OBJECTIVE: To evaluate the association between changes in haemoglobin A1c (HbA1c) and the concurrent incidence of cardiovascular disease (CVD) in type 2 diabetes mellitus (T2DM) patients.
METHODS: We conducted a retrospective cohort study among T2DM patients with HbA1c measurement after T2DM diagnosis between August 2009 and September 2010. The patients were classified into six subgroups based on baseline HbA1c (<7%; 7%-7.9%; ≥8%) and age (<65; ≥65 years), and then clustered into classes by HbA1c trajectory and CVD incidence over the 12-year follow-up period using joint latent class mixture models. We explored the HbA1c trajectories and CVD incidences in each latent class. Multinomial logistic regression was used to compare the baseline characteristics among different latent classes.
RESULTS: A total of 128 843 T2DM patients were included with a median follow-up period of 11.7 years. Ten latent classes were identified in patients with baseline HbA1c ≥ 8% and age <65 years, while seven classes were identified in the other five groups. Among all the identified latent classes, patients with fluctuating HbA1c trajectories, characterized by alternating periods of increase and decrease, had higher CVD incidences. Male patients, and patients with higher baseline HbA1c and use of antidiabetic drugs were more likely to have a fluctuating HbA1c trajectory. More specifically, patients aged < 65 years with younger age or a smoking habit, and patients aged ≥ 65 years with a longer duration of T2DM were more likely to have a fluctuating HbA1c trajectory.
CONCLUSIONS: We found that T2DM patients with fluctuating HbA1c trajectories could have a higher CVD risk. Different trajectory-associated characteristics in age subgroups highlight the need for individualized management of T2DM patients.

OBJECTIVE: This retrospective observational study aimed to comprehensively analyse the clinical profile and treatment modalities of patients diagnosed with type 2 diabetes mellitus (T2DM) who were treated at a tertiary care centre.
METHODS: The study included a cohort of 300 individuals who sought medical care at the hospital from January 2023 to January 2024. The analysis primarily examined parameters such as the mean number of anti-diabetic medications per prescription, the proportion of various categories of anti-diabetic medications prescribed, the predominant class and type of anti-diabetic medications prescribed, and the proportion of anti-diabetic medications prescribed from the essential drug lists.
RESULTS: The age distribution demonstrated that 52.0% of participants were above 60 years old, showcasing a substantial elderly representation. Gender distribution emphasized a male predominance at 65.0%, highlighting potential gender-specific implications in type II diabetes. The blood profile analysis of patients with T2DM revealed a range of values for key parameters. Fasting blood glucose levels ranged from a minimum of 101 mg/dL to a maximum of 359 mg/dL, with a mean of 180.01 mg/dl. The comprehensive analysis of anti-diabetic drug utilization, based on the total number of units prescribed, sheds light on the diverse treatment approaches employed for managing diabetes mellitus (DM). Insulin, comprising 31.3% of the total units, plays a pivotal role in glycemic control, with both regular and biphasic formulations contributing significantly at 26.3% and 9.3%, respectively. Among the 300 patients, the overall utilization of anti-diabetic drugs reveals that 38.7% of individuals are using a combination of insulin with oral anti-diabetic drugs, while 61.3% are relying on oral anti-diabetic drugs alone. The most frequently prescribed drug combinations for diabetes management include sulphonylurea with biguanides, emerging as the most prevalent combination with 22 occurrences.
CONCLUSIONS: The study\'s findings contribute valuable insights into the socio-demographic profiles and anti-diabetic drug utilization patterns among diabetes patients.

