Is there any agreed cut off point for serum HbA1c level to be considered as a protective burden for Ischemic Cerebrovascular Accidents occurrence in Diabetics?

Is there any agreed cut off point for serum HbA1c level to be considered as a protective burden for Ischemic Cerebrovascular Accidents occurrence in Diabetics? | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Is there any agreed cut off point for serum HbA1c level to be considered as a protective burden for Ischemic Cerebrovascular Accidents occurrence in Diabetics? Hassan Motamed, Poyan Alizadeh, Reza Ajodani, Azin Kalantari, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8751498/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction Diabetes mellitus is one of the most common chronic diseases worldwide. It associated with a higher risk of cardiovascular complications, including cerebrovascular accidents. Studies show that people with diabetes have twice the risk of stroke compared to those without diabetes. The high rates of stroke-related morbidity result in a substantial economic burden. In patients with type 2 diabetes, maintaining HbA1c about 1 percentage point lower with intensive glucose control for several years leads to lasting clinical benefits. The current study aims to determine, despite the potential role of diabetes mellitus in cerebrovascular events (ischemic stroke), which HbA1c cut-off increased the risk of cerebrovascular events and which cut-off is safe in terms of cerebrovascular events. This study had been designed with a fucose on HBA1c cut-off point determination compatible with significant increased risk and incidence for ischemic cerebrovascular attacks in diabetes. Methods and Materials Diabetic patients of more than 18 years old who had clinical symptoms and signs of an acute ischemic stroke in recent 6 hours which have been confirmed subsequently by cranial neuroimaging of Computed Tomography Scan or Magnetic Resonance Imaging by an emergency medicine specialist or a neurologist, were included in the study, while diabetic patients with no history of stroke were considered the control group. Serum HbA1c level has been evaluated for both groups. Data has been analyzed to evaluate correlation of serum HbA1c level cut-off with risk of cerebrovascular ischemic stroke in diabetics. Sample size with a power of 80% was calculated 62 diabetic patients with acute ischemic stroke and 62 diabetic patients without stroke as control group. Results Demographic and baseline characteristics of both the case and control groups were compared. There were no significant differences between the two groups in age, sex, IHD, HTN, DLP, and smoking. We had 62 diabetic patients with CVA with a mean age of 64.16±12.43 and 62 diabetic patients without CVA with a mean age of 63.37±6.82. Regarding comparing the HbA1C average between patients with and without CVA, the mean in patients with CVA was 8.21 ±1.70, while in patients without CVA it was 7.56 ±1.28 that which was significantly higher in CVA (p-value <0.02). Using logistic regression, the odds ratio (OR) with a 95% confidence interval was calculated as 1.34 (1.05,1.71). The predictive value of HbA1c for an increase in the risk of CVA occurrence was determined by ROC curve plotting; an AUC with 95% CI (0.516,0.694) was calculated 0.608 (p-value<0.036). Youden index for optimal HbA1c range for CVA risk, considering sensitivity as 69.35 and specificity as 35.48; showed a HbA1c cut-off point of 6.8. Discussion Several studies have assessed differences in mean HbA1c levels between individuals with and without stroke, but the findings have been inconsistent. In addition, only a few studies have demonstrated the predictive value of HbA1c for stroke or identified the specific levels that put patients at higher risk. In this study, we show that the HbA1c mean in diabetic patients with stroke was significantly higher than diabetic patients without stroke. Having diabetes substantially increased the odds of ischemic stroke roughly in the range of 30%to 100% higher risk after adjusting for other vascular risk factors. In a trial, patients with HbA1c8.6% faced increased risk, indicating that lifestyle intervention’s vascular benefits including ischemic stroke prevention are limited to patients with relatively well controlled baseline glycemia. Our study shows that higher HbA1c levels are associated with a raised risk of stroke. Recognizing the HbA1c level that puts patients at higher risk of stroke can help clinicians focus on better glycemic control. Therefore, keeping HbA1c within safe ranges may play an important role in preventing strokes. Conclusion Elevated HbA1c levels exceeding 8% among diabetic patients appear to significantly cause prominent elevation in ischemic stroke occurrence risk, whereas maintaining HbA1c within the 6.8 to 7.0% range accompany with less potential risk for ischemic stroke events. Figures Figure 1 Figure 2 Introduction Diabetes mellitus is one of the most common chronic diseases worldwide ( 1 ). It is associated with a higher risk of cardiovascular complications, including cerebrovascular accidents ( 2 ). Studies show that people with diabetes have twice the risk of stroke compared to those without diabetes ( 2 , 3 ). And about 30% of people with stroke also have diabetes ( 3 , 4 ). The rise in life expectancy and the aging population have led to an increase in stroke cases. Consequently, over the past 30 years, the total number of people affected by stroke, including deaths and long-term disability, has nearly doubled. Stroke was the second most common cause of death in 2019, with 6.5 million mortalities, and the third leading cause of disability, which was responsible for 143 million DALYs (Disability Adjusted Life Years) ( 5 ). The high rates of stroke-related morbidity result in a substantial economic burden, so that the global cost of stroke is more than US $ 890 billion annually ( 6 ). It is predicted that the total cost of stroke, including treatment, rehabilitation, and lost income due to disability, could rise from US $ 891 billion in 2017 to over US $ 2.3 trillion by 2050. However, this increase could be avoided because stroke is highly preventable ( 7 ). People with diabetes face a substantially higher like hood of small vessel damage eye, kidney and nerve disease as well as large artery complications like heart attacks, ischemic stroke and peripheral arterial disease. The chapter summarizes evidence showing that bringing HbA1c into the very low range below roughly 6 to6.5% yields only modest extra microvascular benefit and has limited impact on major macrovascular outcomes such as stroke which are influenced more by global cardiovascular risk and the chronicity of diabetes ( 8 ).cardiac conditions, diabetes accounted for a meaningful proportion of the overall burden of stroke at the population level, underscoring its role as a key, but partly preventable, vascular risk factor worldwide ( 9 ). In a Japanese randomized trial, patients who had experienced a prior stroke were randomly allocated to usual blood pressure targets below 140/90 mm Hg or to more aggressive treatment aiming for values under 120/80 mmHg, then followed for several years to monitor new stroke. the intensive-treatment arm showed fewer recurrent strokes than the standard group, but because the study was stopped early, the reduction was not statistically definitive by itself. however, when these data were combined with earlier intensive vs standard blood pressure studies in a metanalysis, aiming for lower blood pressure(generally < 130/80 mmHg)produced a significant roughly one fifth reduction in the overall risk of having another stroke, driven largely by fewer hemorrhagic strokes ( 10 ). In a large trial of people with type 2 diabetes, targeting an HbA1c of 6.5% or lower with a gliclazide based regimen lowered average HbA1c to 6.5%,compared with about 7.3% under standard care, corresponding to roughly a 0.8 percentage point difference sustained for 5years.this degree of HbA1c lowering clearly reduced overall major vascular events when microvascular and macrovascular outcomes were combined principally by lowering the risk of nephropathy whereas the impact on major macrovascular events such as myocardial infarction and stroke alone was small and did not reach statistical significance, highlighting that intensive HbA1c reduction primarily benefits microvascular disease in this population ( 11 ). In patients with type 2 diabetes, maintaining HbA1c about 1 percentage point lower with intensive glucose control (typically near 7% versus close to 8%) for several years leads to lasting clinical benefits, even if this HbA1c difference disappears within about a year after stopping intensive treatment. long-term follow-up demonstrates that those who initially achieved lower HbA1c experience fewer microvascular complications and meaningful reductions in myocardial infarction and all causes mortality, supporting the concept of a durable “legacy effect” of early tight glycemic control on vascular outcomes ( 12 ). Having diabetes substantially increased the odds of both ischemic and hemorrhagic stroke roughly in the range of 30%to 100% higher risk after adjusting for other vascular risk factors, with some variation by geographic region and stroke type. When combined