Seasonal variation in hemoglobin a1c in korean patients with type 2 diabetes mellitus

A Tailored Intervention for Improving Diabetes Self-care Among Adults With Visual Impairment: A Pilot Study

OBJECTIVES

Our aim in this study was to develop and evaluate a tailored intervention for improving diabetes self-care among people with visual impairment (TID-VI) in South Korea.

METHODS

The TID-VI program was designed around the barriers, resources, and perceptual factors to promote diabetes self-care in those with visual impairment (VI). A single-arm pilot study was conducted to evaluate the feasibility and preliminary effects of the intervention. Diabetes self-efficacy, self-care behaviours, depression, health-related quality of life, and clinical outcomes (fasting blood glucose, glycated hemoglobin [A1C], lipids, and blood pressure) were measured before, and up to 2 months after the 12-week intervention.

RESULTS

All 14 participants completed TID-VI. Diabetes self-efficacy, diabetes self-care behaviours, depression, and health-related quality of life showed improvement from baseline that was sustained at 2 months. Although high- and low-density lipoprotein also improved, there were no differences in blood glucose, A1C, total cholesterol, or blood pressure at 2 months.

CONCLUSIONS

A theory-driven, tailored intervention specific to the needs of adults with VI can produce substantial improvements in patient-reported quality of life and health status outcomes, although the benefits are yet to be confirmed in a controlled study.

Seasonal variation of HbA1c levels in diabetic and non-diabetic patients

Background

Hemoglobin A1c (HbA1c) serves as a pivotal marker for long-term glycemic control. The Diabetes Control and Complications Trial (DCCT) established its relevance, yet gaps exist in understanding potential seasonal variations in HbA1c levels among diabetic patients. The study highlights the need to explore potential seasonal variations in HbA1c levels and their impact on diabetic patients.

Materials and methods

This is an observational study conducted in a tertiary care hospital from January to December 2019, the study analyzed HbA1c levels in 8138 patients. Blood samples were collected using Potassium EDTA-containing vials and processed with an automated analyzer. Seasonal variations were explored using time series analysis.

Results

Mean HbA1c levels peaked during the monsoon (June to September) and were lowest in autumn (October to November). Subgroup analysis revealed differences in patients with HbA1c values below and above 6.5 %. Those with controlled blood sugar showed higher levels in winter (December to February) and monsoon (June to September), while patients with HbA1c values ≥ 6.5 % exhibited significantly lower levels in monsoon (June to September) and autumn (October to November) compared to summer (March to May).

Conclusion

In contrast to global trends, Indian patients demonstrated distinct seasonal variations in HbA1c levels. The highest levels during the monsoon (June to September) may be linked to reduced outdoor activity and dietary changes. The study emphasizes the need for tailored diabetes management considering seasonal influences. Further extensive, longitudinal studies across diverse Indian regions are recommended to comprehensively grasp the impact of seasonal changes on diabetes outcomes.

Seasonal variation and its interaction with pre-pregnancy BMI for GDM: a large population-based study in Tianjin, China

To evaluate the independent association of seasonal variation with GDM incidence in Tianjin, China, and to test whether there is an additive interaction between seasonal variation and pre-pregnancy body mass index (BMI) on GDM incidence. A population-based observational cohort study was conducted using the healthcare records data from Tianjin, China. Logistic regression was used to obtain odds ratios (ORs) and 95% confidence intervals (CIs). Additive interaction between pre-pregnancy BMI groups and seasons was estimated by using relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP), and synergy index (S). Among the 112,639 pregnant women, 20.8% developed GDM at 24-28 weeks of gestation. The multivariable adjusted ORs and 95% CIs were 1.00, 1.00 (0.96-1.05), 1.15 (1.09-1.20) and 1.22 (1.16-1.29) respectively based on seasons (spring, summer, autumn and winter). Compared with the spring/summer and pre-pregnant BMI < 24 kg/m2 group, co-presence of autumn/winter and pre-pregnancy BMI ≥ 24 kg/m2 increased the OR from 1.00 to 2.70 (95% CI 2.28-3.20), with a significant additive interaction: RERI (0.32, 95% CI 0.19-0.45), S (1.21, 95% CI 1.12-1.31) and AP (0.11, 95% CI 0.07-0.16). Autumn/winter is an independent risk factor for GDM incidence, and can significantly amplify the obesity-associated risk for GDM incidence. The underlying mechanism warrants further investigations. We suggest that seasonality is an additional factor when interpreting OGTT results for the diagnosis of GDM.