OBJECTIVE: To examine cross-sectional associations between continuous glucose monitoring (CGM)-derived metrics and cerebral small vessel disease (SVD) in older adults with type 2 diabetes.
METHODS: In total, 80 patients with type 2 diabetes aged ≥70 years were analysed. Participants underwent CGM for 14 days. From the CGM data, we derived mean sensor glucose, percentage glucose coefficient of variation, mean amplitude of glucose excursion, time in range (TIR, 70-180 mg/dl), time above range (TAR) and time below range metrics, glycaemia risk index and high/low blood glucose index. The presence of cerebral SVD, including lacunes, microbleeds, enlarged perivascular spaces and white matter hyperintensities, was assessed, and the total number of these findings comprised the total cerebral SVD score (0-4). Ordinal logistic regression analyses were performed to examine the association of CGM-derived metrics with the total SVD score.
RESULTS: The median SVD score was 1 (interquartile range 0-2). Higher hyperglycaemic metrics, including mean sensor glucose, TAR >180 mg/dl, TAR >250 mg/dl, and high blood glucose index and glycaemia risk index, were associated with a higher total SVD score. In contrast, a higher TIR (per 10% increase) was associated with a lower total SVD score (odds ratio 0.73, 95% confidence interval 0.56-0.95). Glycated haemoglobin, percentage glucose coefficient of variation, mean amplitude of glucose excursions, time below range and low blood glucose index were not associated with total cerebral SVD scores.
CONCLUSIONS: The hyperglycaemia metrics and TIR, derived from CGM, were associated with cerebral SVD in older adults with type 2 diabetes.

Pre-diabetes (pre-DM) is a strong predictor of diabetes (DM) over time. This study investigated how much of the recent increase in pre-DM identified among Alaska Native (AN) peoples living in urban southcentral Alaska may be due to changes in diagnostic methods. We used clinical and demographic data collected at baseline between 2004 and 2006 and at follow-up collected between 2015 and 2017 from the urban southcentral Alaska Education and Research Towards Health (EARTH) cohort. We used descriptive statistics and logistic regression to explore differences in demographic and clinical variables among the identified pre-DM groups. Of 388 participants in the follow-up study, 243 had A1c levels indicating pre-DM with only 20 demonstrating pre-DM also by fasting blood glucose (FBG). Current smoking was the sole predictor for pre-DM by A1c alone while abdominal obesity and elevated FBG-predicted pre-DM by A1c+FBG. No participants had an elevated FBG without an A1c elevation. A substantial portion of the rise in pre-DM found among urban southcentral AN peoples in the EARTH follow-up study was due to the addition of A1c testing. Pre-DM by A1c alone should be used to motivate behavioural changes that address modifiable risk factors, including smoking cessation, physical activity and weight management.

UNASSIGNED: The aim of this study was to assess the relationship between haemoglobin A1c (HbA1c) values and operative wound infection.
UNASSIGNED: During the period from 2013-2016, consecutive patients with type 2 diabetes were prospectively evaluated. Data were retrospectively analysed. All included patients were admitted for an elective surgical procedure, requiring the use of prosthetic graft in a groin wound. The patients were divided into two groups according to their preoperative HbA1c values. The main outcome was groin wound infection. The association between preoperative long-term glycoregulation and wound infection was evaluated, as well as the impact of postoperative glycaemic values, regardless of the level of HbA1c.
UNASSIGNED: Of the 93 participating patients, wound infection occurred in 20 (21.5%). Wound infection occurred in 28.2% of patients with uncontrolled diabetes (HbA1c >7%) and 16.7% of patients with controlled diabetes (HbA1c <7%); however, the difference did not reach statistical significance (p=0.181). In regression modelling, operative time (p=0.042) was a significant predictor of wound infection, while patients\' age (p=0.056) was on the borderline of statistical significance. Females had a higher probability for wound infection (odds ratio (OR): 1.739; 95% confidence interval (CI):0.483-6.265), but there was no statistical significance (p=0.397). Patients with elevated levels of HbA1c had a higher chance of wound infection compared with patients with controlled diabetes (OR: 2.243; 95% CI: 0.749-6.716), nevertheless, this was not statistically significant (p=0.149).
UNASSIGNED: We found no statistically significant correlation between elevated values of preoperative HbA1c and postoperative groin wound infection.