with elevated blood pressure, abdominal adiposity, abnormal lipids, smoking. Since strokes related to metabolic risk factors account for 69% of all strokes ( 6 ), controlling metabolic diseases such as diabetes can play an important role in reducing the global stroke burden. The current study aims to determine, despite the potential role of diabetes mellitus in cerebrovascular events (ischemic stroke), which HbA1c cut-off increased the risk of cerebrovascular events and which cut-off is safe in terms of cerebrovascular events. This study had been designed with a fucose on HBA1c cut-off point determination compatible with significant increased risk and incidence for ischemic cerebrovascular attacks in diabetes. Methods and Materials This case-control study took place at Golestan Hospital in Ahvaz, located in the southwest of Iran, between October 2024 and July 2025. diabetic Patients who had been confirmed by a neurologist or an emergency physician to have experienced an acute ischemic stroke at recent 6 hours were considered the case group, while diabetic patients with no history of stroke were considered the control group. The study protocol was approved by the Ethics Committee of Ahvaz University of Medical Sciences (IR.AJUMS.REC.1403.366). Inclusion criteria for the case group were age 18 years or older, the presence of clinical signs of cerebrovascular accident (CVA), such as hemiparesis or aphasia, which occurrence of CVA was confirmed by a registered emergency medicine or a neurologist or imaging (brain CT scan or MRI), and also patients with diabetes, which was confirmed by an endocrinologist or patients as known diabetic cases were enrolled as the case group. Patients older than 18 years who were known diabetic cases without any neurological symptoms were enrolled as the control group. Exclusion criteria for both the case and control group were a lack of patient consent, age below 18 years, a history of hemorrhagic stroke, and neurological symptoms caused by other conditions, such as hypoglycemia, TIA, or other neuropathies. Known diabetic patients who were under treatment by an endocrinologist and were admitted to Golestan Hospital during the study period were assessed for eligibility. After applying the inclusion and exclusion criteria, diabetic patients with acute ischemic stroke were included in the case group, and diabetic patients without stroke were included in the control group (Fig. 1 ). Demographic and medical information, including age, sex, and history of ischemic heart disease (IHD), hypertension (HTN), dyslipidemia (DLP), and smoking, was collected directly from patients through interviews. Serum HbA1c samples were collected from all patients within the first 24 hours of admission and were measured using the Selectra XL autoanalyzer. This procedure did not interfere with the standard management of CVA; all patients received the necessary treatment according to established clinical protocols, and it did not incur any additional costs for the patients. the analytic data has been analyzed based on the patients` data to answer this question that how can HbA1c level, influence cerebrovascular risk of ischemic stroke in diabetic patients. Statistical analysis Data were analyzed using SPSS software (version 22). Quantitative variables were reported as mean ± standard deviation (SD), while Categorical variables were reported as percentages. The normality of continuous variables was assessed using the Shapiro Wilk test, and they were normally distributed. Comparison of quantitative variables between two groups was performed using the t-test. To compare Categorical variables, the Chi-square test was applied. Additionally, a logistic regression model was applied to assess the effect of HbA1C on stroke occurrence, and odds ratios (OR) with 95% confidence intervals (CI) were reported. To determine the predictive value of HbA1c for stroke, a Receiver Operating Characteristic (ROC) curve was plotted, and the area under the curve (AUC) was calculated. The optimal cut-off point for safe limitation of HbA1c was determined using Youden’s Index. A p-value less than 0.05 was considered statistically significant. According to previous studies ( 13 ), the sample size with a power of 80% was calculated as follows: 62 diabetic patients with acute ischemic stroke were enrolled as the case group, and 62 diabetic patients without stroke were enrolled as the control group. Results Demographic and baseline characteristics of both the case and control groups were compared. There were no significant differences between the two groups in age, sex, IHD, HTN, DLP, and smoking. We had 62 diabetic patients with CVA with a mean age of 64.16 ± 12.43 (53.2% male and 46.8% female) and 62 diabetic patients without CVA with a mean age of 63.37 ± 6.82 (46.8% male and 53.2% female). The medical history was as follows: in the case group, 48.4% had IHD, 59.7% had HTN, 16.1% had DLP, and 40% were smokers, while in the control group, 38% had IHD, 51.6% had HTN, 21% had DLP, and 32.3% were smokers. (Table 1 ) Table 1 Demographic and baseline characteristics CVA Non CVA p-value Age , years 64.16 ± 12.43 63.37 ± 6.82 0.662 Sex , n (%) Male Female 33(53.2%) 29(46.8%) 29(46.8%) 33(53.2%) 0.472 IHD , n (%) NO YES 32(51.6%) 30(48.4%) 38(61.3%) 24(38.7%) 0.277 HTN , n (%) NO YES 25(40.3%) 37(59.7%) 30(48.4%) 32(51.6%) 0.366 DLP , n (%) NO YES 52(83.9%) 10(16.1%) 49(79%) 13(21%) 0.488 Smoking , n (%) NO YES 37(59.7%) 25(40.3%) 42(67.7%) 20(32.3%) 0.350 CVA: cerebrovascular accident, IHD: ischemic heart disease, HTN: hypertension, DLP: dyslipidemia Regarding comparing the HbA1C average between patients with and without CVA, the mean in patients with CVA was 8.21 ± 1.70, while in patients without CVA it was 7.56 ± 1.28 that which was significantly higher in CVA (p-value < 0.02). Using logistic regression, the odds ratio (OR) with a 95% confidence interval was calculated as 1.34(1.05,1.71) (Table 2 ). Table 2 Comparison of mean HbA1c levels between patients with and without stroke, and odds ratio. CVA Non CVA OR (95%CI) P value HbA1C, % 8.21 ± 1.70 7.56 ± 1.28 1.34 (1.05,1.71) 0.02 CVA: cerebrovascular accident, OR: odds ratio, CI: confidence interval To investigate the predictive value of HbA1c for an increase in the risk of CVA occurrence, the ROC curve was plotted, and the AUC with 95% CI (0.516,0.694) was calculated as 0.608 (p-value < 0.036) (Fig. 2 ) (Table 3 ). Table 3 ROC curve analysis of the predictive value of HbA1c for stroke AUC 95% CI p-value 0.608 (0.516,0.694) 0.036 AUC: area under the curve, CI: confidence interval We used the Youden index to determine the optimal HbA1c range for CVA risk, considering sensitivity as 69.35 and specificity as 35.48; the cut-off point for HbA1c was 6.8 (Table 4 ). Table 4 The optimal HbA1c cutoff for predicting CVA according to the Youden index with selective sensitivity and specificity Cutoff value Sensitivity Specificity 6 93.55 1.61 6.4 88.71 16.13 6.8 69.35 35.48 7.2 59.68 51.61 7.6 53.23 62.90 Discussion Several studies have assessed differences in mean HbA1c levels between individuals with and without stroke, but the findings have been inconsistent. In addition, only a few studies have demonstrated the predictive value of HbA1c for stroke or identified the specific levels that put patients at higher risk. In this study, we show that the HbA1c mean in diabetic patients with stroke was significantly higher than diabetic patients without stroke. An odds ratio of 1.3 indicates 30% higher odds of stroke occurrence among patients with higher HbA1c levels. Also, we demonstrated that HbA1c can be a predictive factor for stroke incidence, so that patients with HbA1c higher than 6.8 were more likely to experience a stroke compared with those with lower levels. In a recent study, Zafar et al. found that HbA1c levels higher than 6.9 were associated with worse functional outcomes after stroke, which is similar to our results and concordant with the necessity of glycemic control ( 14 ). Analysis of nearly 5,000 individuals living with diabetes who had survived a previous stroke or TIA revealed that keeping HbA1c levels precisely between 6.8% and 7.0% offered the best protection against future ischemic brain events or heart attacks. Compared to this sweet spot, Diabetic patients whose HbA1c fell below 6.8% or climbed above 7.0% faced substantially greater chances of experiencing another stroke during follow-up. The pattern indicated steadily worsening odds of recurrent ischemic stroke as HbA1c rose beyond 7.0% while unexpectedly low readings under 6.0% also correlated with poorer outcomes, forming a U-shaped relationship where HbA1c around 6.8% to 7.0% represented the safest zone for preventing repeat cerebrovascular accidents in this high risk diabetic population ( 15 ). Researchers synthesized data from 13 studies involving 12,810 individuals who experienced stroke, predominantly ischemic cases (10,131) versus hemorrhagic (2,679), To assess HbA1c thresholds of under 6.5% the 6.5–8.2% band, and readings exceeding 8.2%. Individuals surpassing the 6.5% mark demonstrated substantially diminished functional recovery (OR 1.86 for mRS 3–6 at 3 months) and elevated death rates relative to those below this level. A clear gradient emerged in the dose response pattern, where climbing