Understanding temporal changes and seasonal variations in glycemic trends using wearable data

Seasonal variations in glycemic trends remain largely unstudied despite the growing prevalence of diabetes. To address this gap, our objective is to investigate temporal changes in glycemic trends by analyzing intensively sampled blood glucose data from 137 patients (ages 2 to 76, primarily type 1 diabetes) over the course of 9 months to 4.5 years. From over 91,000 days of continuous glucose monitor data, we found that glycemic control decreases significantly around the holidays, with the largest decline observed on New Year's Day among the patients with already poor glycemic control (i.e., <55% time in the target range). We also observed seasonal variations in glycemic trends, with patients having worse glycemic control in the months of November to February (i.e., mid-fall and winter, in the United States), and better control in the months of April to August (i.e., mid-spring and summer). These insights are critical to inform targeted interventions that can improve diabetes outcomes.

Serum 25-Hydroxyvitamin D Levels in Type 2 Diabetes Patients in North China: Seasonality and the Association between Vitamin D Status and Glycosylated Hemoglobin Levels

Background and Aims

Previous studies have reported a correlation between vitamin D levels and seasonality in healthy populations. However, there are few studies on the seasonal variation in vitamin D levels and its relationship with glycosylated hemoglobin (HbA1c) in patients with type 2 diabetes mellitus (T2DM). The objective of this study was to investigate seasonal changes in serum 25-hydroxyvitamin D [25(OH)D] levels and the associations between these vitamin D concentrations and HbA1c levels in T2DM patients in Hebei, China.

Methods

A cross-sectional study of 1,074 individuals with T2DM was conducted from May 2018 to September 2021. Levels of 25(OH)D in these patients were assessed based on both sex and season, and relevant clinical or laboratory variables that could impact vitamin D status were also considered.

Results

In the T2DM patient cohort, the mean blood 25(OH)D levels were 17.05 ng/mL. A total of 698 patients (65.0%) had insufficient serum 25(OH)D levels. The vitamin D deficiency rates were significantly higher in the winter and spring compared to the autumn (P < 0.05), indicating that seasonal fluctuations can have a significant impact on 25(OH)D levels. The levels of vitamin D inadequacy were highest in the winter (74%), and females were more likely than males to be deficient (73.4% vs. 59.5%, P < 0.001). In comparison to the winter and spring, both males and females showed higher 25(OH)D levels in the summer (P < 0.001). HbA1c levels were 8.9% higher in those with vitamin D deficiencies than in nondeficient patients (P < 0.001). HbA1c and vitamin D levels were negatively correlated (r = -0.119, P < 0.001).

Conclusion

Vitamin D deficiencies are particularly prevalent among T2DM patients in Hebei, China, with exceptionally high rates in the winter and spring. Female T2DM patients were at an elevated risk of vitamin D deficiency, and vitamin D levels were negatively correlated with HbA1c.

Associations between cold spells and hospital admission and mortality due to diabetes: A nationwide multi-region time-series study in Korea

BACKGROUND

Climate change is predicted to increase the frequency, intensity, and duration of extreme cold events in the mid-latitudes. However, although diabetes is one of the most critical metabolic diseases due to its high and increasing prevalence worldwide, few studies have investigated the short-term association between cold exposure and diabetes-related outcomes.

