After the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from China, Italy became the second most affected country. One of the first outbreaks started in the municipality of Vo’ in the Padua province of the Veneto region. The area was quarantined, and most residents with symptomatic coronavirus disease 2019 (COVID-19) were admitted to the Padua Hospital. Due to escalating numbers of cases, lockdown measures were imposed at a national level. Along with mass testing, such interventions helped with restraining SARS-CoV-2 diffusion (1). During lockdown, hospitals reorganized to care for COVID-19 patients. From 15 March 2020, outpatient visits were limited to nondeferrable ones, while other appointments were switched to telemedicine, postponed, or cancelled.

Diabetes is a key risk factor for severe COVID-19 (2), but the impact of lockdown on diabetes care is less appreciated. We analyzed the outpatient clinic database of the Padua Hospital, containing routine clinical data on demographics, anthropometrics, laboratory results, complications, and therapies. Patients had provided written informed consent for the reuse of anonymized data for research purposes. In agreement with national regulation, the local ethics committee (Padua, Italy) was notified of the protocol.

We first identified patients for whom a visit was available during lockdown from 15 March to 14 April 2020 and then identified patients seen in 2018 and 2019 in the same month to match for seasonal variations in access to the clinic. To account for year-to-year variations, we compared patients seen from 15 January–14 February in 2018, 2019, and 2020. We used a generalized estimating equation to compare clinical characteristics of patients seen during lockdown with characteristics of those attending the clinic in the same period of 2018–2019, adjusting for differences in the prelockdown period.

The number of visits (on-site or online) performed in the lockdown period was 47.7% lower than in the same month of the previous 2 years (660 vs. 1,208 and 1,316; P < 0.001), while no substantial reduction was observed in the prelockdown month. The reduction was significantly greater for type 2 diabetes (T2D) (−53%) than for type 1 diabetes (T1D) (−40%; P < 0.001). During lockdown, on-site visits had high priority due to emerging issues in diabetes management, glucose control, or complications, but most visits (82% for T2D and 95% for T1D) were performed via e-mail, telephone, and other media. Patients received remote consultations on health status, review of laboratory exams and imaging studies, and discussion of issues related to diabetes management including pharmacotherapies. The obliged online approach affected the patients’ ability to contact the clinic and attend the visit, particularly for those with T2D, who are older and arguably have less digital skills than patients with T1D. Patients with T2D assisted during lockdown as compared with those seen in previous years were significantly younger, had a shorter disease duration, and had a lower prevalence of microangiopathy and heart failure history, and they were not as often treated with metformin, sulfonylureas, glucagon-like peptide 1 receptor agonists (GLP-1RA), and antihypertensive, lipid-lowering, and antiplatelet medications (Table 1). As a mirror of these characteristics, we infer that aged T2D patients with a heavier complication burden and complex pharmacotherapies could not get in contact with the clinic for an on-site visit or remote consultation. This means that the toll of lockdown was paid by the most fragile patients, who needed more attention than others during limited functioning of many health care services.

Table 1

Clinical characteristics of patients with T2D assisted before and during lockdown

