RESULTS: Among 18 998 insulin users (47% women, mean ± SD age 59.2 ± 11.7 years, diabetes duration 13.2 ± 8.3 years, glycated haemoglobin [HbA1c] 72 ± 21.4 mmol/mol [8.74 ± 1.95%], median total daily insulin dose [TDD] 0.27-0.82 units/kg), 25% and 29.5% had YOD and DKD, respectively. Premixed (44%) and basal-only (42%) insulin were the most common regimens. Despite being more commonly treated with these two regimens with higher insulin dosages, patients with YOD had worse HbA1c levels than their late-onset peers (73 ± 20.5 vs. 71 ± 21.2 mmol/mol [8.82 ± 1.87% vs. 8.66 ± 1.94%]; P
DESIGN: A cross-sectional facility-based survey.
SETTING: Hospitals around the country with different levels of care.
PARTICIPANTS: A total of 1795 respondents, including 360 men and 1435 women who participated in the survey.
PRIMARY OUTCOME MEASURES: Burnout was assessed using the Physician Work Life Study. A score of ≥3 implied burnout.
RESULTS: Of the 1795 respondents, 723 (40.3%) reported burnout, and 669 (37.3%) cared for patients with COVID-19. Anxiety levels were mild in 185 (10.3%) respondents, moderate in 209 (11.6%) and severe in 1401 (78.1%). The mean Center for Epidemiologic Studies Depression Scale-10 score was 9.5±6.3, and 817 (45.5%) respondents were classified as having depression. Factors associated with burnout were working in acute and critical care (ACC) divisions (adjusted OR (aOR)=1.84, 95% CI 1.20 to 3.39, p=0.019), caring for patients with COVID-19 (aOR=3.90, 95% CI 1.14 to 13.37, p=0.031) and having depressive disorder (aOR=9.44, 95% CI 7.44 to 11.97, p<0.001).
CONCLUSIONS: Physicians and nurses are vulnerable to burnout during a pandemic, especially those working in ACC divisions. Anxiety disorder, depressive disorder and care of patients with COVID-19 may be factors that influence the occurrence of burnout among healthcare providers.
METHODOLOGY: A cross-sectional observational study was performed on patients diagnosed with MetS and compared to normal controls. All patients underwent ophthalmic and anthropometric examination, serological and biochemical blood investigations; and ocular imaging using spectral-domain optical coherence tomography. Patients with ocular pathology were excluded. Unpaired t-test was used to compare mean thickness between the two groups. One-way ANOVA with Bonferroni correction for multiple comparisons was used to compare mean thickness between different tertiles of MetS parameters, and a generalized estimating equation was used to correct for inter-eye correlation and to assess association between mean thickness and covariates.
RESULTS: Two hundred and forty-eight eyes from 124 participants (1:1 ratio of MetS patients to controls) were included. Age ranged between 30 to 50 years old, and mean age was 40 ± 6.6 years. RNFL thickness was lower globally (93.6 ± 9.9 μm vs 99.0 ± 9.3, p<0.001) and in the inferior (124.5 ± 17.5 μm vs 131.0 ± 16.4 μm, p = 0.002), superior (117.2 ± 16.0 μm vs 126.3 ± 14.4 μm, p<0.001) and temporal (65.5 ± 10.2 μm vs 69.5 ± 9.8, p = 0.002) sectors in MetS patients compared to controls. Only the central (237.0 ± 14.0 μm vs 243.6 ± 18.0 μm, p = 0.002) and inferior parafoveal (307.8 ± 20.9 vs 314.6 ± 14.6, p = 0.004) area of the macula was significantly thinner. The inferior RNFL sector had the most difference (mean difference = 9.1 μm). The Generalized Estimating Equation found that, after adjusting for age, diastolic blood pressure, BMI, HDL and obesity; the number of MetS components and elevated triglyceride levels were independent risk factors for reduced thickness in global RNFL (β = -4.4, 95% CI = -7.29 to -1.5, p = 0.003) and inferior parafovea (β = -6.85, 95% CI = -11.58 to -2.13, p = 0.004) thickness respectively.
CONCLUSION: RNFL thinning was seen more than macula thinning in MetS patients, suggesting RNFL susceptibility to neurodegeneration than the macula. A higher number of metabolic components and elevated triglyceride levels were independent risk factors for retinal thinning in this group of patients.