OBJECTIVE

The aim of this study was to investigate the associations between cold spells and their characteristics (intensity, duration, and seasonal timing) and hospital admission and mortality due to diabetes.

METHODS

This study used claims data from the National Health Insurance Service and cause-specific mortality data from Statistics Korea (2010-2019). Cold spells were defined as ≥2 consecutive days with a daily mean temperature lower than the region-specific 5th percentile during the cold season (November-March). Quasi-Poisson regressions combined with distributed lag models were used to assess the associations between exposures and outcomes in 16 regions across the Republic of Korea. Meta-analyses were conducted to pool the region-specific estimates.

RESULTS

Exposure to cold spells was associated with an increased risk of hospital admission [relative risk (RR) = 1.45, 95% confidence interval (CI): 1.26, 1.66] and mortality (RR = 2.02, 95% CI: 1.37, 2.99) due to diabetes. The association between cold spells and hospital admission due to diabetes was stronger for cold spells that were more intense, longer, and occurred later during the cold season. The association between cold spells and diabetes-related mortality was stronger for more intense and longer cold spells.

CONCLUSION

This study emphasizes the importance of developing effective interventions against cold spells, including education on the dangers of cold spells and early alarm systems. Further studies are needed to create real-world interventions and evaluate their effectiveness in improving diabetes-related outcomes.

Intermediate- and long-term associations between air pollution and ambient temperature and glycated hemoglobin levels in women of child bearing age

BACKGROUND

Air pollution has been linked to obesity while higher ambient temperatures typically reduce metabolic demand in a compensatory manner. Both relationships may impact glucose metabolism, thus we examined the association between intermediate- and long-term exposure to fine particulate matter (PM2.5) and ambient temperature and glycated hemoglobin(HbA1c), a longer-term marker of glucose control.

METHODS

We assessed 3-month, 6-month, and 12-month average air pollution and ambient temperature at 1-km2 spatial resolution via satellite remote sensing models (2013-2019), and assessed HbA1c at four, six, and eight years postpartum in women enrolled in the Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS) cohort based in Mexico City. PM2.5 and ambient temperature were matched to participants' addresses and confirmed by GPS tracker. Using linear mixed-effects models, we examined the association between 3-month, 6-month, and 12-month average PM2.5 and ambient temperature with repeated log-transformed HbA1c values. All models included a random intercept for each woman and were adjusted for calendar year, season, and individual-level confounders (age, marital status, smoking, alcohol consumption level, and education level).

RESULTS

We analyzed 1,265 HbA1c measurements of 484 women. Per 1 µg/m3 increase in 3-month and 6-month PM2.5, HbA1c levels increased by 0.28% (95% confidence interval (95 %CI): 0.14, 0.42%) and 0.28% (95 %CI: 0.04, 0.52%) respectively. No association was seen for 12-month average PM2.5. Per 1 °C increase in ambient temperature, HbA1c levels decreased by 0.63% (95 %CI: -1.06, -0.21%) and 0.61% (95 %CI: -1.08, -0.13%), while the 12-month average again is not associated with HbA1c.

CONCLUSIONS

Intermediate-term exposure to PM2.5 and ambient temperature are associated with opposing changes in HbA1c levels, in this region of high PM2.5 and moderate temperature fluctuation. These effects, measurable in mid-adult life, may portend future risk of type 2 diabetes and possible heart disease.

Seasonal variations and the influence of COVID-19 pandemic on hemoglobin A1c, glycoalbumin, and low-density lipoprotein cholesterol

Aim

The purpose of the study was to investigate seasonal variations in HbA1c, GA and LDL-C and to examine the effects of the COVID-19 pandemic on these variations and on glycemic and lipid control themselves in patients with type 2 diabetes.

Patients and methods

The subjects were outpatients with type 2 diabetes who had received standard treatment for glycemic control for more than 3 years. Data for patients who visited our hospital from January 2021 to March 2021 were retrospectively investigated based on electronic medical records.