OBJECTIVE: Rising prevalence of obesity has led to increased rates of prediabetes and diabetes mellitus (DM) in children. This study compares rates of prediabetes and diabetes using two recommended screening tests (fasting plasma glucose [FPG] and haemoglobin A1c [HbA1c]).
METHODS: Data were collected prospectively from 37 multi-component paediatric weight management programs in POWER (Paediatric Obesity Weight Evaluation Registry).
RESULTS: For this study, 3962 children with obesity without a known diagnosis of DM at presentation and for whom concurrent measurement of FPG and HbA1c were available were evaluated (median age 12.0 years [interquartile range, IQR 9.8, 14.6]; 48% males; median body mass index 95th percentile [%BMIp95] 134% [IQR 120, 151]). Notably, 10.7% had prediabetes based on FPG criteria (100-125 mg/dL), 18.6% had prediabetes based on HbA1c criteria (5.7%-6.4%), 0.9% had DM by FPG abnormality (≥126 mg/dL) and 1.1% had DM by HbA1c abnormality (≥6.5%). Discordance between the tests was observed for youth in both age groups (10-18 years [n = 2915] and age 2-9 years [n = 1047]).
CONCLUSIONS: There is discordance between FPG and HbA1c for the diagnosis of prediabetes and DM in youth with obesity. Further studies are needed to understand the predictive capability of these tests for development of DM (in those diagnosed with prediabetes) and cardiometabolic risk.

Background: The coronavirus disease 2019 (COVID-19) pandemic was associated with an increased incidence of mucormycosis globally. However, the clinical pattern, epidemiologic features and risk factors for adverse outcomes are not well established. Methods: We performed a retrospective analysis of the data from patients hospitalized with proven mucormycosis between April 2021 and August 2021. Patients were managed with a multi-disciplinary approach involving medical, surgical, and comorbidity treatment. The clinical presentation, management details, complications and outcomes, including mortality, were reviewed from clinical records. Results: The mean age of presentation was 53.7 (± 11.8) years, and 88 (84.6%) were men. Of the 104 cases with COVID-19-associated mucormycosis, 97 (93.27%) patients had diabetes, and 80.8% had a haemoglobin A1C (HbA1c) of ≥6.4% at diagnosis. Seventy percent of diabetes cases experienced steroid-induced hyperglycaemia during treatment. Even with appropriate treatment, 17 (16.35%) patients died. High HbA1c and creatinine levels, presence of chronic kidney disease (CKD), need for intensive care unit admission, and orbital evisceration were the risk factors associated with high mortality on multivariate logistic regression analysis. Cox regression analysis revealed that the overall mortality increased by a factor of 12% with each 1 percentage point increase in HbA1c ≥6.4% (hazard ratio 1.12; 95% confidence interval 0.95- 1.31). The mortality risk was even higher when diabetes was associated with CKD (hazard ratio 1.82; 95% confidence interval 0.24-14.00). Conclusion: High HbA1c and creatinine levels, intensive care unit admission, CKD, and aggressive disease requiring orbital evisceration are the predictors of mortality in patients with COVID-19-associated mucormycosis. Patients with these risk factors should be managed more actively to reduce morbidity and mortality.

OBJECTIVE: Over the past decades, glycosylated haemoglobin (HbA1c) has been a gold standard for monitoring diabetes control over a long period, relative to blood glucose level (BGL) which measures short-term results. It is speculated that anaemia and factors that induce haemolysis may cause falsely elevated HbA1c leading to \'false positive\' interpretations. This study aimed to investigate how anaemia impacts HbA1c.
METHODS: This was a pathology-based observational pilot study using archived data of diabetic subjects monitored with both BGL and HbA1c in regional New South Wales (NSW), Australia. A total of 28,487 cases of blood glucose results were pooled and those with HbA1c and anaemia results were evaluated for correlation with the BGL results. Data collection was limited to de-identified information from the laboratory information system, hence details on the ethnicity and medical history were unavailable. Descriptive frequencies and Pearson correlations were performed.
RESULTS: In the pooled data, 53.36% of individuals were females, and 50.54% had BGL ≥5.6 mmol/L. In the pilot dataset, the majority (64.86%) were males, 18.92% with BGL ≤5.6 mmol/L and 67.57% had HbA1c (≥6.5%). In the entire dataset, BGL was moderately and positively correlated with HbA1c (r = 0.6), whereas in the subset of individuals with normo-BGL and anaemia, the correlation was negative (r = -0.2).
CONCLUSIONS: This pilot investigation observed a pertinent issue, which is a negative correlation between glycaemia and HbA1c in patients with anaemia. HbA1c was falsely increased despite normal blood glucose levels in individuals with anaemia. This advances the speculation that anaemia falsely increases HbA1c. Therefore, caution is necessary while interpreting HbA1c results for patients with anaemia, and new methods for interpretation are required.

