to 1.14)) and diabetes without complications (1.14 (1.10 to 1.19) vs 0.95 (0.87 to 1.05)).

Interpretation

In-hospital mortality rates for patients with a diagnosis of COVID-19 have fallen substantially and there is evidence that the relative importance of some covariates has changed since the start of the pandemic. These patterns should continue to be tracked as new variants of the virus emerge, vaccination programmes are rolled out and hospital pressures fluctuate.

Funding

None.

The effect of age on the association between diabetes and mortality in adult patients with COVID-19 in Mexico

Diabetes is associated with severe COVID-19 and mortality. The aim of the present study was to determine the effect of age on the association between diabetes and mortality in patients with laboratory-confirmed COVID-19 in Mexico. This retrospective cohort study involved patients aged 20 years or older with symptoms of viral respiratory disease who were screened for SARS-CoV-2 infection across the System of Epidemiological Surveillance of Viral Respiratory Disease in Mexico from January 1 through November 4, 2020. Cox proportional-hazard regression was used to calculate the hazard ratio for 28-day mortality and its 95% confidence interval (CI). Among 757,210 patients with COVID-19 (outpatients and inpatients), 120,476 (16%) had diabetes and 80,616 died. Among 878,840 patients without COVID-19 (those who tested negative for SARS-CoV-2 infection), 88,235 (10.0%) had diabetes and 20,134 died. Among patients with COVID-19, diabetes was associated with a hazard ratio for death of 1.49 (95% CI 1.47-1.52), adjusting for age, sex, smoking habit, obesity, hypertension, immunodeficiency, and cardiovascular, pulmonary, and chronic renal disease. The strength of the association decreased with age (trend test: P = 0.004). For example, the adjusted hazard ratio for death was 3.12 (95% CI 2.86-3.40) for patients 20-39 years of age; in contrast, the adjusted hazard ratio of death for patients 80 years of age or older was 1.11 (95% CI 1.06-1.16). The adjusted hazard ratios were 1.66 (95% CI 1.58-1.74) in outpatients and 1.14 (95% CI 1.12-1.16) in inpatients. In hospitalized patients 80 years of age or older, no association was observed between diabetes and COVID-19-related mortality (adjusted hazard ratio: 1.03; 95% CI 0.98-1.08). Among patients without COVID-19, the adjusted hazard ratio for death was 1.78 (95% CI 1.73-1.84). In conclusion, in adult patients with COVID-19 in Mexico, the risk of death associated with diabetes decreased with age. No association between diabetes and mortality was observed among inpatients 80 years of age or older. Our findings should be verified in other populations.

Type 2 Diabetes Mellitus and COVID-19: A Narrative Review

The pandemic of coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has involved more than one hundred million individuals, including more than two million deaths. Diabetes represents one of the most prevalent chronic conditions worldwide and significantly increases the risk of hospitalization and death in COVID-19 patients. In this review, we discuss the prevalence, the pathophysiological mechanisms, and the outcomes of COVID-19 infection in people with diabetes. We propose a rationale for using drugs prescribed in patients with diabetes and some pragmatic clinical recommendations to deal with COVID-19 in this kind of patient.

Diabetes, obesity, metabolism, and SARS-CoV-2 infection: the end of the beginning

The increased prevalence of obesity, diabetes, and cardiovascular risk factors in people hospitalized with severe COVID-19 illness has engendered considerable interest in the metabolic aspects of SARS-CoV-2-induced pathophysiology. Here, I update concepts informing how metabolic disorders and their co-morbidities modify the susceptibility to, natural history, and potential treatment of SARS-CoV-2 infection, with a focus on human biology. New data informing genetic predisposition, epidemiology, immune responses, disease severity, and therapy of COVID-19 in people with obesity and diabetes are highlighted. The emerging relationships of metabolic disorders to viral-induced immune responses and viral persistence, and the putative importance of adipose and islet ACE2 expression, glycemic control, cholesterol metabolism, and glucose- and lipid-lowering drugs is reviewed, with attention to controversies and unresolved questions. Rapid progress in these areas informs our growing understanding of SARS-CoV-2 infection in people with diabetes and obesity, while refining the therapeutic strategies and research priorities in this vulnerable population.