15 January–14 February15 March–14 April
2018–201920202018–20192020Effect on lockdown visit
Overall, % available(n = 1,527)(n = 739)P(n = 1,643)(n = 387)PEffect directionPinteraction
Demographics          
 Age, years 100 69.7 ± 12.1 70.2 ± 12.4 0.388 69.5 ± 12.1 68.0 ± 14.6 0.053 ↘ 0.029 
 Female sex 100 609 (39.9) 283 (38.3) 0.469 641 (39.0) 137 (35.4) 0.189  0.537 
 T2D  1,527 (100.0) 739 (100.0) — 1,643 (100.0) 387 (100.0) —  — 
 T1D  0 (0.0) 0 (0.0) — 0 (0.0) 0 (0.0) —  — 
 Diabetes duration, years 91 13.1 (6.2–18.1) 14.3 (7.5–20.1) 0.005 14.1 (7.5–19.3) 14.1 (6.3–19.2) 0.461 ↘ 0.021 
Anthropometrics          
 Weight, kg 98 80.6 ± 16.9 79.9 ± 16.3 0.348 80.6 ± 16.5 81.2 ± 18.4 0.564  0.308 
 BMI, kg/m2 96 28.8 ± 5.4 28.3 ± 5.1 0.042 28.8 ± 5.1 28.5 ± 5.6 0.509  0.541 
Other risk factor measures          
 SBP, mmHg 98 145.4 ± 21.8 147.5 ± 20.2 0.029 144.3 ± 21.6 144.8 ± 22.2 0.726  0.307 
 DBP, mmHg 98 78.2 ± 11.3 76.5 ± 11.9 0.003 77.9 ± 11.0 78.2 ± 11.0 0.672 ↗ 0.035 
 HbA1c, % (mmol/mol) 95 7.5 ± 1.3 (58 ± 10) 7.5 ± 1.2 (58 ± 9) 0.411 7.6 ± 1.3 (59 ± 10) 7.5 ± 1.3 (58 ± 10) 0.129  0.087 
 FPG, mg/dL 87 156.8 ± 55.2 153.1 ± 47.0 0.143 158.7 ± 52.4 156.7 ± 58.6 0.612  0.689 
 Total cholesterol, mg/dL 91 163.6 ± 39.0 158.2 ± 37.2 0.004 163.3 ± 38.9 156.5 ± 38.0 0.007  0.658 
 HDL cholesterol, mg/dL 89 49.7 ± 14.2 49.9 ± 13.4 0.836 50.1 ± 14.6 48.9 ± 13.1 0.160  0.221 
 Triglycerides, mg/dL 91 131.6 ± 109.0 131.9 ± 74.8 0.945 131.2 ± 83.1 130.9 ± 74.5 0.945  0.924 
 LDL cholesterol, mg/dL 88 87.7 ± 31.7 82.1 ± 30.8 0.000 87.1 ± 31.7 80.4 ± 31.1 0.002  0.627 
Renal function          
 Creatinine, mg/dL 93 1.0 ± 0.6 1.1 ± 0.7 0.080 1.1 ± 0.8 1.1 ± 0.8 0.593  0.342 
 eGFR, mL/min/1.73 m2 93 74.8 ± 22.4 72.6 ± 22.7 0.048 73.5 ± 23.7 73.0 ± 24.1 0.731  0.323 
 Normoalbuminuria 79 729 (64.1) 364 (65.1) 0.669 783 (62.6) 156 (61.4) 0.725  0.755 
 Microalbuminuria 79 307 (27.0) 148 (26.5) 0.827 346 (27.7) 75 (29.5) 0.545  0.727 
 Macroalbuminuria 79 102 (9.0) 47 (8.4) 0.704 122 (9.8) 23 (9.1) 0.732  0.970 
Complications          
 Nephropathy 100 593 (38.8) 293 (39.6) 0.710 682 (41.5) 149 (38.5) 0.279  0.262 
 CKD stage III 93 316 (25.7) 183 (29.0) 0.133 398 (27.8) 97 (30.7) 0.307  0.881 
 Retinopathy 70 327 (32.9) 162 (32.0) 0.712 353 (32.0) 59 (27.3) 0.175  0.370 
 Neuropathy 29 174 (49.2) 111 (51.6) 0.567 236 (49.0) 46 (47.4) 0.782  0.569 
 MACE 100 204 (13.4) 114 (15.4) 0.185 226 (13.8) 45 (11.6) 0.269  0.061 
 PAD and foot disease 100 118 (7.7) 58 (7.8) 0.920 122 (7.4) 21 (5.4) 0.169  0.244 
 Heart failure 100 29 (1.9) 20 (2.7) 0.218 39 (2.4) 8 (2.1) 0.719 ↘ 0.022 
 Carotid atherosclerosis 100 625 (40.9) 311 (42.1) 0.601 683 (41.6) 138 (35.7) 0.033 ↘ 0.043 
 Any macroangiopathy 100 692 (45.3) 351 (47.5) 0.329 750 (45.6) 144 (37.2) 0.003 ↘ 0.003 
 Any microangiopathy 91 790 (60.9) 395 (61.6) 0.762 907 (63.0) 187 (60.1) 0.338  0.630 
Diabetes medications 100 1,415 (92.7) 711 (96.2) 0.001 1,534 (93.4) 362 (93.5) 0.901 ↘ 0.030 
 Any insulin 100 620 (40.6) 292 (39.5) 0.620 782 (47.6) 175 (45.2) 0.400  0.743 
 Basal-bolus insulin 100 387 (25.3) 157 (21.2) 0.033 490 (29.8) 95 (24.5) 0.040  0.840 
 Metformin 100 977 (64.0) 523 (70.8) 0.001 1,014 (61.7) 240 (62.0) 0.913 ↘ 0.039 
 Secretagogues 100 247 (16.2) 129 (17.5) 0.443 307 (18.7) 51 (13.2) 0.011 ↘ 0.012 
 Pioglitazone 100 30 (2.0) 13 (1.8) 0.737 36 (2.2) 5 (1.3) 0.264  0.544 
 DPP-4 inhibitors 100 368 (24.1) 182 (24.6) 0.783 369 (22.5) 84 (21.7) 0.749  0.652 
 GLP-1RA 100 131 (8.6) 142 (19.2) <0.001 153 (9.3) 52 (13.4) 0.016 ↘ 0.013 
 SGLT2 inhibitors 100 105 (6.9) 84 (11.4) <0.001 89 (5.4) 28 (7.2) 0.169  0.355 
Other medications          
 Antihypertensive 100 1,225 (80.2) 610 (82.5) 0.187 1,330 (80.9) 291 (75.2) 0.011 ↘ 0.004 
 ACEi/ARB 100 1,007 (65.9) 495 (67.0) 0.625 1,055 (64.2) 233 (60.2) 0.142  0.129 
 Lipid lowering 100 1,082 (70.9) 540 (73.1) 0.274 1,148 (69.9) 255 (65.9) 0.128 ↘ 0.049 
 Statin 100 997 (65.3) 506 (68.5) 0.134 1,068 (65.0) 242 (62.5) 0.361  0.080 
 Antiplatelet 100 810 (53.0) 389 (52.6) 0.856 827 (50.3) 166 (42.9) 0.009 ↘ 0.043 
 Diuretics 100 717 (47.0) 360 (48.7) 0.432 759 (46.2) 162 (41.9) 0.124  0.078 
 β-Blockers 100 534 (35.0) 279 (37.8) 0.196 598 (36.4) 133 (34.4) 0.454  0.152 
 Anticoagulants 100 152 (10.0) 79 (10.7) 0.587 178 (10.8) 54 (14.0) 0.084  0.320 
