Association between antidiabetic drug use and the risk of COVID-19 hospitalization in the INSIGHT Clinical Research Network in New York City

Application of a data continuity prediction algorithm to an electronic health record-based pharmacoepidemiology study

BACKGROUND AND OBJECTIVES

Use of algorithms to identify patients with high data-continuity in electronic health records (EHRs) may increase study validity. Practical experience with this approach remains limited.

METHODS

We developed and validated four algorithms to identify patients with high data continuity in an EHR-based data source. Selected algorithms were then applied to a pharmacoepidemiologic study comparing rates of COVID-19 hospitalization in patients exposed to insulin versus noninsulin antidiabetic drugs.

RESULTS

A model using a short list of five EHR-derived variables performed as well as more complex models to distinguish high- from low-data continuity patients. Higher data continuity was associated with more accurate ascertainment of key variables. In the pharmacoepidemiologic study, patients with higher data continuity had higher observed rates of the COVID-19 outcome and a large unadjusted association between insulin use and the outcome, but no association after propensity score adjustment.

DISCUSSION

We found that a simple, portable algorithm to predict data continuity gave comparable performance to more complex methods. Use of the algorithm significantly impacted the results of an empirical study, with evidence of more valid results at higher levels of data continuity.

Potential use of sodium glucose co-transporter 2 inhibitors during acute illness: a systematic review based on COVID-19

OBJECTIVE

SGLT-2i are increasingly recognized for their benefits in patients with cardiometabolic risk factors. Additionally, emerging evidence suggests potential applications in acute illnesses, including COVID-19. This systematic review aims to evaluate the effects of SGLT-2i in patients facing acute illness, particularly focusing on SARS-CoV-2 infection.

METHODS

Following PRISMA guidelines, a systematic search of PubMed, Scopus, medRxiv, Research Square, and Google Scholar identified 22 studies meeting inclusion criteria, including randomized controlled trials and observational studies. Data extraction and quality assessment were conducted independently.

RESULTS

Out of the 22 studies included in the review, six reported reduced mortality in DM-2 patients taking SGLT-2i, while two found a decreased risk of hospitalization. Moreover, one study demonstrated a lower in-hospital mortality rate in DM-2 patients under combined therapy of metformin plus SGLT-2i. However, three studies showed a neutral effect on the risk of hospitalization. No increased risk of developing COVID-19 was associated with SGLT-2i use in DM-2 patients. Prior use of SGLT-2i was not associated with ICU admission and need for MV. The risk of acute kidney injury showed variability, with inconsistent evidence regarding diabetic ketoacidosis.

CONCLUSION

Our systematic review reveals mixed findings on the efficacy of SGLT-2i use in COVID-19 patients with cardiometabolic risk factors. While some studies suggest potential benefits in reducing mortality and hospitalizations, others report inconclusive results. Further research is needed to clarify optimal usage and mitigate associated risks, emphasizing caution in clinical interpretation.

Pre-admission use of sodium glucose transporter-2 inhibitor (SGLT-2i) may significantly improves Covid-19 outcomes in patients with diabetes: A systematic review, meta-analysis, and meta-regression

AIMS

This study aims to examine the effectiveness of using sodium glucose transporter-2 inhibitor (SGLT-2i) before hospital admission on Covid-19 outcomes in diabetic patients.

METHODS

A literature search was conducted using specific keywords until October 24th, 2022 on 4 databases: Medline, Scopus, Cochrane Library, and ClinicalTrials.gov. All articles regarding SGLT-2i in diabetic patients with Covid-19 were included in the study. Outcomes in this study were calculated using random-effect models to generate pooled odds ratio (OR) with 95% confidence intervals (CI).

RESULTS

A total of 17 studies were included in the analysis. Our meta-analysis showed that pre-admission use of SGLT-2i was associated with reduced mortality (OR 0.69; 95 %CI: 0.56 - 0.87, p = 0.001, I² = 91 %) and severity of Covid-19 (OR 0.88; 95 %CI: 0.80 - 0.97, p = 0.008, I² = 13 %). This benefit of SGLT-2i on Covid-19 mortality was not significantly affected by patient's factors such as age (p = 0.2335), sex (p = 0.2742), hypertension (p = 0.2165), heart failure (p = 0.1616), HbA1c levels (p = 0.4924), metformin use (p = 0.6617), duration of diabetes (p = 0.7233), and BMI (p = 0.1797).

CONCLUSIONS

This study suggests that SGLT-2i as glucose lowering treatment in patients with diabetes has a positive effect on Covid-19 outcomes, therefore can be considered as an antidiabetic drug of choice, especially during the Covid-19 pandemic. Short Title: SGLT-2i in diabetes and Covid-19.

REGISTRATION DETAILS

CRD42022369784.

Association of Glucose-Lowering Drugs With Outcomes in Patients With Diabetes Before Hospitalization for COVID-19: A Systematic Review and Network Meta-analysis

IMPORTANCE

Patients with COVID-19 have a high prevalence of diabetes, and diabetes and blood glucose control are determinants of intensive care unit admission and mortality.

OBJECTIVE

To evaluate the association between COVID-19-related adverse outcomes and 8 antihyperglycemic drugs in patients with diabetes who were subsequently diagnosed and hospitalized with COVID-19.

DATA SOURCES

Data were retrieved and collected in PubMed, Embase, Cochrane Central Register, Web of Science, and ClinicalTrials.gov from database inception to September 5, 2022.

STUDY SELECTION

For this systematic review and network meta-analysis, randomized clinical trials and observational studies conducted among patients with diabetes while receiving glucose-lowering therapies for at least 14 days before the confirmation of COVID-19 infection were included after blinded review by 2 independent reviewers and consultations of disagreement by a third independent reviewer. Of 1802 studies initially identified, 31 observational studies met the criteria for further analysis.

DATA EXTRACTION AND SYNTHESIS

This study follows the Preferred Reporting Items for Systematic Reviews and Meta-analyses reporting guideline. Bayesian network meta-analyses were performed with random effects.

MAIN OUTCOMES AND MEASURES

A composite adverse outcome, including the need for intensive care unit admission, invasive and noninvasive mechanical ventilation, or in-hospital death.

RESULTS

Thirty-one distinct observational studies (3 689 010 patients with diabetes hospitalized for COVID-19) were included. The sodium-glucose cotransporter-2 inhibitors (SGLT-2is) were associated with relatively lower risks of adverse outcomes compared with insulin (log of odds ratio [logOR], 0.91; 95% credible interval [CrI], 0.57-1.26), dipeptidyl peptidase-4 inhibitors (logOR, 0.61; 95% CrI, 0.28-0.93), secretagogues (logOR, 0.37; 95% CrI, 0.02-0.72), and glucosidase inhibitors (logOR, 0.50; 95% CrI, 0.00-1.01). Based on the surface under the cumulative ranking curves value, SGLT-2is were associated with the lowest probability for adverse outcomes (6%), followed by glucagon-like peptide-1 receptor agonists (25%) and metformin (28%). A sensitivity analysis revealed that the study was reliable.

CONCLUSIONS AND RELEVANCE

These findings suggest that the use of an SGLT-2i before COVID-19 infection is associated with lower COVID-19-related adverse outcomes. In addition to SGLT-2is, glucagon-like peptide-1 receptor agonists and metformin were also associated with relatively low risk of adverse outcomes.