past 6.5% steadily worsened prognosis, reaching peak risk for adverse outcomes and mortality among ischemic stroke patients when HbA1c topped 8.2% ( 16 ). GBD 2019 investigators quantified stroke disability worldwide by linking it to fasting glucose elevations, a reliable proxy for HbA1c ≥ 7.0 across every country over three decades. This metabolic risk factor placed sixth among all stroke causes globally, accounting for nearly 10% of ischemic stroke cases by 2019.among diabetic populations specifically, higher chronic glucose readings tied directly to greater ischemic stroke rates, with risk attribution surging 76% in working age groups(15–59 years)during the study timeframe, positioning sustained hyperglycemia as a prime target for preventing ischemic brain events on a global scale ( 5 ). Among 7,380 patients with acute ischemic stroke, those with HbA1c ≥ 6.5% faced higher odds of unfavorable functional status at 3months compared toHbA1c < 5.7%.in younger adults(< 65yearsold)with small vessel disease, elevated HbA1c ≥ 6.5%markedly worsened both short term and long term outcomes, while the link was weaker or absent in other stroke subtypes and older patients ( 17 ). In an 18 years period follow-up of type1 diabetes` patients intensive glucose lowering maintained mean HbA1c around 7.4% (vs 9.0% in conventional care) without causing cognitive impairment, even with higher severe hypoglycemia rates in the intensive arm. neuropsychological testing across multiple domains showed no deterioration attributable to intensive treatment or recurrent hypoglycemia, indicating that sustained lower HbA1c over nearly two decades preserves cognitive function in longstanding type1 diabetes ( 18 ). Among 301 participants, intensive glucose lowering dropped HbA1c by about 1.4 percentage points and cut CVD events by 89% specifically in those with minimal coronary calcification. Preexisting calcified atherosclerosis determines intensive glycemic therapy effectiveness ( 19 ). Analyzing 532,779 participants across 29 studies,HbA1c ≥ 6.5% doubled first ever stroke risk versus < 5.7%.each 1 percentage point HbA1c rise increased stroke odds by 17% among diabetics and 12% in nondiabetics with ischemic stroke showing even stronger links 24% higher per 1% in diabetes and 49% in nondiabetic groups ( 20 ). In a trial, intensive lifestyle intervention among overweight and obese adults with type2 diabetes achieved HbA1c reductions of 0.3 to 0.5% alongside 4.7% mean 8 years weight loss, yet demonstrated no overall cardiovascular benefit including ischemic stroke within the primary composite endpoint. Critically, baseline HbA1c stratified outcomes: patients with HbA1c 8.6% faced increased risk, indicating that lifestyle intervention’s vascular benefits including ischemic stroke prevention are limited to patients with relatively well controlled baseline glycemia ( 21 ). Among 1,293 acute ischemic stroke patients, admission HbA1c ≥ 6.5% predicted 1.82 fold higher odds of unfavorable 90 day functional status compared to HbA1c < 6.5%.every 1 percentage point HbA1c elevation independently increased poor outcomes risk by 25% after stroke severity adjustment ( 22 ). ACCORD aggressively targeted HbA1c < 6.0%, rapidly dropping 1.7% in 4 months, yet increased mortality by 22% after 3.5 years, prompting early termination. while nonfatal MI decreased, ischemic stroke showed no benefit and severe hypoglycemia was 3 fold higher, demonstrating rapid intensive lowering risks outweigh CV benefits in high risk T2DM ( 23 ). Type1 diabetes conferred 2.54 fold risk for ischemic stroke and 1.88 fold risk for hemorrhagic stroke vs controls, while type2 diabetes showed 1.37 folded ischemic stroke risk without hemorrhagic stroke excess.HbA1c thresholds differed:type1 diabetes ischemic stroke risk rose at > 6.9%;type 2 hemorrhagic stroke only at > 7.9% ( 24 ). Among 359,783 stroke patients,28% had diabetes (ischemic:33%, hemorrhagic:26%). Diabetes linked to poorer functional outcomes and higher mortality post stroke. Elevated HbA1c independently predicated increased stroke severity, mortality rates, and recurrence risk, confirming diabetes as high prevalence comorbidity worsening stroke prognosis ( 4 ). In acute ischemic stroke patients,HbA1c > 6.5% markedly increased risk of severe stroke (high NIHSS scores),with risk escalating at HbA1c > 8.0%.each 1% HbA1c increase correlated with higher stroke severity independent of acute hyperglycemia, age, and comorbidities, establishing chronic poor glycemic control as a key determinant of worse neurological impairment at presentation ( 25 ). 21% of 2.8 million Beijing diabetics had stroke, facing higher rates of hypertension, coronary disease, dyslipidemia, respiratory issues, and osteoporosis vs non stroke diabetics. Medical costs rose 40%(13,400 yuan/year diabetes plus stroke vs 9,600yuan diabetes alone),with stroke amplifying medication burden and complications through comorbidity synergy ( 26 ). Tian et al., in a cohort study, showed that an increase in HbA1c baseline was associated with a 10% higher risk of stroke ( 27 ). They had a different method, but it resulted in a similar conclusion to ours. Results of a previous study that investigated both diabetic and non-diabetic patients demonstrated that a rise in HbA1c could be an independent risk factor for stroke ( 28 ). In a case-control study between non diabetics in Pakistani people, the HbA1c value in the stroke group was significantly higher, and they also reported that Patients with the highest HbA1c levels were almost 8 times more likely to experience an ischemic stroke compared with those with the lowest levels, and determined HbA1c as a predictive factor for stroke ( 13 ). In a previous study that evaluated risk factors of stroke in diabetic patients, they did not find a significant association between HbA1c levels and stroke. Nevertheless, the fasting blood glucose in the stroke group was significantly higher than the group without stroke ( 29 ). Our study shows that higher HbA1c levels are associated with a raised risk of stroke. Recognizing the HbA1c level that puts patients at higher risk of stroke can help clinicians focus on better glycemic control. Therefore, keeping HbA1c within safe ranges may play an important role in preventing strokes. Conclusion Elevated HbA1c levels exceeding 8% among diabetic patients appear to significantly cause prominent elevation in ischemic stroke occurrence risk, whereas maintaining HbA1c within the 6.8 to 7.0% range accompany with less potential risk for ischemic stroke events; an alarming preventive recommendation, to be noticed for better prevention of possible diabetes acute ischemic cerebrovascular accident attacks. More studies with larger sample volume should be established to clarify the precise Hb A1c cut of point which directly effect on increasing related complications. Declarations Conflict of interest: There is no conflict of interest to declare. Acknowledgement: We Thank Clinical Research Development Unit, Golestan Hospital< Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran for their supports. References Russo MP, Grande-Ratti MF, Burgos MA, Molaro AA, Bonella MB (2023) Prevalencia de diabetes, características epidemiológicas y complicaciones vasculares. Arch Cardiol Mex 93(1):30–36 Mosenzon O, Cheng AY, Rabinstein AA, Sacco S (2023) Diabetes and Stroke: What Are the Connections? J Stroke 25(1):26–38 Kernan WN, Forman R, Inzucchi SE (2023) Caring for Patients With Diabetes in Stroke Neurology. Stroke 54(3):894–904 Lau L-H, Lew J, Borschmann K, Thijs V, Ekinci EI (2019) Prevalence of diabetes and its effects on stroke outcomes: A meta-analysis and literature review. J Diabetes Investig 10(3):780–792 Global (2021) regional, and national burden of stroke and its risk factors, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Neurol 20(10):795–820 Feigin VL, Brainin M, Norrving B, Martins SO, Pandian J, Lindsay P et al (2025) World Stroke Organization: Global Stroke Fact Sheet 2025. Int J Stroke 20(2):132–144 Feigin VL, Owolabi MO (2023) Pragmatic solutions to reduce the global burden of stroke: a World Stroke Organization-Lancet Neurology Commission. Lancet Neurol 22(12):1160–1206 9 (2025) Pharmacologic Approaches to Glycemic Treatment: Standards of Care in Diabetes-2025. Diabetes Care 48(1 Suppl 1):S181–S206 O'Donnell MJ, Chin SL, Rangarajan S, Xavier D, Liu L, Zhang H et al (2016) Global and regional effects of potentially modifiable risk factors associated with acute stroke in 32 countries (INTERSTROKE): a case-control study. Lancet 388(10046):761–775 Kitagawa K, Yamamoto Y, Arima H, Maeda T, Sunami N, Kanzawa T et al (2019) Effect of Standard vs Intensive Blood Pressure Control on the Risk of Recurrent Stroke: A Randomized Clinical Trial and Meta-analysis. JAMA Neurol 76(11):1309–1318 Patel A, MacMahon S, Chalmers J, Neal B, Billot L, Woodward M et al (2008) Intensive blood glucose control and vascular outcomes in patients with type 2 diabetes. N Engl J Med 358(24):2560–2572 Holman RR, Paul SK, Bethel MA, Matthews DR, Neil HAW (2008) 10-year follow-up of intensive glucose control in type 2 diabetes. N Engl J Med 359(15):1577–1589 Nomani AZ, Nabi S, Ahmed S, Iqbal M, Rajput HM, Rao S (2016) High HbA1c is associated with higher risk of ischaemic stroke in Pakistani population