15 January–14 February15 March–14 April
2018–201920202018–20192020Effect on lockdown visit
Overall, % available(n = 1,527)(n = 739)P(n = 1,643)(n = 387)PEffect directionPinteraction
Demographics          
 Age, years 100 69.7 ± 12.1 70.2 ± 12.4 0.388 69.5 ± 12.1 68.0 ± 14.6 0.053 ↘ 0.029 
 Female sex 100 609 (39.9) 283 (38.3) 0.469 641 (39.0) 137 (35.4) 0.189  0.537 
 T2D  1,527 (100.0) 739 (100.0) — 1,643 (100.0) 387 (100.0) —  — 
 T1D  0 (0.0) 0 (0.0) — 0 (0.0) 0 (0.0) —  — 
 Diabetes duration, years 91 13.1 (6.2–18.1) 14.3 (7.5–20.1) 0.005 14.1 (7.5–19.3) 14.1 (6.3–19.2) 0.461 ↘ 0.021 
Anthropometrics          
 Weight, kg 98 80.6 ± 16.9 79.9 ± 16.3 0.348 80.6 ± 16.5 81.2 ± 18.4 0.564  0.308 
 BMI, kg/m2 96 28.8 ± 5.4 28.3 ± 5.1 0.042 28.8 ± 5.1 28.5 ± 5.6 0.509  0.541 
Other risk factor measures          
 SBP, mmHg 98 145.4 ± 21.8 147.5 ± 20.2 0.029 144.3 ± 21.6 144.8 ± 22.2 0.726  0.307 
 DBP, mmHg 98 78.2 ± 11.3 76.5 ± 11.9 0.003 77.9 ± 11.0 78.2 ± 11.0 0.672 ↗ 0.035 
 HbA1c, % (mmol/mol) 95 7.5 ± 1.3 (58 ± 10) 7.5 ± 1.2 (58 ± 9) 0.411 7.6 ± 1.3 (59 ± 10) 7.5 ± 1.3 (58 ± 10) 0.129  0.087 
 FPG, mg/dL 87 156.8 ± 55.2 153.1 ± 47.0 0.143 158.7 ± 52.4 156.7 ± 58.6 0.612  0.689 
 Total cholesterol, mg/dL 91 163.6 ± 39.0 158.2 ± 37.2 0.004 163.3 ± 38.9 156.5 ± 38.0 0.007  0.658 
 HDL cholesterol, mg/dL 89 49.7 ± 14.2 49.9 ± 13.4 0.836 50.1 ± 14.6 48.9 ± 13.1 0.160  0.221 
 Triglycerides, mg/dL 91 131.6 ± 109.0 131.9 ± 74.8 0.945 131.2 ± 83.1 130.9 ± 74.5 0.945  0.924 
 LDL cholesterol, mg/dL 88 87.7 ± 31.7 82.1 ± 30.8 0.000 87.1 ± 31.7 80.4 ± 31.1 0.002  0.627 
Renal function          
 Creatinine, mg/dL 93 1.0 ± 0.6 1.1 ± 0.7 0.080 1.1 ± 0.8 1.1 ± 0.8 0.593  0.342 
 eGFR, mL/min/1.73 m2 93 74.8 ± 22.4 72.6 ± 22.7 0.048 73.5 ± 23.7 73.0 ± 24.1 0.731  0.323 
 Normoalbuminuria 79 729 (64.1) 364 (65.1) 0.669 783 (62.6) 156 (61.4) 0.725  0.755 
 Microalbuminuria 79 307 (27.0) 148 (26.5) 0.827 346 (27.7) 75 (29.5) 0.545  0.727 
 Macroalbuminuria 79 102 (9.0) 47 (8.4) 0.704 122 (9.8) 23 (9.1) 0.732  0.970 
Complications          
 Nephropathy 100 593 (38.8) 293 (39.6) 0.710 682 (41.5) 149 (38.5) 0.279  0.262 
 CKD stage III 93 316 (25.7) 183 (29.0) 0.133 398 (27.8) 97 (30.7) 0.307  0.881 
 Retinopathy 70 327 (32.9) 162 (32.0) 0.712 353 (32.0) 59 (27.3) 0.175  0.370 
 Neuropathy 29 174 (49.2) 111 (51.6) 0.567 236 (49.0) 46 (47.4) 0.782  0.569 
 MACE 100 204 (13.4) 114 (15.4) 0.185 226 (13.8) 45 (11.6) 0.269  0.061 
 PAD and foot disease 100 118 (7.7) 58 (7.8) 0.920 122 (7.4) 21 (5.4) 0.169  0.244 
 Heart failure 100 29 (1.9) 20 (2.7) 0.218 39 (2.4) 8 (2.1) 0.719 ↘ 0.022 
 Carotid atherosclerosis 100 625 (40.9) 311 (42.1) 0.601 683 (41.6) 138 (35.7) 0.033 ↘ 0.043 
 Any macroangiopathy 100 692 (45.3) 351 (47.5) 0.329 750 (45.6) 144 (37.2) 0.003 ↘ 0.003 
 Any microangiopathy 91 790 (60.9) 395 (61.6) 0.762 907 (63.0) 187 (60.1) 0.338  0.630 
Diabetes medications 100 1,415 (92.7) 711 (96.2) 0.001 1,534 (93.4) 362 (93.5) 0.901 ↘ 0.030 
 Any insulin 100 620 (40.6) 292 (39.5) 0.620 782 (47.6) 175 (45.2) 0.400  0.743 
 Basal-bolus insulin 100 387 (25.3) 157 (21.2) 0.033 490 (29.8) 95 (24.5) 0.040  0.840 
 Metformin 100 977 (64.0) 523 (70.8) 0.001 1,014 (61.7) 240 (62.0) 0.913 ↘ 0.039 
 Secretagogues 100 247 (16.2) 129 (17.5) 0.443 307 (18.7) 51 (13.2) 0.011 ↘ 0.012 
 Pioglitazone 100 30 (2.0) 13 (1.8) 0.737 36 (2.2) 5 (1.3) 0.264  0.544 
 DPP-4 inhibitors 100 368 (24.1) 182 (24.6) 0.783 369 (22.5) 84 (21.7) 0.749  0.652 
 GLP-1RA 100 131 (8.6) 142 (19.2) <0.001 153 (9.3) 52 (13.4) 0.016 ↘ 0.013 
 SGLT2 inhibitors 100 105 (6.9) 84 (11.4) <0.001 89 (5.4) 28 (7.2) 0.169  0.355 
Other medications          
 Antihypertensive 100 1,225 (80.2) 610 (82.5) 0.187 1,330 (80.9) 291 (75.2) 0.011 ↘ 0.004 
 ACEi/ARB 100 1,007 (65.9) 495 (67.0) 0.625 1,055 (64.2) 233 (60.2) 0.142  0.129 
 Lipid lowering 100 1,082 (70.9) 540 (73.1) 0.274 1,148 (69.9) 255 (65.9) 0.128 ↘ 0.049 
 Statin 100 997 (65.3) 506 (68.5) 0.134 1,068 (65.0) 242 (62.5) 0.361  0.080 
 Antiplatelet 100 810 (53.0) 389 (52.6) 0.856 827 (50.3) 166 (42.9) 0.009 ↘ 0.043 
 Diuretics 100 717 (47.0) 360 (48.7) 0.432 759 (46.2) 162 (41.9) 0.124  0.078 
 β-Blockers 100 534 (35.0) 279 (37.8) 0.196 598 (36.4) 133 (34.4) 0.454  0.152 
 Anticoagulants 100 152 (10.0) 79 (10.7) 0.587 178 (10.8) 54 (14.0) 0.084  0.320 

