scholarly journals Clinical Characteristics of COVID-19 Patients in a Regional Population With Diabetes Mellitus: The ACCREDIT Study

2022 ◽  
Vol 12 ◽  
Author(s):  
Daniel Kevin Llanera ◽  
Rebekah Wilmington ◽  
Haika Shoo ◽  
Paulo Lisboa ◽  
Ian Jarman ◽  
...  

ObjectiveTo identify clinical and biochemical characteristics associated with 7- & 30-day mortality and intensive care admission amongst diabetes patients admitted with COVID-19.Research Design and MethodsWe conducted a cohort study collecting data from medical notes of hospitalised people with diabetes and COVID-19 in 7 hospitals within the Mersey-Cheshire region from 1 January to 30 June 2020. We also explored the impact on inpatient diabetes team resources. Univariate and multivariate logistic regression analyses were performed and optimised by splitting the dataset into a training, test, and validation sets, developing a robust predictive model for the primary outcome.ResultsWe analyzed data from 1004 diabetes patients (mean age 74.1 (± 12.6) years, predominantly men 60.7%). 45% belonged to the most deprived population quintile in the UK. Median BMI was 27.6 (IQR 23.9-32.4) kg/m2. The primary outcome (7-day mortality) occurred in 24%, increasing to 33% by day 30. Approximately one in ten patients required insulin infusion (9.8%). In univariate analyses, patients with type 2 diabetes had a higher risk of 7-day mortality [p < 0.05, OR 2.52 (1.06, 5.98)]. Patients requiring insulin infusion had a lower risk of death [p = 0.02, OR 0.5 (0.28, 0.9)]. CKD in younger patients (<70 years) had a greater risk of death [OR 2.74 (1.31-5.76)]. BMI, microvascular and macrovascular complications, HbA1c, and random non-fasting blood glucose on admission were not associated with mortality. On multivariate analysis, CRP and age remained associated with the primary outcome [OR 3.44 (2.17, 5.44)] allowing for a validated predictive model for death by day 7.ConclusionsHigher CRP and advanced age were associated with and predictive of death by day 7. However, BMI, presence of diabetes complications, and glycaemic control were not. A high proportion of these patients required insulin infusion warranting increased input from the inpatient diabetes teams.

2021 ◽  
Vol 12 ◽  
pp. 204209862098569
Author(s):  
Phyo K. Myint ◽  
Ben Carter ◽  
Fenella Barlow-Pay ◽  
Roxanna Short ◽  
Alice G. Einarsson ◽  
...  

Background: Whilst there is literature on the impact of SARS viruses in the severely immunosuppressed, less is known about the link between routine immunosuppressant use and outcome in COVID-19. Consequently, guidelines on their use vary depending on specific patient populations. Methods: The study population was drawn from the COPE Study (COVID-19 in Older People), a multicentre observational cohort study, across the UK and Italy. Data were collected between 27 February and 28 April 2020 by trained data-collectors and included all unselected consecutive admissions with COVID-19. Load (name/number of medications) and dosage of immunosuppressant were collected along with other covariate data. Primary outcome was time-to-mortality from the date of admission (or) date of diagnosis, if diagnosis was five or more days after admission. Secondary outcomes were Day-14 mortality and time-to-discharge. Data were analysed with mixed-effects, Cox proportional hazards and logistic regression models using non-users of immunosuppressants as the reference group. Results: In total 1184 patients were eligible for inclusion. The median (IQR) age was 74 (62–83), 676 (57%) were male, and 299 (25.3%) died in hospital (total person follow-up 15,540 days). Most patients exhibited at least one comorbidity, and 113 (~10%) were on immunosuppressants. Any immunosuppressant use was associated with increased mortality: aHR 1.87, 95% CI: 1.30, 2.69 (time to mortality) and aOR 1.71, 95% CI: 1.01–2.88 (14-day mortality). There also appeared to be a dose–response relationship. Conclusion: Despite possible indication bias, until further evidence emerges we recommend adhering to public health measures, a low threshold to seek medical advice and close monitoring of symptoms in those who take immunosuppressants routinely regardless of their indication. However, it should be noted that the inability to control for the underlying condition requiring immunosuppressants is a major limitation, and hence caution should be exercised in interpretation of the results. Plain Language Summary Regular Use of Immune Suppressing Drugs is Associated with Increased Risk of Death in Hospitalised Patients with COVID-19 Background: We do not have much information on how the COVID-19 virus affects patients who use immunosuppressants, drugs which inhibit or reduce the activity of the immune system. There are various conflicting views on whether immune-suppressing drugs are beneficial or detrimental in patients with the disease. Methods: This study collected data from 10 hospitals in the UK and one in Italy between February and April 2020 in order to identify any association between the regular use of immunosuppressant medicines and survival in patients who were admitted to hospital with COVID-19. Results: 1184 patients were included in the study, and 10% of them were using immunosuppressants. Any immunosuppressant use was associated with increased risk of death, and the risk appeared to increase if the dose of the medicine was higher. Conclusion: We therefore recommend that patients who take immunosuppressant medicines routinely should carefully adhere to social distancing measures, and seek medical attention early during the COVID-19 pandemic.