without diabetes. Stroke Vasc Neurol 1(3):133–139 Zafar A, Albakr A, Shahid R, Alkhamis F, Alabdali M, Aljaafari D et al (2023) Association between glycated hemoglobin and functional outcomes in patients with intracranial large artery atherosclerotic disease-related acute ischemic stroke: identifying the magic number. Front Neurol 14:1249535 Ovbiagele B (2010) SWEET-FIX: a quality improvement initiative for hospitalized stroke patients with undiagnosed diabetes or prediabetes. Crit Pathw Cardiol 9(4):185–191 Bao Y, Gu D (2021) Glycated Hemoglobin as a Marker for Predicting Outcomes of Patients With Stroke (Ischemic and Hemorrhagic): A Systematic Review and Meta-Analysis. Front Neurol 12:642899 Jeong J, Park JK, Koh YH, Park J-M, Bae H-J, Yun S-M (2023) Association of HbA1c with functional outcome by ischemic stroke subtypes and age. Front Neurol 14:1247693 Jacobson AM, Musen G, Ryan CM, Silvers N, Cleary P, Waberski B et al (2007) Long-term effect of diabetes and its treatment on cognitive function. N Engl J Med 356(18):1842–1852 Reaven PD, Moritz TE, Schwenke DC, Anderson RJ, Criqui M, Detrano R et al (2009) Intensive glucose-lowering therapy reduces cardiovascular disease events in veterans affairs diabetes trial participants with lower calcified coronary atherosclerosis. Diabetes 58(11):2642–2648 Mitsios JP, Ekinci EI, Mitsios GP, Churilov L, Thijs V (2018) Relationship Between Glycated Hemoglobin and Stroke Risk: A Systematic Review and Meta-Analysis. J Am Heart Assoc ; 7(11) Eight-year weight (2014) losses with an intensive lifestyle intervention: the look AHEAD study. Obes (Silver Spring) 22(1):5–13 Wang H, Cheng Y, Chen S, Li X, Zhu Z, Zhang W (2019) Impact of Elevated Hemoglobin A1c Levels on Functional Outcome in Patients with Acute Ischemic Stroke. J Stroke Cerebrovasc Dis 28(2):470–476 Zhang C-Y, Sun A-J, Zhang S-N, Wu C-n, Fu M-Q, Xia G et al (2010) Effects of intensive glucose control on incidence of cardiovascular events in patients with type 2 diabetes: a meta-analysis. Ann Med 42(4):305–315 Mavridis A, Viktorisson A, Eliasson B, von Euler M, Sunnerhagen KS (2025) Risk of Ischemic and Hemorrhagic Stroke in Individuals With Type 1 and Type 2 Diabetes: A Nationwide Cohort Study in Sweden. Neurology 104(7):e213480 Alhawiti NM, Elsokkary EM, Aldali JA, Alotaibi BA (2025) Investigating the impact of glycated hemoglobin levels on stroke severity in patients with acute ischemic stroke. Sci Rep 15(1):12114 Huang L, Zeng J, Luo Y, Wang H, Zhang Z, Zeng Y (2025) The comorbidity burden of diabetes and stroke: a retrospective study in Beijing, China. BMC Public Health 25(1):546 Tian X, Xia X, Zhang Y, Xu Q, Luo Y, Wang A (2024) Association and pathways of baseline and longitudinal hemoglobin A1c with the risk of incident stroke: A nationwide prospective cohort study. Diabetes Res Clin Pract 208:111127 Selvin E, Coresh J, Shahar E, Zhang L, Steffes M, Sharrett AR (2005) Glycaemia (haemoglobin A1c) and incident ischaemic stroke: the Atherosclerosis Risk in Communities (ARIC) Study. Lancet Neurol 4(12):821–826 Liu J, Li X, Qu J (2023) Risk factors for acute ischemic stroke in patients with type 2 diabetes mellitus. 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Motamed","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5UlEQVRIiWNgGAWjYBACAxQeTwW6CD4tPGDiDMlaeNuI0GLOfvzh5wKGbXL27KcTH7ydd1jenL35AMOPim04tVj25BhLz2C4bczDk7vZcO62w4Y7e44lMPacuY3bYQdyGKR5GG4n9jDkbpPm3XaYccONHANmxjY8Ws4/f/wbrIX/7fbfvHMO2xPWciPBDGKLRO42Zt6Gw4lEaHljZs0D8suNt5sl5xxLT95w5ljCQbx+OZ/++DZQixx7f+7GD29qrG03HG8++OBHBW4tYMD4D85sBpMH8KtHBXWkKB4Fo2AUjIIRAgC5S1toIvSsigAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0001-9062-085X","institution":"Ahvaz Jundishapur University of Medical Sciences: Ahvaz Jondishapour University of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Hassan","middleName":"","lastName":"Motamed","suffix":""},{"id":587777065,"identity":"d645832b-c8a9-485e-8f93-ca3d1a89d7f5","order_by":1,"name":"Poyan Alizadeh","email":"","orcid":"","institution":"Ahvaz Jundishapur University of Medical Sciences: Ahvaz Jondishapour University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Poyan","middleName":"","lastName":"Alizadeh","suffix":""},{"id":587777066,"identity":"f41990fc-11d8-4c79-840d-332cafcb6a78","order_by":2,"name":"Reza Ajodani","email":"","orcid":"","institution":"Ahvaz Jundishapur University of Medical Sciences: Ahvaz Jondishapour University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Reza","middleName":"","lastName":"Ajodani","suffix":""},{"id":587777067,"identity":"fa5f953c-85da-4508-8218-215dc5860912","order_by":3,"name":"Azin Kalantari","email":"","orcid":"","institution":"Ahvaz Jundishapur University of Medical Sciences: Ahvaz Jondishapour University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Azin","middleName":"","lastName":"Kalantari","suffix":""},{"id":587777068,"identity":"7d5d8c0b-70d4-49dc-bbb5-7d8c1dcd57cf","order_by":4,"name":"Arian Kalantari","email":"","orcid":"","institution":"Ahvaz Jundishapur University of Medical Sciences: Ahvaz Jondishapour University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Arian","middleName":"","lastName":"Kalantari","suffix":""},{"id":587777069,"identity":"3e9c1ab8-66f4-4c4c-8982-0801de7b0bc0","order_by":5,"name":"Elham Sadeghi","email":"","orcid":"","institution":"Ahvaz Jundishapur University of Medical Sciences: Ahvaz Jondishapour University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Elham","middleName":"","lastName":"Sadeghi","suffix":""},{"id":587777070,"identity":"a01508ca-c90c-4beb-b8fe-805f717657db","order_by":6,"name":"Mohammadreza Sahrifpor","email":"","orcid":"","institution":"Ahvaz Jundishapur University of Medical Sciences: Ahvaz Jondishapour University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Mohammadreza","middleName":"","lastName":"Sahrifpor","suffix":""},{"id":587777071,"identity":"db101c9f-299d-4b76-ba58-6ec586ba6b82","order_by":7,"name":"Reyhane Jahangir","email":"","orcid":"","institution":"Ahvaz Jundishapur University of Medical Sciences: Ahvaz Jondishapour University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Reyhane","middleName":"","lastName":"Jahangir","suffix":""}],"badges":[],"createdAt":"2026-01-31 16:58:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8751498/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8751498/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102746834,"identity":"a480ba49-34b7-408a-8f6e-5d6c47448ad7","added_by":"auto","created_at":"2026-02-16 09:01:54","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":54809,"visible":true,"origin":"","legend":"\u003cp\u003eParticipant Selection\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8751498/v1/229db1af41c7c7a6c7533a7f.png"},{"id":102529746,"identity":"287b6312-dc72-4ce2-b65e-3ad215a0eaec","added_by":"auto","created_at":"2026-02-12 16:11:27","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":117518,"visible":true,"origin":"","legend":"\u003cp\u003eArea under the ROC curve (AUC)\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8751498/v1/7358d62eaef082806d8e83d2.png"},{"id":105565448,"identity":"3f8921b9-9b17-4603-bb04-b810e2aa2f82","added_by":"auto","created_at":"2026-03-27 12:53:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":610320,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8751498/v1/fc3f3d29-53e1-4d03-86dd-a109be8bc03f.pdf"}],"financialInterests":"","formattedTitle":"Is there any agreed cut off point for serum HbA1c level to be considered as a protective burden for Ischemic Cerebrovascular Accidents occurrence in Diabetics?","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDiabetes mellitus is one of the most common chronic diseases worldwide (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). It is associated with a higher risk of cardiovascular complications, including cerebrovascular accidents (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Studies show that people with diabetes have twice the risk of stroke compared to those without diabetes (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). And about 30% of people with stroke also have diabetes (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). The rise in life expectancy and the aging population have led to an increase in stroke cases. Consequently, over the past 30 years, the total number of people affected by stroke, including deaths and long-term disability, has nearly doubled. Stroke was the second most common cause of death in 2019, with 6.5\u0026nbsp;million mortalities, and the third leading cause of disability, which was responsible for 143\u0026nbsp;million DALYs (Disability Adjusted Life Years) (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). The high rates of stroke-related morbidity result in a substantial economic burden, so that the global cost of stroke is more than US\u003cspan\u003e$\u003c/span\u003e890\u0026nbsp;billion annually (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). It is predicted that the total cost of stroke, including treatment, rehabilitation, and lost income due to disability, could rise from US\u003cspan\u003e$\u003c/span\u003e891\u0026nbsp;billion in 2017 to over US\u003cspan\u003e$\u003c/span\u003e2.3 trillion by 2050. However, this increase could be avoided because stroke is highly preventable (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). People with diabetes face a substantially higher like hood of small vessel damage eye, kidney and nerve disease as well as large artery complications like heart attacks, ischemic stroke and peripheral arterial disease. The chapter summarizes evidence showing that bringing HbA1c into the very low range below roughly 6 to6.5% yields only modest extra microvascular benefit and has limited impact on major macrovascular outcomes such as stroke which are influenced more by global cardiovascular risk and the chronicity of diabetes (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).cardiac conditions, diabetes accounted for a meaningful proportion of the overall burden of stroke at the population level, underscoring its role as a key, but partly preventable, vascular risk factor worldwide (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn a Japanese randomized trial, patients who had experienced a prior stroke were randomly allocated to usual blood pressure targets below 140/90 mm Hg or to more aggressive treatment aiming for values under 120/80 mmHg, then followed for several years to monitor new stroke. the intensive-treatment arm showed fewer recurrent strokes than the standard group, but because the study was stopped early, the reduction was not statistically definitive by itself. however, when these data were combined with earlier intensive vs standard blood pressure studies in a metanalysis, aiming for lower blood pressure(generally\u0026thinsp;\u0026lt;\u0026thinsp;130/80 mmHg)produced a significant roughly one fifth reduction in the overall risk of having another stroke, driven largely by fewer hemorrhagic strokes (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). In a large trial of people with type 2 diabetes, targeting an HbA1c of 6.5% or lower with a gliclazide based regimen lowered average HbA1c to 6.5%,compared with about 7.3% under standard care, corresponding to roughly a 0.8 percentage point difference sustained for 5years.this degree of HbA1c lowering clearly reduced overall major vascular events when microvascular and macrovascular outcomes were combined principally by lowering the risk of nephropathy whereas the impact on major macrovascular events such as myocardial infarction and stroke alone was small and did not reach statistical significance, highlighting that intensive HbA1c reduction primarily benefits microvascular disease in this population (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn patients with type 2 diabetes, maintaining HbA1c about 1 percentage point lower with intensive glucose control (typically near 7% versus close to 8%) for several years leads to lasting clinical benefits, even if this HbA1c difference disappears within about a year after stopping intensive treatment. long-term follow-up demonstrates that those who initially achieved lower HbA1c experience fewer microvascular complications and meaningful reductions in myocardial infarction and all causes mortality, supporting the concept of a durable \u0026ldquo;legacy effect\u0026rdquo; of early tight glycemic control on vascular outcomes (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Having diabetes substantially increased the odds of both ischemic and hemorrhagic stroke roughly in the range of 30%to 100% higher risk after adjusting for other vascular risk factors, with some variation by geographic region and stroke type. When combined with elevated blood pressure, abdominal adiposity, abnormal lipids, smoking. Since strokes related to metabolic risk factors account for 69% of all strokes (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), controlling metabolic diseases such as diabetes can play an important role in reducing the global stroke burden. The current study aims to determine, despite the potential role of diabetes mellitus in cerebrovascular events (ischemic stroke), which HbA1c cut-off increased the risk of cerebrovascular events and which cut-off is safe in terms of cerebrovascular events. This study had been designed with a fucose on HBA1c cut-off point determination compatible with significant increased risk and incidence for ischemic cerebrovascular attacks in diabetes.\u003c/p\u003e"},{"header":"Methods and Materials","content":"\u003cp\u003eThis case-control study took place at Golestan Hospital in Ahvaz, located in the southwest of Iran, between October 2024 and July 2025. diabetic Patients who had been confirmed by a neurologist or an emergency physician to have experienced an acute ischemic stroke at recent 6 hours were considered the case group, while diabetic patients with no history of stroke were considered the control group. The study protocol was approved by the Ethics Committee of Ahvaz University of Medical Sciences (IR.AJUMS.REC.1403.366).\u003c/p\u003e \u003cp\u003eInclusion criteria for the case group were age 18 years or older, the presence of clinical signs of cerebrovascular accident (CVA), such as hemiparesis or aphasia, which occurrence of CVA was confirmed by a registered emergency medicine or a neurologist or imaging (brain CT scan or MRI), and also patients with diabetes, which was confirmed by an endocrinologist or patients as known diabetic cases were enrolled as the case group. Patients older than 18 years who were known diabetic cases without any neurological symptoms were enrolled as the control group.\u003c/p\u003e \u003cp\u003eExclusion criteria for both the case and control group were a lack of patient consent, age below 18 years, a history of hemorrhagic stroke, and neurological symptoms caused by other conditions, such as hypoglycemia, TIA, or other neuropathies.\u003c/p\u003e \u003cp\u003eKnown diabetic patients who were under treatment by an endocrinologist and were admitted to Golestan Hospital during the study period were assessed for eligibility. After applying the inclusion and exclusion criteria, diabetic patients with acute ischemic stroke were included in the case group, and diabetic patients without stroke were included in the control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDemographic and medical information, including age, sex, and history of ischemic heart disease (IHD), hypertension (HTN), dyslipidemia (DLP), and smoking, was collected directly from patients through interviews. Serum HbA1c samples were collected from all patients within the first 24 hours of admission and were measured using the Selectra XL autoanalyzer. This procedure did not interfere with the standard management of CVA; all patients received the necessary treatment according to established clinical protocols, and it did not incur any additional costs for the patients. the analytic data has been analyzed based on the patients` data to answer this question that how can HbA1c level, influence cerebrovascular risk of ischemic stroke in diabetic patients.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eData were analyzed using SPSS software (version 22). Quantitative variables were reported as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD), while Categorical variables were reported as percentages.\u003c/p\u003e \u003cp\u003eThe normality of continuous variables was assessed using the Shapiro Wilk test, and they were normally distributed. Comparison of quantitative variables between two groups was performed using the t-test. To compare Categorical variables, the Chi-square test was applied.\u003c/p\u003e \u003cp\u003eAdditionally, a logistic regression model was applied to assess the effect of HbA1C on stroke occurrence, and odds ratios (OR) with 95% confidence intervals (CI) were reported.\u003c/p\u003e \u003cp\u003eTo determine the predictive value of HbA1c for stroke, a Receiver Operating Characteristic (ROC) curve was plotted, and the area under the curve (AUC) was calculated. The optimal cut-off point for safe limitation of HbA1c was determined using Youden\u0026rsquo;s Index.\u003c/p\u003e \u003cp\u003eA p-value less than 0.05 was considered statistically significant.\u003c/p\u003e \u003cp\u003eAccording to previous studies (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), the sample size with a power of 80% was calculated as follows: 62 diabetic patients with acute ischemic stroke were enrolled as the case group, and 62 diabetic patients without stroke were enrolled as the control group.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eDemographic and baseline characteristics of both the case and control groups were compared. There were no significant differences between the two groups in age, sex, IHD, HTN, DLP, and smoking. We had 62 diabetic patients with CVA with a mean age of 64.16\u0026thinsp;\u0026plusmn;\u0026thinsp;12.43 (53.2% male and 46.8% female) and 62 diabetic patients without CVA with a mean age of 63.37\u0026thinsp;\u0026plusmn;\u0026thinsp;6.82 (46.8% male and 53.2% female). The medical history was as follows: in the case group, 48.4% had IHD, 59.7% had HTN, 16.1% had DLP, and 40% were smokers, while in the control group, 38% had IHD, 51.6% had HTN, 21% had DLP, and 32.3% were smokers.\u003c/p\u003e \u003cp\u003e(Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic and baseline characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCVA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNon CVA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.16\u0026thinsp;\u0026plusmn;\u0026thinsp;12.