Factors Related to Improvement of Glycemic Control Among Adults with Type 1 Diabetes During Lockdown Due to COVID-19

Abstract

Diabetes Technology & TherapeuticsVol. 23, No. 5 Letter to the EditorFree AccessFactors Related to Improvement of Glycemic Control Among Adults with Type 1 Diabetes During Lockdown Due to COVID-19Óscar Moreno-Domínguez, Noemí González-Pérez de Villar, Beatriz Barquiel, Natalia Hillman-Gadea, Ruth Gaspar-Lafuente, Montserrat Arévalo-Gómez, and Lucrecia HerranzÓscar Moreno-DomínguezAddress correspondence to: Óscar Moreno-Domínguez, MD, Division of Diabetes, Department of Endocrinology and Nutrition, Hospital Universitario La Paz, Paseo de la Castellana, 261, Madrid 28046, Spain E-mail Address: [email protected]Division of Diabetes, Department of Endocrinology and Nutrition, Hospital Universitario La Paz, Madrid, Spain.Search for more papers by this author, Noemí González-Pérez de VillarDivision of Diabetes, Department of Endocrinology and Nutrition, Hospital Universitario La Paz, Madrid, Spain.Search for more papers by this author, Beatriz BarquielDivision of Diabetes, Department of Endocrinology and Nutrition, Hospital Universitario La Paz, Madrid, Spain.Search for more papers by this author, Natalia Hillman-GadeaDivision of Diabetes, Department of Endocrinology and Nutrition, Hospital Universitario La Paz, Madrid, Spain.Search for more papers by this author, Ruth Gaspar-LafuenteDivision of Diabetes, Department of Endocrinology and Nutrition, Hospital Universitario La Paz, Madrid, Spain.Search for more papers by this author, Montserrat Arévalo-GómezDivision of Diabetes, Department of Endocrinology and Nutrition, Hospital Universitario La Paz, Madrid, Spain.Search for more papers by this author, and Lucrecia HerranzDivision of Diabetes, Department of Endocrinology and Nutrition, Hospital Universitario La Paz, Madrid, Spain.Search for more papers by this authorPublished Online:20 Apr 2021https://doi.org/10.1089/dia.2020.0550AboutSectionsPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookXLinked InRedditEmail Dear Editor:Owing to the COVID-19 pandemic, the Spanish government declared a state of alarm in which general mobility was limited. Because of this, people with type 1 diabetes experienced changes in lifestyle, which could have affected their glycemic control.1We evaluated the impact of lockdown in 138 adults in follow-up at La Paz University Hospital (Madrid, Spain): mean age 42.5 ± 15.3 years, 89 females/49 males, duration of diabetes 21.7 ± 13.8 years, 31.9% overweight, 7.9% obesity, 18.8% continuous subcutaneous insulin infusion (CSII) therapy and 81.2% multiple daily injection (MDI) therapy, last laboratory A1c 7.1% ± 0.9% (55 ± 10 mmol/mol), 87.7% received a structured diabetes educational program, 10.9% hypertension, 34.8% dyslipidemia, 5.1% diabetic kidney disease, 19.6% retinopathy, and 2.9% COVID-19 infection. All subjects met inclusion criteria (age ≥18 years old, type 1 diabetes, FreeStyle Libre [version 1] device users during the past 6 months, use of LibreView® platform to share data, and continuous glucose monitoring [CGM] use ≥70%). Each participant gave informed consent for data use.We analyzed the CGM metrics2 in three different periods: 2 weeks of normality before lockdown (February 21–March 5, 2020) (Period 1), 2 weeks of lockdown where leaving one's home was prohibited except for essential work and activities (March 16–29, 2020) (Period 2), and 2 weeks of de-escalation in which nonessential work and home departures were allowed in time bands (May 14–27, 2020) (Period 3). CGM metrics were compared between Period 1 and Period 2 and between Period 1 and Period 3 (Table 1). When comparing Period 1 with Period 2, a reduction in glucose mean (P < 0.001), GMI (P < 0.001), and time in range (P < 0.001) were observed, as well as an increase in time in range (P = 0.001). When comparing Period 1 with Period 3, these findings were maintained, as well as an increase in CGM use (P = 0.021) and in scans per day (P = 0.040) and a decrease in coefficient of variation (CV) (P = 0.002).Table 1. Comparison of Continuous Glucose Monitoring Metrics Between Period 1 and Period 2 and Between Period 1 and Period 3CGM metrics (n = 138)Before lockdownDuring lockdownP-valuea(vs. before lockdown)De-escalationP-valuea(vs. before lockdown)CGM use (%)94.7 ± 7.894.6 ± 7.00.94796.2 ± 5.50.021Scans per day11.6 ± 7.711.6 ± 7.60.88112.6 ± 8.00.040Mean glucose (mg/dL)155.5 ± 28.6149.0 ± 26.8<0.001145.6 ± 22.9<0.001GMI (%)7.03 ± 0.686.87 ± 0.55<0.0016.80 ± 0.54<0.001GMI (mmol/mol)53.3 ± 7.551.7 ± 7.0<0.00150.8 ± 6.0<0.001TAR (>180 mg/dL) (%)30.7 ± 16.727.0 ± 16.7<0.00124.7 ± 14.9<0.001TIR (70–180 mg/dL) (%)63.8 ± 15.266.7 ± 15.20.00169.5 ± 13.8<0.001TBR (<70 mg/dL) (%)5.5 ± 5.36.1 ± 5.20.0525.7 ± 5.50.553Coefficient of variation (CV) (%)36.6 ± 6.536.1 ± 6.20.15135.3 ± 6.40.002Data are expressed as mean ± standard deviation.aPaired Student's t-test.CGM, continuous glucose monitoring; CV, coefficient of variation; GMI, glucose management indicator; TAR, time above range; TBR, time below range; TIR, time in range.Patients who presented a clinically meaningful glycemic improvement (CMGI) during lockdown, defined by a decrease in GMI ≥0.5%,3–5 were compared with those who presented a decrease in GMI <0.5% in relation to their demographic characteristics. Likewise, a predictive model was performed to determine which variables predicted CMGI in this period.Twenty-four subjects (17.4%) presented a CMGI. They had a higher last laboratory A1c value than subjects who did not show it: 7.5% ± 1.0% (58 ± 11 mmol/mol) versus 7.1% ± 0.8% (54 ± 9 mmol/mol) (P = 0.041). No significant differences were obtained when comparing the rest of the variables. A forward stepwise multivariate logistic regression multiple analysis was performed to predict a CMGI. Only CSII therapy (adjusted odds ratio [OR] 3.77; 95% confidence interval [CI] [1.29–10.97]) (P = 0.015) and the last laboratory A1c (adjusted OR 1.96; 95% CI [1.15–3.34]) (P = 0.014) predicted a higher probability of presenting CMGI, whereas the duration of diabetes (adjusted OR 0.96; 95% CI [0.91–0.998]) (P = 0.039) predicted a lower probability of achieving such improvement.This study confirms that glycemic control based on CGM metrics in adults with type 1 diabetes significantly improved during lockdown due to the COVID-19 pandemic and maintained over time for at least 2 months during de-escalation. These results may support that having more time for self-management, along with the regularity of daily schedules, the type of food and physical activity, allows improving and maintaining glycemic control in patients with type 1 diabetes even 2 months after lockdown.Although similar data have been reported,6,7 this study consists of the largest sample of patients analyzed during the three periods mentioned and demonstrates the existence of clinical variables (CSII therapy, poor prior glycemic control, and shorter diabetes duration) that are associated with a better glycemic control during lockdown.AcknowledgmentsThe authors appreciate the support of all the members of the Division of Diabetes of the Department of Endocrinology at the Hospital Universitario La Paz.Author Disclosure StatementNo competing financial interests exist.Funding InformationNo funding was received for this study.References1. Ahola AJ, Mutter S, Forsblom C, et al.: Meal timing, meal frequency, and breakfast skipping in adult individuals with type 1 diabetes—associations with glycaemic control. Sci Rep 2019;9:20063. Crossref, Medline, Google Scholar2. Danne T, Nimri R, Battelino T, et al.: International consensus on use of continuous glucose monitoring. Diabetes Care 2017;40:1631–1640. Crossref, Medline, Google Scholar3. Bergenstal RM, Beck RW, Close KL, et al.: Glucose management indicator (GMI): a new term for estimating A1C from continuous glucose monitoring. Diabetes Care 2018;41:2275–2280. Crossref, Medline, Google Scholar4. Little RR, Rohlfing CL, Sacks DB; National Glycohemoglobin Standardization Program (NGSP) Steering Committee: status of hemoglobin A1c measurement and goals for improvement: from chaos to order for improving diabetes care. Clin Chem 2011;57:205–214. Crossref, Medline, Google Scholar5. Donna L: Applying recent A1C recommendations in clinical practice. US Pharm 2018;43:15–23. Google Scholar6. Prabhu Navis J, Leelarathna L, Mubita W, et al.: Impact of COVID-19 lockdown on flash and real-time glucose sensor users with type 1 diabetes in England. Acta Diabetol 2020:1–7. DOI: 10.007/s0592-020-016145. Crossref, Medline, Google Scholar7. Aragona M, Rodia C, Bertolotto A, et al.: Type 1 diabetes and COVID-19: the "lockdown effect." Diabetes Res Clin Pract 2020;170:108468. 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