Results

HbA1c showed seasonal variation (high in winter–spring and low in summer–autumn), and this was similar during the COVID-19 pandemic. However, the mean HbA1c over 1 year was significantly elevated during the COVID-19 pandemic (7.53 ± 1.02% in 2020) compared with the previous 2 years: (7.34 ± 0.91 in 2018, 7.39 ± 0.93 in 2019; 2020 vs. 2018; 0.19%, P < 0.001; 2020 vs. 2019; 0.14%, P = 0.0013) and the difference was larger in winter. GA showed no apparent seasonal variation, but mean GA during the COVID-19 pandemic was elevated compared with earlier years (2020 vs. 2018, P < 0.001; 2020 vs. 2019, P < 0.001). LDL-C did not show apparent seasonal variation and was unaffected by COVID-19 pandemic.

Conclusion

The COVID-19 pandemic influenced mean HbA1c and GA levels over 1 year, but did not affect seasonal variations, while LDL-C was not affected by COVID-19. Observation of these levels over a longer period is warranted to determine the longer-term influence of the COVID-19 pandemic.

Year-Long Trend in Glycated Hemoglobin Levels in Patients with Type 2 Diabetes during the COVID-19 Pandemic

It has been suggested that the coronavirus disease 2019 (COVID-19) pandemic has had a negative impact on glycemic control in patients with type 2 diabetes mellitus (T2DM). However, no study has examined yearly trends in glycated hemoglobin (HbA1c) levels after the start of the COVID-19 outbreak. Here, we performed a retrospective analysis of HbA1c concentrations during the early period of the COVID-19 outbreak (COVID-19 cohort) and then compared the yearly trend in the mean HbA1c level, along with fluctuations in HbA1c levels, with those during previous years (non-COVID-19 cohorts). We observed that the mean HbA1c level in patients with T2DM increased during the first 6 months of the COVID-19 outbreak. After 6 months, HbA1c levels in the COVID-19 cohort returned to levels seen in the non-COVID-19 cohorts. The data suggest that vulnerable patients with T2DM should be monitored closely during the early period of a pandemic to ensure they receive appropriate care.

Seasonal variations in HbA1c among type 2 diabetes patients on a semi-arid climate between the years 2005-2015

AIMS

To investigate the seasonal variations of HbA1c values in a semi-arid climate among type 2 diabetic patients throughout 11 years of care.

METHODS

A retrospective cohort study of 2860 patients with 61,187 HbA1c measures. We calculated the averages of HbA1c values of all patients and sub-groups defined by age, gender, BMI, ethnicity, insulin use, smoking status and region of residence, matched to the mean temperature and diurnal range over the 30 and 60 days prior to the HbA1c test date.

RESULTS

We found a sinusoidal seasonal pattern with statistically significant HbA1c levels gaps between the spring peak and the autumn trough (F = 18.4, P < 0.001). The lowest values were in October-November and the highest in March or August with a difference of 0.17-0.31% (2-4 mmol/mol). We found different relations between the mean temperature and HbA1c depending on season, gender, age, ethnicity and smoking habits.

CONCLUSION

The study identified specific subgroups in which the seasonal influence is particularly marked. A possible explanation is that during hot periods people tend to change their diet and decrease their physical activity, effecting indirectly diabetic imbalance. Recognition of the seasonal variations of HbA1c levels in this geographical region could help physicians with diabetes care and HbA1c control.