Global pandemics interconnected - obesity, impaired metabolic health and COVID-19

Obesity and impaired metabolic health are established risk factors for the non-communicable diseases (NCDs) type 2 diabetes mellitus, cardiovascular disease, neurodegenerative diseases, cancer and nonalcoholic fatty liver disease, otherwise known as metabolic associated fatty liver disease (MAFLD). With the worldwide spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), obesity and impaired metabolic health also emerged as important determinants of severe coronavirus disease 2019 (COVID-19). Furthermore, novel findings indicate that specifically visceral obesity and characteristics of impaired metabolic health such as hyperglycaemia, hypertension and subclinical inflammation are associated with a high risk of severe COVID-19. In this Review, we highlight how obesity and impaired metabolic health increase complications and mortality in COVID-19. We also summarize the consequences of SARS-CoV-2 infection for organ function and risk of NCDs. In addition, we discuss data indicating that the COVID-19 pandemic could have serious consequences for the obesity epidemic. As obesity and impaired metabolic health are both accelerators and consequences of severe COVID-19, and might adversely influence the efficacy of COVID-19 vaccines, we propose strategies for the prevention and treatment of obesity and impaired metabolic health on a clinical and population level, particularly while the COVID-19 pandemic is present.

Hypertension and COVID-19: Ongoing Controversies

Coronavirus disease 2019 (COVID-19) has become a worldwide pandemic responsible for millions of deaths around the world. Hypertension has been identified as one of the most common comorbidities and risk factors for severity and adverse outcome in these patients. Recent investigations have raised the question whether hypertension represents a predictor of outcome in COVID-19 patients independently of other common comorbidities such as diabetes, obesity, other cardiovascular diseases, chronic kidney, liver, and pulmonary diseases. However, the impact of chronic and newly diagnosed hypertension in COVID-19 patients has been insufficiently investigated. The same is true for the relationship between blood pressure levels and outcomes in COVID-19 patients. It seems that the long discussion about the impact of angiotensin-converting enzyme inhibitors (ACEI) and blockers of angiotensin I receptors (ARB) on severity and outcome in COVID-19 is approaching an end because the large number of original studies and meta-analyses discarded the initial findings about higher prevalence of ACEI/ARB use in patients with unfavorable outcomes. Nevertheless, there are many controversies in the relationship between hypertension and COVID-19. The aim of this review article is to provide a clinical overview of the currently available evidence regarding the predictive value of hypertension, the effect of blood pressure levels, the impact of previously known and newly diagnosed hypertension, and the effect of antihypertensive therapy on the severity and outcomes in COVID-19 patients.

Diabetes predicts severity of COVID-19 infection in a retrospective cohort: A mediatory role of the inflammatory biomarker C-reactive protein

Diabetes is a risk factor for developing severe COVID-19, but the pathogenesis remains unclear. We investigated if the association of diabetes and COVID-19 severity may be mediated by inflammation. We also hypothesized that this increased risk may extend to prediabetes. Hospitalized patients in Singapore with COVID-19 were subdivided into three groups in a retrospective cohort: normoglycemia (HbA1c: ≤5.6%), prediabetes (HbA1c: 5.7%-6.4%) and diabetes (HbA1c: ≥6.5%). The primary outcome of severe COVID-19 was defined by respiratory rate ≥30, SpO2 ≤93% or intensive care unit admission. The association between clinical factors on severe COVID-19 outcome was analyzed by cox regression. Adjusted mediation analysis of C-reactive protein (CRP) on the relationship between diabetes and severe COVID-19 was performed. Of 1042 hospitalized patients, mean age 39 ± 11 years, 13% had diabetes, 9% prediabetes and 78% normoglycemia. Severe COVID-19 occurred in 4.9% of subjects. Compared to normoglycemia, diabetes was significantly associated with severe COVID-19 on both univariate (hazard ratio [HR]: 9.94; 95% confidence interval [CI]: 5.54-17.84; p < .001) and multivariate analysis (HR: 3.99; 95% CI: 1.92-8.31; p < .001), while prediabetes was not a risk factor (HR: 0.94; 95% CI: 0.22-4.03; p = .929). CRP, a biomarker of inflammation, mediated 32.7% of the total association between diabetes and severe COVID-19 outcome. In conclusion, CRP is a partial mediator of the association between diabetes and severe COVID-19 infection, confirming that inflammation is important in the pathogenesis of severe COVID-19 in diabetes.