Data are means ± SD or n (%) unless otherwise indicated. We show data for patients who attended the outpatient clinic physically or by remote contact in 2018–2019 and in 2020 during the month from 15 January to 14 February (prelockdown control) and during one lockdown month (from 15 March to 14 April). Effect direction: ↘, higher (or positive) value associated with less probability of visits during lockdown; ↗ higher (or positive) value associated with higher probability of visits during lockdown. ACEi, ACE inhibitors; ARB, angiotensin receptor blockers; CKD, chronic kidney disease; DBP, diastolic blood pressure; eGFR, estimated glomerular filtration rate; DPP-4, dipeptidyl peptidase 4; FPG, fasting plasma glucose; MACE, major adverse cardiovascular events; PAD, peripheral arterial disease; SBP, systolic blood pressure; SGLT2, sodium–glucose cotransporter 2.

Worryingly, the increase in the prescription of GLP-1RA observed prior to lockdown was significantly halted for T2D patients assisted during lockdown. Along with the reduced use of antiplatelet agents and lipid-lowering therapies, this suggests a less appropriate management of cardiovascular risk. During lockdown, emergency accesses for cardiovascular events dropped all over the world (3). In this unprecedented situation, patients with an event did not seek care, thereby posing themselves at increased risk of death or adverse sequelae, such as heart failure. Thus, treatment of patients with drugs that prevent fatal and nonfatal cardiovascular events and heart failure becomes even more important.