Seasonal fluctuation of erectile dysfunction: A cross-sectional study from a tertiary university hospital across 10 years

Erectile dysfunction (ED) shares several risk factors with diabetes mellitus (DM), hypertension (HT) and coronary vascular disease (CVD), which were well-associated with seasonal fluctuation with the highest peak in winter. In this study, we aimed to determine whether ED demonstrates seasonal fluctuations with the above-mentioned systemic diseases. Database from a tertiary university hospital between 2010 and 2020 was deciphered to retrieve patients diagnosed with ED. Patients with primary bladder tumour and post-procedural ED constituted the negative control groups from the same study period. International index of erectile function questionnaire (IIEF-15) was used to segregate included patients into mild/moderate and severe ED groups. The probability of detecting DM, HT and CVD in patients with severe ED was significantly higher than that of with mild/moderate ED (p < 0.05). More ED symptoms emerged and were diagnosed in the winter seasons even though no statistical significance was observed between patients with mild/moderate and severe ED (p = 0.946, Cramer's V coefficient = 0.19). The seasonal variation of patients with bladder tumour and post-procedural ED groups showed no significant difference (p > 0.05, both). ED admissions are associated with higher peaks in the winter seasons. This may help in daily clinical practice to warrant better clinical and epidemiological interpretation of ED.

Seasonal variation of diabetes with hyperosmolarity hospitalizations and its characteristics in mainland Portugal

AIMS

The family physician devotes a part of his care to the surveillance of diabetic patients. Hyperosmolarity is a severe acute complication. The aim of this study was to analyse seasonal variation of type 2 diabetes with hyperosmolarity hospitalizations, regarding their occurrence, mortality, length of stay, Charlson comorbidity index and its factors.

METHODS

The authors analysed all hospitalizations in Portuguese Mainland public sector hospitals between 2000 and 2015 with primary diagnosis of type 2 diabetes with hyperosmolarity (ICD-9-CM codes 250.20 or 250.22), using a national administrative database. Cases were classified into four seasons according to date of admission. The authors compared the occurrence, length of stay, in-hospital mortality and Charlson comorbidity index and its factors.

RESULTS

A total of 6596 hospitalization episodes were included. The authors found that admissions occurred more in winter, being 23% more common. No seasonal statistically significant differences were found considering the other variables.

CONCLUSIONS

There is an increased occurrence of this acute metabolic complication during the winter in patients with type 2 diabetes. These results should be taken into account by the family physician when planning surveillance to this risk group.

A Study of Seasonal Variation in the Effect of Add-On Sitagliptin on Blood Glucose Control in Insulin-Treated Patients With Type 2 Diabetes

Background

There are several reports of seasonal variation in hemoglobin A1c (HbA1c) in patients with type 2 diabetes (T2DM), but no reports of seasonal variation in the effect of add-on drugs on blood glucose control in insulin-treated patients.

Methods

Using data collected from 630 patients in a multicenter study, we compared the amount of change in HbA1c after 1, 3, 6, 9, and 12 months of add-on administration of sitagliptin in insulin-treated patients divided into four groups based on the month when sitagliptin was started.

Results

A significantly larger decrease in HbA1c at 6 months from baseline was observed in the group that started add-on sitagliptin in February to April than in the other three groups. However, the amount of change in HbA1c at 12 months did not differ among the groups.

Conclusions

The consideration of seasonal variation enables more accurate evaluation of a drug’s short-term effect on blood glucose control.

Efficacy and Safety of Switching to Teneligliptin in Patients with Type 2 Diabetes Inadequately Controlled with Dipeptidyl Peptidase-4 Inhibitors: A 12-Week Interim Report

INTRODUCTION

Teneligliptin, an antidiabetic agent classified as a class III dipeptidyl peptidase-4 (DPP-4) inhibitor, has a unique structural feature that provides strong binding to DPP-4 enzymes. We investigated the efficacy and safety of switching patients with type 2 diabetes mellitus (T2DM) who had inadequate glycemic control on a stable dose of other DPP-4 inhibitors to teneligliptin.

METHODS

Patients with T2DM whose glycosylated hemoglobin (HbA1c) levels were ≥ 7% despite taking DPP-4 inhibitors other than teneligliptin, with or without other hypoglycemic agents, for at least 3 months were enrolled. The DPP-4 inhibitors taken before participating in the study were switched to 20 mg qd teneligliptin, and this was to be maintained for 52 weeks. The primary end point was the change in HbA1c levels after 12 weeks. Metabolic parameters including fasting plasma glucose (FPG) and blood lipids were assessed also. To assess safety, adverse and hypoglycemic events were monitored. The data from baseline to week 12 were used for analysis in this interim report.