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63.37\u0026thinsp;\u0026plusmn;\u0026thinsp;6.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.662\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33(53.2%)\u003c/p\u003e \u003cp\u003e29(46.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29(46.8%)\u003c/p\u003e \u003cp\u003e33(53.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.472\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIHD\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32(51.6%)\u003c/p\u003e \u003cp\u003e30(48.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38(61.3%)\u003c/p\u003e \u003cp\u003e24(38.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.277\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHTN\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25(40.3%)\u003c/p\u003e \u003cp\u003e37(59.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30(48.4%)\u003c/p\u003e \u003cp\u003e32(51.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.366\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDLP\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52(83.9%)\u003c/p\u003e \u003cp\u003e10(16.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49(79%)\u003c/p\u003e \u003cp\u003e13(21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.488\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37(59.7%)\u003c/p\u003e \u003cp\u003e25(40.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42(67.7%)\u003c/p\u003e \u003cp\u003e20(32.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.350\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eCVA: cerebrovascular accident, IHD: ischemic heart disease, HTN: hypertension, DLP: dyslipidemia\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRegarding comparing the HbA1C average between patients with and without CVA, the mean in patients with CVA was 8.21\u0026thinsp;\u0026plusmn;\u0026thinsp;1.70, while in patients without CVA it was 7.56\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28 that which was significantly higher in CVA (p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.02). Using logistic regression, the odds ratio (OR) with a 95% confidence interval was calculated as 1.34(1.05,1.71) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of mean HbA1c levels between patients with and without stroke, and odds ratio.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCVA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon CVA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHbA1C, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.21\u0026thinsp;\u0026plusmn;\u0026thinsp;1.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.56\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.34 (1.05,1.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eCVA: cerebrovascular accident, OR: odds ratio, CI: confidence interval\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTo investigate the predictive value of HbA1c for an increase in the risk of CVA occurrence, the ROC curve was plotted, and the AUC with 95% CI (0.516,0.694) was calculated as 0.608 (p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.036) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eROC curve analysis of the predictive value of HbA1c for stroke\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0.608\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.516,0.694)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eAUC: area under the curve, CI: confidence interval\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWe used the Youden index to determine the optimal HbA1c range for CVA risk, considering sensitivity as 69.35 and specificity as 35.48; the cut-off point for HbA1c was 6.8 (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe optimal HbA1c cutoff for predicting CVA according to the Youden index with selective sensitivity and specificity\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCutoff value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e93.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e88.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e69.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e59.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e53.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eSeveral studies have assessed differences in mean HbA1c levels between individuals with and without stroke, but the findings have been inconsistent. In addition, only a few studies have demonstrated the predictive value of HbA1c for stroke or identified the specific levels that put patients at higher risk. In this study, we show that the HbA1c mean in diabetic patients with stroke was significantly higher than diabetic patients without stroke. An odds ratio of 1.3 indicates 30% higher odds of stroke occurrence among patients with higher HbA1c levels. Also, we demonstrated that HbA1c can be a predictive factor for stroke incidence, so that patients with HbA1c higher than 6.8 were more likely to experience a stroke compared with those with lower levels. In a recent study, Zafar et al. found that HbA1c levels higher than 6.9 were associated with worse functional outcomes after stroke, which is similar to our results and concordant with the necessity of glycemic control (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Analysis of nearly 5,000 individuals living with diabetes who had survived a previous stroke or TIA revealed that keeping HbA1c levels precisely between 6.8% and 7.0% offered the best protection against future ischemic brain events or heart attacks. Compared to this sweet spot, Diabetic patients whose HbA1c fell below 6.8% or climbed above 7.0% faced substantially greater chances of experiencing another stroke during follow-up. The pattern indicated steadily worsening odds of recurrent ischemic stroke as HbA1c rose beyond 7.0% while unexpectedly low readings under 6.0% also correlated with poorer outcomes, forming a U-shaped relationship where HbA1c around 6.8% to 7.0% represented the safest zone for preventing repeat cerebrovascular accidents in this high risk diabetic population (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eResearchers synthesized data from 13 studies involving 12,810 individuals who experienced stroke, predominantly ischemic cases (10,131) versus hemorrhagic (2,679), To assess HbA1c thresholds of under 6.5% the 6.5\u0026ndash;8.2% band, and readings exceeding 8.2%. Individuals surpassing the 6.5% mark demonstrated substantially diminished functional recovery (OR 1.86 for mRS 3\u0026ndash;6 at 3 months) and elevated death rates relative to those below this level. A clear gradient emerged in the dose response pattern, where climbing past 6.5% steadily worsened prognosis, reaching peak risk for adverse outcomes and mortality among ischemic stroke patients when HbA1c topped 8.2% (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). GBD 2019 investigators quantified stroke disability worldwide by linking it to fasting glucose elevations, a reliable proxy for HbA1c\u0026thinsp;\u0026ge;\u0026thinsp;7.0 across every country over three decades. This metabolic risk factor placed sixth among all stroke causes globally, accounting for nearly 10% of ischemic stroke cases by 2019.among diabetic populations specifically, higher chronic glucose readings tied directly to greater ischemic stroke rates, with risk attribution surging 76% in working age groups(15\u0026ndash;59 years)during the study timeframe, positioning sustained hyperglycemia as a prime target for preventing ischemic brain events on a global scale (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Among 7,380 patients with acute ischemic stroke, those with HbA1c\u0026thinsp;\u0026ge;\u0026thinsp;6.5% faced higher odds of unfavorable functional status at 3months compared toHbA1c\u0026thinsp;\u0026lt;\u0026thinsp;5.7%.in younger adults(\u0026lt;\u0026thinsp;65yearsold)with small vessel disease, elevated HbA1c\u0026thinsp;\u0026ge;\u0026thinsp;6.5%markedly worsened both short term and long term outcomes, while the link was weaker or absent in other stroke subtypes and older patients (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). In an 18 years period follow-up of type1 diabetes` patients intensive glucose lowering maintained mean HbA1c around 7.4% (vs 9.0% in conventional care) without causing cognitive impairment, even with higher severe hypoglycemia rates in the intensive arm. neuropsychological testing across multiple domains showed no deterioration attributable to intensive treatment or recurrent hypoglycemia, indicating that sustained lower HbA1c over nearly two decades preserves cognitive function in longstanding type1 diabetes (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Among 301 participants, intensive glucose lowering dropped HbA1c by about 1.4 percentage points and cut CVD events by 89% specifically in those with minimal coronary calcification. Preexisting calcified atherosclerosis determines intensive glycemic therapy effectiveness (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Analyzing 532,779 participants across 29 studies,HbA1c\u0026thinsp;\u0026ge;\u0026thinsp;6.5% doubled first ever stroke risk