2021 ◽  
Vol 39 (28_suppl) ◽  
pp. 330-330
Author(s):  
Teja Ganta ◽  
Stephanie Lehrman ◽  
Rachel Pappalardo ◽  
Madalene Crow ◽  
Meagan Will ◽  
...  

330 Background: Machine learning models are well-positioned to transform cancer care delivery by providing oncologists with more accurate or accessible information to augment clinical decisions. Many machine learning projects, however, focus on model accuracy without considering the impact of using the model in real-world settings and rarely carry forward to clinical implementation. We present a human-centered systems engineering approach to address clinical problems with workflow interventions utilizing machine learning algorithms. Methods: We aimed to develop a mortality predictive tool, using a Random Forest algorithm, to identify oncology patients at high risk of death within 30 days to move advance care planning (ACP) discussions earlier in the illness trajectory. First, a project sponsor defined the clinical need and requirements of an intervention. The data scientists developed the predictive algorithm using data available in the electronic health record (EHR). A multidisciplinary workgroup was assembled including oncology physicians, advanced practice providers, nurses, social workers, chaplain, clinical informaticists, and data scientists. Meeting bi-monthly, the group utilized human-centered design (HCD) methods to understand clinical workflows and identify points of intervention. The workgroup completed a workflow redesign workshop, a 90-minute facilitated group discussion, to integrate the model in a future state workflow. An EHR (Epic) analyst built the user interface to support the intervention per the group’s requirements. The workflow was piloted in thoracic oncology and bone marrow transplant with plans to scale to other cancer clinics. Results: Our predictive model performance on test data was acceptable (sensitivity 75%, specificity 75%, F-1 score 0.71, AUC 0.82). The workgroup identified a “quality of life coordinator” who: reviews an EHR report of patients scheduled in the upcoming 7 days who have a high risk of 30-day mortality; works with the oncology team to determine ACP clinical appropriateness; documents the need for ACP; identifies potential referrals to supportive oncology, social work, or chaplain; and coordinates the oncology appointment. The oncologist receives a reminder on the day of the patient’s scheduled visit. Conclusions: This workgroup is a viable approach that can be replicated at institutions to address clinical needs and realize the full potential of machine learning models in healthcare. The next steps for this project are to address end-user feedback from the pilot, expand the intervention to other cancer disease groups, and track clinical metrics.


The Physician ◽  
2020 ◽  
Vol 6 (2) ◽  
Author(s):  
Anna Zatorska ◽  
Niladri Konar ◽  
Pratyasha Saha ◽  
Alice Moseley ◽  
Jessica Denman ◽  
...  

Ethnicity was found to be an independent risk factor in COVID-19 outcomes in the UK and the USA during the pandemic surge. London, being in the epicentre and having one of the most ethnically diverse population in the UK, was likely to have experienced a much higher intensity of this phenomenon. Black Asian and Minority ethnic groups were more likely to be admitted, more likely to require admission to intensive care, and more likely to die from COVID-19. We undertook an analysis of a case series to explore the impact of ethnicity in hospitalised patients with confirmed COVID-19 during the 3 months of the pandemic. Our results demonstrated that although the proportion of Asian and Black patients were representative of the local population distribution, they were much younger. The prevalence of comorbidities was similar but logistic regression analysis showed that male sex (OR 1.4, 95% CI 1.1-1.9; p=0.02), age (OR 1.03, 95% CI 1.02 - 1.04, p<0.001), those in the ‘Other’ [Odds ratio 1.7 (1.1-2.6) p = 0.01] and ‘Asian’[Odds ratio 1.8 (1.1-2.7) p=0.01], category were at higher risk of death in this cohort. Our results, therefore, are consistent with the overall data from the UK and USA indicating that ethnicity remains a significant additional risk and hence our clinical services must ensure that adequate provision is made to cater to this risk and research must be designed to understand the causes.   