RESULTS

The mean change in HbA1c levels from baseline to week 12 was - 0.44%. At week 12, the percentage of patients achieving HbA1c < 7.0% was 31.6% and that of achieving HbA1c < 6.5% was 11.4%, respectively. In 41.2% of patients, the HbA1c levels decreased by at least 0.5% at 12 weeks. The mean change in FPG levels from baseline to week 12 was - 11.5 mg/dl. No severe hypoglycemia was reported.

CONCLUSION

After switching to teneligliptin, HbA1c levels decreased significantly in patients with T2DM inadequately controlled with other DPP-4 inhibitors.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT03793023.

FUNDING

Handok Inc.

Type 2 Diabetes and Glycemic Variability: Various Parameters in Clinical Practice

It has become possible to measure blood glucose levels continuously from 24 h to approximately 2 weeks due to the recent development of relevant devices such as continuous glucose monitoring and flash glucose monitoring systems. This has enabled not only medical professionals but also patients to monitor details of glycemic variability (GV) which was not possible in the past. Details of GV for both short and intermediate periods can now be obtained, and it is important in patient care to appropriately evaluate the data obtained. Types of GV in terms of time frame vary from short-term to long-term. Several studies reported that long-term GV was related to micro- and macro-angiopathies in patients with type 2 diabetes mellitus (T2DM). However, there are still unknown aspects regarding the relationships of various durations of GV with prognosis. Further clinical trials are required to examine the mechanism of GV and to evaluate whether GV can be a valuable therapeutic target in treatment of patients with T2DM.

Analysis of the effect of seasonal administration on the efficacy of sitagliptin: Subanalysis of the Januvia Multicenter Prospective Trial in Type 2 Diabetes Study

AIMS/INTRODUCTION

Hemoglobin A1c (HbA1c) levels in patients with type 2 diabetes mellitus fluctuate throughout the year. However, there are few studies that have evaluated the therapeutic effect of hypoglycemic agents while considering such fluctuations. In a multicenter study (Januvia Multicenter Prospective Trial in Type 2 Diabetes Study), pretreatment patients with type 2 diabetes mellitus were divided into seven groups and given sitagliptin for 1 year. The aim of the present study was to evaluate the differences in the therapeutic effect, and the efficacy of sitagliptin in patients with type 2 diabetes mellitus based on the month the administration of the drug began as a subanalysis of the Januvia Multicenter Prospective Trial in Type 2 Diabetes Study.

MATERIALS AND METHODS

Patients with type 2 diabetes mellitus were divided into four groups according to the month of initiation of sitagliptin. Changes in HbA1c in each group were compared at 3 and 12 months after administration of sitagliptin. As a negative correlation has been reported between baseline HbA1c and the degree of change after administration of sitagliptin, an analysis using the residual error from the approximate line was carried out.

RESULTS

In the analysis of the degree of change in HbA1c, patients in the group in which administration of sitagliptin was started between August and October had the lowest degree of improvement at 3 months after starting sitagliptin. However, there was no significant intergroup difference in improvement at 12 months after the start of sitagliptin. The same result was also obtained in residual analysis.

CONCLUSIONS

The present study suggested that the season of administration of sitagliptin influenced the subsequent hypoglycemic effect even after analysis excluding the influence of HbA1c value at the start of treatment. This study provides possibility, showing that seasonal fluctuations have an effect on the efficacy of antidiabetic drugs.

HbA1c variability in type 2 diabetes is associated with the occurrence of new-onset albuminuria within three years

AIMS

To evaluate the association between HbA1c coefficient of variation (HbA1c-CV) and 3-year new-onset albuminuria risk.