versus \u0026lt;\u0026thinsp;5.7%.each 1 percentage point HbA1c rise increased stroke odds by 17% among diabetics and 12% in nondiabetics with ischemic stroke showing even stronger links 24% higher per 1% in diabetes and 49% in nondiabetic groups (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). In a trial, intensive lifestyle intervention among overweight and obese adults with type2 diabetes achieved HbA1c reductions of 0.3 to 0.5% alongside 4.7% mean 8 years weight loss, yet demonstrated no overall cardiovascular benefit including ischemic stroke within the primary composite endpoint. Critically, baseline HbA1c stratified outcomes: patients with HbA1c\u0026thinsp;\u0026lt;\u0026thinsp;6.8% experienced cardio protection, those with 6.8% to 8.7% showed neutral effects, while HbA1c\u0026thinsp;\u0026gt;\u0026thinsp;8.6% faced increased risk, indicating that lifestyle intervention\u0026rsquo;s vascular benefits including ischemic stroke prevention are limited to patients with relatively well controlled baseline glycemia (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAmong 1,293 acute ischemic stroke patients, admission HbA1c\u0026thinsp;\u0026ge;\u0026thinsp;6.5% predicted 1.82 fold higher odds of unfavorable 90 day functional status compared to HbA1c\u0026thinsp;\u0026lt;\u0026thinsp;6.5%.every 1 percentage point HbA1c elevation independently increased poor outcomes risk by 25% after stroke severity adjustment (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). ACCORD aggressively targeted HbA1c\u0026thinsp;\u0026lt;\u0026thinsp;6.0%, rapidly dropping 1.7% in 4 months, yet increased mortality by 22% after 3.5 years, prompting early termination. while nonfatal MI decreased, ischemic stroke showed no benefit and severe hypoglycemia was 3 fold higher, demonstrating rapid intensive lowering risks outweigh CV benefits in high risk T2DM (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Type1 diabetes conferred 2.54 fold risk for ischemic stroke and 1.88 fold risk for hemorrhagic stroke vs controls, while type2 diabetes showed 1.37 folded ischemic stroke risk without hemorrhagic stroke excess.HbA1c thresholds differed:type1 diabetes ischemic stroke risk rose at \u0026gt;\u0026thinsp;6.9%;type 2 hemorrhagic stroke only at \u0026gt;\u0026thinsp;7.9% (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Among 359,783 stroke patients,28% had diabetes (ischemic:33%, hemorrhagic:26%). Diabetes linked to poorer functional outcomes and higher mortality post stroke. Elevated HbA1c independently predicated increased stroke severity, mortality rates, and recurrence risk, confirming diabetes as high prevalence comorbidity worsening stroke prognosis (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). In acute ischemic stroke patients,HbA1c\u0026thinsp;\u0026gt;\u0026thinsp;6.5% markedly increased risk of severe stroke (high NIHSS scores),with risk escalating at HbA1c\u0026thinsp;\u0026gt;\u0026thinsp;8.0%.each 1% HbA1c increase correlated with higher stroke severity independent of acute hyperglycemia, age, and comorbidities, establishing chronic poor glycemic control as a key determinant of worse neurological impairment at presentation (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). 21% of 2.8\u0026nbsp;million Beijing diabetics had stroke, facing higher rates of hypertension, coronary disease, dyslipidemia, respiratory issues, and osteoporosis vs non stroke diabetics. Medical costs rose 40%(13,400 yuan/year diabetes plus stroke vs 9,600yuan diabetes alone),with stroke amplifying medication burden and complications through comorbidity synergy (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Tian et al., in a cohort study, showed that an increase in HbA1c baseline was associated with a 10% higher risk of stroke (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). They had a different method, but it resulted in a similar conclusion to ours. Results of a previous study that investigated both diabetic and non-diabetic patients demonstrated that a rise in HbA1c could be an independent risk factor for stroke (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). In a case-control study between non diabetics in Pakistani people, the HbA1c value in the stroke group was significantly higher, and they also reported that Patients with the highest HbA1c levels were almost 8 times more likely to experience an ischemic stroke compared with those with the lowest levels, and determined HbA1c as a predictive factor for stroke (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn a previous study that evaluated risk factors of stroke in diabetic patients, they did not find a significant association between HbA1c levels and stroke. Nevertheless, the fasting blood glucose in the stroke group was significantly higher than the group without stroke (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur study shows that higher HbA1c levels are associated with a raised risk of stroke. Recognizing the HbA1c level that puts patients at higher risk of stroke can help clinicians focus on better glycemic control. Therefore, keeping HbA1c within safe ranges may play an important role in preventing strokes.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eElevated HbA1c levels exceeding 8% among diabetic patients appear to significantly cause prominent elevation in ischemic stroke occurrence risk, whereas maintaining HbA1c within the 6.8 to 7.0% range accompany with less potential risk for ischemic stroke events; an alarming preventive recommendation, to be noticed for better prevention of possible diabetes acute ischemic cerebrovascular accident attacks. More studies with larger sample volume should be established to clarify the precise Hb A1c cut of point which directly effect on increasing related complications.\u003c/p\u003e"},{"header":"Declarations","content":" \u003ch2\u003eConflict of interest:\u003c/h2\u003e \u003cp\u003eThere is no conflict of interest to declare.\u003c/p\u003e\u003ch2\u003eAcknowledgement:\u003c/h2\u003e \u003cp\u003eWe Thank Clinical Research Development Unit, Golestan Hospital\u0026lt; Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran for their supports.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRusso MP, Grande-Ratti MF, Burgos MA, Molaro AA, Bonella MB (2023) Prevalencia de diabetes, caracter\u0026iacute;sticas epidemiol\u0026oacute;gicas y complicaciones vasculares. Arch Cardiol Mex 93(1):30\u0026ndash;36\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMosenzon O, Cheng AY, Rabinstein AA, Sacco S (2023) Diabetes and Stroke: What Are the Connections? J Stroke 25(1):26\u0026ndash;38\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKernan WN, Forman R, Inzucchi SE (2023) Caring for Patients With Diabetes in Stroke Neurology. Stroke 54(3):894\u0026ndash;904\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLau L-H, Lew J, Borschmann K, Thijs V, Ekinci EI (2019) Prevalence of diabetes and its effects on stroke outcomes: A meta-analysis and literature review. J Diabetes Investig 10(3):780\u0026ndash;792\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGlobal (2021) regional, and national burden of stroke and its risk factors, 1990\u0026ndash;2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Neurol 20(10):795\u0026ndash;820\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFeigin VL, Brainin M, Norrving B, Martins SO, Pandian J, Lindsay P et al (2025) World Stroke Organization: Global Stroke Fact Sheet 2025. Int J Stroke 20(2):132\u0026ndash;144\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFeigin VL, Owolabi MO (2023) Pragmatic solutions to reduce the global burden of stroke: a World Stroke Organization-Lancet Neurology Commission. Lancet Neurol 22(12):1160\u0026ndash;1206\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e9 (2025) Pharmacologic Approaches to Glycemic Treatment: Standards of Care in Diabetes-2025. Diabetes Care 48(1 Suppl 1):S181\u0026ndash;S206\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eO'Donnell MJ, Chin SL, Rangarajan S, Xavier D, Liu L, Zhang H et al (2016) Global and regional effects of potentially modifiable risk factors associated with acute stroke in 32 countries (INTERSTROKE): a case-control study. Lancet 388(10046):761\u0026ndash;775\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKitagawa K, Yamamoto Y, Arima H, Maeda T, Sunami N, Kanzawa T et al (2019) Effect of Standard vs Intensive Blood Pressure Control on the Risk of Recurrent Stroke: A Randomized Clinical Trial and Meta-analysis. JAMA Neurol 76(11):1309\u0026ndash;1318\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePatel A, MacMahon S, Chalmers J, Neal B, Billot L, Woodward M et al (2008) Intensive blood glucose control and vascular outcomes in patients with type 2 diabetes. N Engl J Med 358(24):2560\u0026ndash;2572\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHolman RR, Paul SK, Bethel MA, Matthews DR, Neil HAW (2008) 10-year follow-up of intensive glucose control in type 2 diabetes. N Engl J Med 359(15):1577\u0026ndash;1589\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNomani AZ, Nabi S, Ahmed S, Iqbal M, Rajput HM, Rao S (2016) High HbA1c is associated with higher risk of ischaemic stroke in Pakistani population without diabetes. Stroke Vasc Neurol 