2020 ◽  
Author(s):  
Gisli Jenkins ◽  
Tom Drake ◽  
Annemarie B Docherty ◽  
Ewan Harrison ◽  
Jennifer Quint ◽  
...  

Rationale: The impact of COVID-19 on patients with Interstitial Lung Disease (ILD) has not been established. Objectives: To assess outcomes following COVID-19 in patients with ILD versus those without in a contemporaneous age, sex and comorbidity matched population. Methods: An international multicentre audit of patients with a prior diagnosis of ILD admitted to hospital with COVID-19 between 1 March and 1 May 2020 was undertaken and compared with patients, without ILD obtained from the ISARIC 4C cohort, admitted with COVID-19 over the same period. The primary outcome was survival. Secondary analysis distinguished IPF from non-IPF ILD and used lung function to determine the greatest risks of death. Measurements and Main Results: Data from 349 patients with ILD across Europe were included, of whom 161 were admitted to hospital with laboratory or clinical evidence of COVID-19 and eligible for propensity-score matching. Overall mortality was 49% (79/161) in patients with ILD with COVID-19. After matching ILD patients with COVID-19 had higher mortality (HR 1.60, Confidence Intervals 1.17-2.18 p=0.003) compared with age, sex and co-morbidity matched controls without ILD. Patients with a Forced Vital Capacity (FVC) of <80% had an increased risk of death versus patients with FVC ≥80% (HR 1.72, 1.05-2.83). Furthermore, obese patients with ILD had an elevated risk of death (HR 1.98, 1.13−3.46). Conclusions: Patients with ILD are at increased risk of death from COVID-19, particularly those with poor lung function and obesity. Stringent precautions should be taken to avoid COVID-19 in patients with ILD.


Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 28-29
Author(s):  
Austin Kulasekararaj ◽  
Shaloo Gupta ◽  
Thomas Schroeder ◽  
Halley Constantino ◽  
Jay Grisolano ◽  
...  

Introduction: Studies have shown that transfusion-dependent (TD) patients with MDS have worse overall survival (OS) than transfusion-independent (TI) patients. However, few studies have examined physicians' perspectives on the relationship between transfusion dependence and OS and other clinical and economic outcomes in MDS. The current study investigated physicians' understanding of the impact of transfusion status (TS) on clinical and economic outcomes in 5 European countries. Methods: Interviews were conducted with physicians (3 each in France, Germany, Italy, Spain, and the UK) to pre-test and revise the study questionnaire, a 40-minute web-based physician survey via the M3 Global Research physician panel, for relevance and understanding. The revised questionnaire was translated to allow physicians to complete the survey in their native language. To participate in the survey, physicians had to be specialized in oncology/hematology, have been in practice for 2-35 years, spend ≥ 75% of their time in direct patient care, and have managed ≥ 15 patients with MDS in the past 3 months. The survey asked physicians for their perspectives on the impact of TS on risk of death, acute myeloid leukemia (AML) progression, chance of leukemia-free state (LFS), significant bleeding events, number of infection events, hospitalizations, and ER visits, based on their own clinical experience, beliefs, and knowledge of the literature. In the instructions accompanying the survey, physicians were provided with a definition of transfusion dependence (≥ 1 unit(s) every 8 weeks), transfusion burden (TB; high burden: ≥ 4 units every 4 weeks), and MDS International Prognostic Scoring System (IPSS) and revised IPSS (IPSS-R) risk levels to ensure consistency across all physicians. All results were reported descriptively, with frequency counts and percentages for categorical/ordinal data and mean (standard error [SE]) for continuous data. Results: Overall, 244 hematologist/oncologists, 124 hematologists, and 10 oncologists completed the survey in France, Germany, Italy, Spain, and the UK (n = 75 [approx.] in each country). On average, physicians were in practice for 14.70 years (SE 0.32), 41.3% were between the age of 45 and 54 years, and 64.3% were male. Physicians had seen an average of 54.5 patients (SE 2.26) with MDS in the past 3 months. The average risk of death among TI patients versus TD patients was 35.27% (SE 1.06) lower in the lower-risk MDS population and 37.61% (SE 0.87) lower among patients of all risk levels. The average risk of death among patients with low versus high TB was 42.65% (SE 0.95) lower among lower-risk TD patients and 41.89% (SE 0.75) lower among all-risk TD patients. The average risk of death for TD patients who became TI after treatment was 40.64% (SE 0.79) lower than for those who remained TD after treatment, across all risk levels (Figure). Similar results were found for AML progression and chance of LFS with TD patients having worse outcomes. The mean number of infection events per person per year (PPPY) was reported to be 3.96 (SE 0.82) for lower-risk TI patients and 5.15 (SE 0.91) for lower-risk TD patients, and the mean number of significant bleeding events PPPY reported was 2.88 (SE 0.85) for lower-risk TI patients and 3.46 (SE 0.81) for lower-risk TD patients. The mean number of all-cause hospitalizations PPPY reported was 3.62 (SE 0.76) among TI patients and 6.35 (SE 0.89) among TD patients. Physicians also reported TI patients having 3.28 (SE 0.84) ER visits PPPY and TD patients having 5.61 (SE 0.84) ER visits PPPY. These findings were numerically similar across all 5 countries. Conclusions: Overall, physicians reported a greater risk of death, AML progression, and leukemic death, more infections and significant bleeding events, and increased hospitalization and ER visits for patients with MDS who are TD versus TI, based on their clinical experience and knowledge of the literature. The results were similar across patients with different risk levels and across the countries in question. New treatment options for patients with MDS to reduce or eliminate TB are warranted. Disclosures Kulasekararaj: Alexion Pharmaceuticals Inc.: Honoraria, Membership on an entity's Board of Directors or advisory committees. Gupta:Kantar: Current Employment; Bristol Myers Squibb: Consultancy, Research Funding. Constantino:Kantar: Current Employment. Grisolano:Kantar: Current Employment; Bristol Myers Squibb: Consultancy. Tang:Bristol Myers Squibb: Current Employment; Asclepius Analytics: Current Employment. Jones:Bristol Myers Squibb: Current Employment. Tang:BMS: Current Employment, Current equity holder in publicly-traded company.