METHODS

A retrospective cohort study involving 716 normoalbuminuric type 2 diabetes patients was conducted between 2010 and 2014. HbA1c-CV was used to categorize patients into low, moderate or high variability groups. Multivariate logistic models were constructed and validated. Integrated discrimination (IDI) and net reclassification (NRI) improvement indices were used to quantify the added predictive value of HbA1c-CV.

RESULTS

The mean age of our cohort was 56.1±12.9years with a baseline HbA1c of 8.3±1.3%. Over 3-years of follow-up, 35.2% (n=252) developed albuminuria. An incremental risk of albuminuria was observed with moderate (6.68-13.43%) and high (above 13.44%) HbA1c-CV categories demonstrating adjusted odds ratios of 1.63 (1.12-2.38) and 3.80 (2.10-6.97) for 3-year new-onset albuminuria, respectively. Including HbA1c-CV for 3-year new-onset albuminuria prediction improved model discrimination (IDI: 0.023, NRI: 0.293, p<0.05). The final model had a C-statistic of 0.760±0.018 on validation.

CONCLUSION

HbA1c-CV improves 3-year prediction of new-onset albuminuria. Together with mean HbA1c, baseline urine albumin-to-creatinine ratio and presence of hypertension, accurate 3-year new-onset albuminuria prediction may be possible.

Time series modelling to forecast prehospital EMS demand for diabetic emergencies

BACKGROUND

Acute diabetic emergencies are often managed by prehospital Emergency Medical Services (EMS). The projected growth in prevalence of diabetes is likely to result in rising demand for prehospital EMS that are already under pressure. The aims of this study were to model the temporal trends and provide forecasts of prehospital attendances for diabetic emergencies.

METHODS

A time series analysis on monthly cases of hypoglycemia and hyperglycemia was conducted using data from the Ambulance Victoria (AV) electronic database between 2009 and 2015. Using the seasonal autoregressive integrated moving average (SARIMA) modelling process, different models were evaluated. The most parsimonious model with the highest accuracy was selected.

RESULTS

Forty-one thousand four hundred fifty-four prehospital diabetic emergencies were attended over a seven-year period with an increase in the annual median monthly caseload between 2009 (484.5) and 2015 (549.5). Hypoglycemia (70%) and people with type 1 diabetes (48%) accounted for most attendances. The SARIMA (0,1,0,12) model provided the best fit, with a MAPE of 4.2% and predicts a monthly caseload of approximately 740 by the end of 2017.

CONCLUSIONS

Prehospital EMS demand for diabetic emergencies is increasing. SARIMA time series models are a valuable tool to allow forecasting of future caseload with high accuracy and predict increasing cases of prehospital diabetic emergencies into the future. The model generated by this study may be used by service providers to allow appropriate planning and resource allocation of EMS for diabetic emergencies.

Correlation between Total Solar Irradiance and Glycated Hemoglobin 2 to 3 Months Later in Patients with Diabetes: A Big-Data Analysis

OBJECTIVES

Much attention has been paid recently to a relationship between glucose metabolism and weather. This study investigated the temporal correlation between total solar irradiance (TSI) and glycated hemoglobin (A1C) values in patients with diabetes.

METHODS

In 1531 patients with diabetes who received follow-up care between 2009 and 2013 (type 1 diabetes, 123 patients; type 2 diabetes, 1408 patients; male 53.6%; mean age, 61.2 years), A1C levels were measured a total of 58,830 times. The correlation between mean monthly TSI and mean A1C values from 1 to 4 months later was then examined.

RESULTS

The mean values for TSI and A1C throughout the entire study period were 13.7 MJ/m² and 7.7%, respectively. The correlation coefficient between TSI and mean monthly A1C values at 1 to 4 months was -0.516, -0.734, -0.726 and -0.475, respectively (all p<0.001).

CONCLUSIONS

There was a highly negative correlation between TSI and mean A1C values 2 to 3 months later in this population; thus, this fact may need to be considered when using A1C levels as a glycemic control index in patients with diabetes. Further studies are warranted.