BACKGROUND: Women are on average diagnosed with diabetes mellitus at later age than men but have higher mortality. As the diagnosis of diabetes mellitus is primarily based on HbA1c, the use of a non-specific reference range and cut point for diabetes mellitus that does not account for gender differences in diabetes could potentially lead to underdiagnosis of diabetes mellitus in women and missed opportunities for intervention. We investigated whether a contributing factor to the later diagnosis in women may be a difference in distribution of HbA1c in premenopausal women versus men of the same age by comparing HbA1c values in men and women across multiple sites in the UK.
METHODS: We analysed the HbA1c levels of 146,907 individuals who underwent single testing only and had HbA1c ≤ 50 mmol/mol between 2012 and 2019 in one laboratory (cohort 1). This was replicated in six laboratories with 938,678 individuals tested between 2019 and 2021 (cohort 2).
RESULTS: In cohort 1, women < 50 years old had an HbA1c distribution markedly lower than that in men by a mean of 1.6 mmol/mol (p < 0.0001), while the difference in the distribution of HbA1c for individuals aged ≥ 50 years was less pronounced (mean difference 0.9 mmol/mol, p < 0.0001). For individuals under the age of 50, HbA1c in women lagged by up to 10 years compared to men. Similar findings were found in cohort 2. We estimated an additional 17% (n = 34,953) of undiagnosed women aged < 50 years in England and Wales could be reclassified to have diabetes mellitus, which may contribute to up to 64% of the difference in mortality rates between men/women with diabetes mellitus aged 16-50 years.
CONCLUSIONS: The HbA1c cut point for diagnosis of diabetes mellitus may need to be re-evaluated in women under the age of 50 years. Early identification of diabetes mellitus in women has the potential to improve women\'s health outcomes in the longer term.

Type 2 diabetes mellitus (T2DM) is a disease of public health importance globally with an increasing burden of undiagnosed pre-diabetes and diabetes in low- and middle-income countries, Nigeria in particular. Pre-diabetes and diabetes are established risk factors for cardiovascular complications. However, data are scanty on the current prevalence of these conditions in Nigeria, based on haemoglobin A1c (HbA1c) diagnosis as recommended by the WHO in 2009. We aimed to determine the prevalence of pre-diabetes, diabetes, and undiagnosed diabetes among the adult population of Nigeria using HbA1c.
A cross-sectional, multi-site population study was carried out in selected states in Nigeria (namely, Ekiti, Lagos, Osun, Oyo, and Kwara states) involving 2,708 adults (≥18 years) in rural and urban community dwellers, without prior diagnosis of pre-diabetes or diabetes. Participants with ongoing acute or debilitating illnesses were excluded. Data were collected using an interviewer-administered pretested, semi-structured questionnaire. Socio-demographic, clinical (weight, height, blood pressure, etc.), and laboratory characteristics of participants including HbA1c were obtained. Data were analysed using STATA version 16.
The mean age of participants was 48.1 ± 15.8 years, and 65.5% were female. The overall prevalence of pre-diabetes and undiagnosed diabetes was 40.5% and 10.7%, respectively, while the prevalence of high blood pressure was 36.7%. The prevalence of pre-diabetes was the highest in Lagos (48.1%) and the lowest in Ekiti (36.7%), while the prevalence of diabetes was the highest in Kwara (14.2%) and the lowest in Ekiti (10%). There was a significant association between age of the participants (p< 0.001), gender (p = 0.009), educational status (p = 0.008), occupation (p< 0.001), tribe (p = 0.004), marital status (p< 0.001), blood pressure (p< 0.001), and their diabetic or pre-diabetic status. Independent predictors of diabetes and pre-diabetes include excess weight gain, sedentary living, and ageing. Participants within the age group 45-54 years had the highest total prevalence (26.6%) of pre-diabetes and diabetes.
Over half of the respondents had pre-diabetes and diabetes, with a high prevalence of undiagnosed diabetes. A nationwide screening campaign will promote early detection of pre-diabetes and undiagnosed diabetes among adult Nigerians. Health education campaigns could be an effective tool in community settings to improve knowledge of the risk factors for diabetes to reduce the prevalence of dysglycaemia.