Diabetologia ◽  
2021 ◽  
Author(s):  
Yue Ruan ◽  
◽  
Robert E. J. Ryder ◽  
Parijat De ◽  
Benjamin C. T. Field ◽  
...  

Abstract Aims/hypothesis The aim of this work was to describe the clinical characteristics of adults with type 1 diabetes admitted to hospital and the risk factors associated with severe coronavirus disease-2019 (COVID-19) in the UK. Methods A retrospective cohort study was performed using data collected through a nationwide audit of people admitted to hospital with diabetes and COVID-19, conducted by the Association of British Clinical Diabetologists from March to October 2020. Prespecified demographic, clinical, medication and laboratory data were collected from the electronic and paper medical record systems of the participating hospitals by local clinicians. The primary outcome of the study, severe COVID-19, was defined as death in hospital and/or admission to the adult intensive care unit (AICU). Logistic regression models were used to generate age-adjusted ORs. Results Forty UK centres submitted data. The final dataset included 196 adults who were admitted to hospital and had both type 1 diabetes and COVID-19 on admission (male sex 55%, white 70%, with mean [SD] age 62 [19] years, BMI 28.3 [7.3] kg/m2 and last recorded HbA1c 76 [31] mmol/mol [9.1 (5.0)%]). The prevalence of pre-existing microvascular disease and macrovascular disease was 56% and 39%, respectively. The prevalence of diabetic ketoacidosis on admission was 29%. A total of 68 patients (35%) died or were admitted to AICU. The proportions of people that died were 7%, 38% and 38% of those aged <55, 55–74 and ≥75 years, respectively. BMI, serum creatinine levels and having one or more microvascular complications were positively associated with the primary outcome after adjusting for age. Conclusions/interpretation In people with type 1 diabetes and COVID-19 who were admitted to hospital in the UK, higher BMI, poorer renal function and presence of microvascular complications were associated with greater risk of death and/or admission to AICU. Risk of severe COVID-19 is reassuringly very low in people with type 1 diabetes who are under 55 years of age without microvascular or macrovascular disease. In people with Type 1 diabetes and COVID-19 admitted to hospital in the UK, BMI and one or more microvascular complications had a positive association and low serum creatine levels had a negative association with death/admission to intensive care unit after adjusting for age.


2012 ◽  
Vol 12 (1) ◽  
Author(s):  
Shema Tariq ◽  
Alex Pillen ◽  
Pat A Tookey ◽  
Alison E Brown ◽  
Jonathan Elford

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