1(3):133\u0026ndash;139\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZafar A, Albakr A, Shahid R, Alkhamis F, Alabdali M, Aljaafari D et al (2023) Association between glycated hemoglobin and functional outcomes in patients with intracranial large artery atherosclerotic disease-related acute ischemic stroke: identifying the magic number. Front Neurol 14:1249535\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOvbiagele B (2010) SWEET-FIX: a quality improvement initiative for hospitalized stroke patients with undiagnosed diabetes or prediabetes. Crit Pathw Cardiol 9(4):185\u0026ndash;191\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBao Y, Gu D (2021) Glycated Hemoglobin as a Marker for Predicting Outcomes of Patients With Stroke (Ischemic and Hemorrhagic): A Systematic Review and Meta-Analysis. Front Neurol 12:642899\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJeong J, Park JK, Koh YH, Park J-M, Bae H-J, Yun S-M (2023) Association of HbA1c with functional outcome by ischemic stroke subtypes and age. Front Neurol 14:1247693\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJacobson AM, Musen G, Ryan CM, Silvers N, Cleary P, Waberski B et al (2007) Long-term effect of diabetes and its treatment on cognitive function. N Engl J Med 356(18):1842\u0026ndash;1852\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eReaven PD, Moritz TE, Schwenke DC, Anderson RJ, Criqui M, Detrano R et al (2009) Intensive glucose-lowering therapy reduces cardiovascular disease events in veterans affairs diabetes trial participants with lower calcified coronary atherosclerosis. Diabetes 58(11):2642\u0026ndash;2648\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMitsios JP, Ekinci EI, Mitsios GP, Churilov L, Thijs V (2018) Relationship Between Glycated Hemoglobin and Stroke Risk: A Systematic Review and Meta-Analysis. J Am Heart Assoc ; 7(11)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEight-year weight (2014) losses with an intensive lifestyle intervention: the look AHEAD study. Obes (Silver Spring) 22(1):5\u0026ndash;13\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang H, Cheng Y, Chen S, Li X, Zhu Z, Zhang W (2019) Impact of Elevated Hemoglobin A1c Levels on Functional Outcome in Patients with Acute Ischemic Stroke. J Stroke Cerebrovasc Dis 28(2):470\u0026ndash;476\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang C-Y, Sun A-J, Zhang S-N, Wu C-n, Fu M-Q, Xia G et al (2010) Effects of intensive glucose control on incidence of cardiovascular events in patients with type 2 diabetes: a meta-analysis. Ann Med 42(4):305\u0026ndash;315\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMavridis A, Viktorisson A, Eliasson B, von Euler M, Sunnerhagen KS (2025) Risk of Ischemic and Hemorrhagic Stroke in Individuals With Type 1 and Type 2 Diabetes: A Nationwide Cohort Study in Sweden. Neurology 104(7):e213480\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlhawiti NM, Elsokkary EM, Aldali JA, Alotaibi BA (2025) Investigating the impact of glycated hemoglobin levels on stroke severity in patients with acute ischemic stroke. Sci Rep 15(1):12114\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuang L, Zeng J, Luo Y, Wang H, Zhang Z, Zeng Y (2025) The comorbidity burden of diabetes and stroke: a retrospective study in Beijing, China. BMC Public Health 25(1):546\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTian X, Xia X, Zhang Y, Xu Q, Luo Y, Wang A (2024) Association and pathways of baseline and longitudinal hemoglobin A1c with the risk of incident stroke: A nationwide prospective cohort study. Diabetes Res Clin Pract 208:111127\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSelvin E, Coresh J, Shahar E, Zhang L, Steffes M, Sharrett AR (2005) Glycaemia (haemoglobin A1c) and incident ischaemic stroke: the Atherosclerosis Risk in Communities (ARIC) Study. Lancet Neurol 4(12):821\u0026ndash;826\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu J, Li X, Qu J (2023) Risk factors for acute ischemic stroke in patients with type 2 diabetes mellitus. Med (Baltim) 102(47):e36114\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8751498/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8751498/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Introduction\n\nDiabetes mellitus is one of the most common chronic diseases worldwide. It associated with a higher risk of cardiovascular complications, including cerebrovascular accidents. Studies show that people with diabetes have twice the risk of stroke compared to those without diabetes. The high rates of stroke-related morbidity result in a substantial economic burden. In patients with type 2 diabetes, maintaining HbA1c about 1 percentage point lower with intensive glucose control for several years leads to lasting clinical benefits. The current study aims to determine, despite the potential role of diabetes mellitus in cerebrovascular events (ischemic stroke), which HbA1c cut-off increased the risk of cerebrovascular events and which cut-off is safe in terms of cerebrovascular events. This study had been designed with a fucose on HBA1c cut-off point determination compatible with significant increased risk and incidence for ischemic cerebrovascular attacks in diabetes.\n\nMethods and Materials\n\nDiabetic patients of more than 18 years old who had clinical symptoms and signs of an acute ischemic stroke in recent 6 hours which have been confirmed subsequently by cranial neuroimaging of Computed Tomography Scan or Magnetic Resonance Imaging by an emergency medicine specialist or a neurologist, were included in the study, while diabetic patients with no history of stroke were considered the control group. Serum HbA1c level has been evaluated for both groups. Data has been analyzed to evaluate correlation of serum HbA1c level cut-off with risk of cerebrovascular ischemic stroke in diabetics. Sample size with a power of 80% was calculated 62 diabetic patients with acute ischemic stroke and 62 diabetic patients without stroke as control group.\n\nResults\n\nDemographic and baseline characteristics of both the case and control groups were compared. There were no significant differences between the two groups in age, sex, IHD, HTN, DLP, and smoking. We had 62 diabetic patients with CVA with a mean age of 64.16±12.43 and 62 diabetic patients without CVA with a mean age of 63.37±6.82. Regarding comparing the HbA1C average between patients with and without CVA, the mean in patients with CVA was 8.21 ±1.70, while in patients without CVA it was 7.56 ±1.28 that which was significantly higher in CVA (p-value \u0026lt;0.02). Using logistic regression, the odds ratio (OR) with a 95% confidence interval was calculated as 1.34 (1.05,1.71). The predictive value of HbA1c for an increase in the risk of CVA occurrence was determined by ROC curve plotting; an AUC with 95% CI (0.516,0.694) was calculated 0.608 (p-value\u0026lt;0.036). Youden index for optimal HbA1c range for CVA risk, considering sensitivity as 69.35 and specificity as 35.48; showed a HbA1c cut-off point of 6.8.\n\nDiscussion\n\nSeveral studies have assessed differences in mean HbA1c levels between individuals with and without stroke, but the findings have been inconsistent. In addition, only a few studies have demonstrated the predictive value of HbA1c for stroke or identified the specific levels that put patients at higher risk. In this study, we show that the HbA1c mean in diabetic patients with stroke was significantly higher than diabetic patients without stroke. Having diabetes substantially increased the odds of ischemic stroke roughly in the range of 30%to 100% higher risk after adjusting for other vascular risk factors. In a trial, patients with HbA1c\u0026lt;6.8% experienced cardio protection, those with 6.8% to 8.7% showed neutral effects, while HbA1c\u0026gt;8.6% faced increased risk, indicating that lifestyle intervention’s vascular benefits including ischemic stroke prevention are limited to patients with relatively well controlled baseline glycemia. Our study shows that higher HbA1c levels are associated with a raised risk of stroke. Recognizing the HbA1c level that puts patients at higher risk of stroke can help clinicians focus on better glycemic control. Therefore, keeping HbA1c within safe ranges may play an important role in preventing strokes.\n\nConclusion\n\nElevated HbA1c levels exceeding 8% among diabetic patients appear to significantly cause prominent elevation in ischemic stroke occurrence risk, whereas maintaining HbA1c within the 6.8 to 7.0% range accompany with less potential risk for ischemic stroke events.","manuscriptTitle":"Is there any agreed cut off point for serum HbA1c level to be considered as a protective burden for Ischemic Cerebrovascular Accidents occurrence in Diabetics?","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-12 16:10:45","doi":"10.21203/rs.3.rs-8751498/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"30d784cf-16c9-494c-b540-5073d657defb","owner":[],"postedDate":"February 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-25T17:29:35+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-12 16:10:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8751498","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8751498","identity":"rs-8751498","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}