Hospital bed capacity and usage across secondary healthcare providers in England during the first wave of the COVID-19 pandemic: a descriptive analysis

OBJECTIVE

In this study, we describe the pattern of bed occupancy across England during the peak of the first wave of the COVID-19 pandemic.

DESIGN

Descriptive survey.

SETTING

All non-specialist secondary care providers in England from 27 March27to 5 June 2020.

PARTICIPANTS

Acute (non-specialist) trusts with a type 1 (ie, 24 hours/day, consultant-led) accident and emergency department (n=125), Nightingale (field) hospitals (n=7) and independent sector secondary care providers (n=195).

MAIN OUTCOME MEASURES

Two thresholds for 'safe occupancy' were used: 85% as per the Royal College of Emergency Medicine and 92% as per NHS Improvement.

RESULTS

At peak availability, there were 2711 additional beds compatible with mechanical ventilation across England, reflecting a 53% increase in capacity, and occupancy never exceeded 62%. A consequence of the repurposing of beds meant that at the trough there were 8.7% (8508) fewer general and acute beds across England, but occupancy never exceeded 72%. The closest to full occupancy of general and acute bed (surge) capacity that any trust in England reached was 99.8% . For beds compatible with mechanical ventilation there were 326 trust-days (3.7%) spent above 85% of surge capacity and 154 trust-days (1.8%) spent above 92%. 23 trusts spent a cumulative 81 days at 100% saturation of their surge ventilator bed capacity (median number of days per trust=1, range: 1-17). However, only three sustainability and transformation partnerships (aggregates of geographically co-located trusts) reached 100% saturation of their mechanical ventilation beds.

CONCLUSIONS

Throughout the first wave of the pandemic, an adequate supply of all bed types existed at a national level. However, due to an unequal distribution of bed utilisation, many trusts spent a significant period operating above 'safe-occupancy' thresholds despite substantial capacity in geographically co-located trusts, a key operational issue to address in preparing for future waves.

Cost effectiveness of bariatric surgery in patients with obesity related comorbidities: A retrospective study

Background and Aim:

Bariatric surgery has been reported to be an effective but expensive method for obesity management. This study aimed to determine the economic benefit for patients who underwent bariatric surgery.

Methodology:

We conducted a retrospective chart review of patients who underwent bariatric surgery and was on medications for obesity-related comorbidities at the Obesity Research Center in King Khalid University Hospital, Riyadh, Saudi Arabia. Data on the use and cost of medications before and after bariatric surgery were collected.

Results:

A total of 266 patients, 107 males (40.23%), and 159 Females (59.77%) with a mean age of 41.06 years were included in the study. There was a reduction in the mean number of medications used by patients before and 1-year post-op (before: 1.84, after: 0.52), with a significant reduction in the cost of medications (SAR5152.24 before, and SAR1695.36 after, 67% reduction, P < 0.001). Patients < 32 years old had the most reduction in medications cost (76.64% reduction). No significant difference in the cost reduction after surgery between genders (P = 0.971). There were significant reductions in numbers of out-patient clinic visits (2.26 ± 2.43 to 1.57 ± 1.42) and in-patient hospitalizations (0.31 ± 0.57 to 0.10 ± 0.36) after surgery (P < 0.001 and P < 0.001, respectively).