No significant difference was noted in the characteristics of patients with T1D attending the clinic during lockdown compared with 2018–2019, suggesting no specific issues in the management of these patients during lockdown. The frequent use of cloud-connected sensors allowed people with T1D to seek advice outside the scheduled visits (4,5). Not all people with T1D may be exempt from the adverse consequences of lockdown, but they are probably more resilient to such challenge, possibly thanks to the widespread use of technology.

Preparing for the next pandemic phase, we should develop strategies that prevent the decrease in care for people with T2D, giving priority to allowing access to those who most need assistance.

This article is part of a special article collection available at https://care.diabetesjournals.org/collection/diabetes-and-COVID19.

B.M.B. and M.L.M. equally contributed.

Funding. This work was supported by the University of Padova Department of Medicine (CARIPARO grant, COVIDIMED project).

Duality of Interest. No potential conflicts of interest relevant to this article were reported.

Author Contributions. B.M.B. contributed to study design, data analysis and interpretation, and manuscript writing. M.L.M. contributed to study design, data analysis and interpretation, and manuscript writing. A.A. contributed to study design and supervision and manuscript revision. G.P.F. contributed to study design and interpretation and manuscript writing. All authors approved the final version of the manuscript. G.P.F. and M.L.M. are the guarantors of this work and, as such, had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

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