Conclusion:

Bariatric surgery can be considered as a cost-effective treatment for patients with obesity-related comorbidities. A significant reduction has been found in post-operative medications cost, out-patient clinic visits and in-patient hospitalizations after bariatric surgery.

Clinical characteristics and short-term prognosis of in-patients with diabetes and COVID-19: A retrospective study from an academic center in Belgium

BACKGROUND AND AIMS

We describe the characteristics and short-term prognosis of in-patients with diabetes and COVID-19 admitted to a Belgian academic care center.

METHODS

We retrospectively reviewed the data on admission from patients with known or newly-diagnosed diabetes and confirmed COVID-19. First, survivors were compared to non-survivors to study the predictive factors of in-hospital death in patients with diabetes. Secondly, diabetic patients with SARS-CoV-2 pneumonia were matched for age and sex with non-diabetic patients with SARS-CoV-2 pneumonia, to study the prognosis and predictive factors of in-hospital death related to diabetes.

RESULTS

Seventy-three diabetic patients were included. Mean age was 69 (±14) years. Women accounted for 52%. Most patients had type 2 diabetes (89.0%), long-term complications of hyperglycemia (59.1%), and hypertension (80.8%). The case-fatality rate (CFR) was 15%. Non-survivors had more severe pneumonia based on imaging (p 0.029) and were less often treated with metformin (p 0.036). In patients with SARS-CoV-2 pneumonia, CFR was 15.6% in diabetic (n = 64) and 25.0% in non-diabetic patients (n = 128), the difference being non-significant (p 0.194). Predictive factors of in-hospital death were elevated white blood cells count (HR 9.4, CI 1.50-58.8, p 0.016) and severe pneumonia on imaging (HR 25.0, CI 1.34-466, p 0.031) in diabetic patients, and cognitive impairment (HR 5.80, CI 1.61-20.9, p 0.007) and cardiovascular disease (HR 5.63, CI 1.54-20.6, p 0.009) in non-diabetic patients.

CONCLUSION

In this monocentric cohort from Belgium, diabetic in-patients with COVID-19 had mostly type 2 diabetes, prevalent hyperglycemia-related vascular complications and comorbidities including hypertension. In this cohort, the CFR was not statistically different between patients with and without diabetes.

A semi-supervised approach for rapidly creating clinical biomarker phenotypes in the UK Biobank using different primary care EHR and clinical terminology systems

OBJECTIVES

The UK Biobank (UKB) is making primary care electronic health records (EHRs) for 500 000 participants available for COVID-19-related research. Data are extracted from four sources, recorded using five clinical terminologies and stored in different schemas. The aims of our research were to: (a) develop a semi-supervised approach for bootstrapping EHR phenotyping algorithms in UKB EHR, and (b) to evaluate our approach by implementing and evaluating phenotypes for 31 common biomarkers.

MATERIALS AND METHODS

We describe an algorithmic approach to phenotyping biomarkers in primary care EHR involving (a) bootstrapping definitions using existing phenotypes, (b) excluding generic, rare, or semantically distant terms, (c) forward-mapping terminology terms, (d) expert review, and (e) data extraction. We evaluated the phenotypes by assessing the ability to reproduce known epidemiological associations with all-cause mortality using Cox proportional hazards models.

RESULTS

We created and evaluated phenotyping algorithms for 31 biomarkers many of which are directly related to COVID-19 complications, for example diabetes, cardiovascular disease, respiratory disease. Our algorithm identified 1651 Read v2 and Clinical Terms Version 3 terms and automatically excluded 1228 terms. Clinical review excluded 103 terms and included 44 terms, resulting in 364 terms for data extraction (sensitivity 0.89, specificity 0.92). We extracted 38 190 682 events and identified 220 978 participants with at least one biomarker measured.

DISCUSSION AND CONCLUSION

Bootstrapping phenotyping algorithms from similar EHR can potentially address pre-existing methodological concerns that undermine the outputs of biomarker discovery pipelines and provide research-quality phenotyping algorithms.