<h4>Background</h4>Substantial variation in testing rates in adults with hypertension across UK primary care suggest that patients are not receiving optimal monitoring.<h4>Aim</h4>To develop a minimal set of evidence-based blood tests for adults with hypertension.<h4>Design and setting</h4>This was a rapid review, routine data analyses, and consensus study. It was set in primary care.<h4>Method</h4>This study examined the rationale and evidence for tests recommended by guidelines or used commonly in adults with hypertension using stepwise rapid evidence reviews. A consensus group, including clinicians and patients, voted to include or exclude each test in the testing panel based on the evidence. If there was no consensus (>80%), additional evidence was sought through rapid reviews or analyses of primary care records, which was subject to further voting.<h4>Results</h4>Sixteen routinely ordered tests were identified. The study found consistent, good evidence that estimated glomerular filtration rate (eGFR) to detect chronic kidney disease and glycosylated haemoglobin (HbA1c) to detect diabetes is beneficial for patients. The study found no or inconsistent evidence of the benefit of routinely measuring lipids, electrolytes, haemoglobin, thyroid function, clotting biomarkers, calcium, ferritin, folate acid, or vitamin B12. Good evidence was found that there is no benefit in routinely monitoring liver function, inflammation markers, or brain natriuretic peptide.<h4>Conclusion</h4>A minimal set of evidence-based blood tests to monitor adults with hypertension was identified. This panel includes eGFR, HbA1c, potassium, and sodium. Implementing these recommendations could reduce harms associated with unwarranted variation in care. Further research is needed to clarify the role of tests with inconsistent evidence and determine the optimal frequency of testing.

<h4>Background</h4>Gegen Qinlian Decoction (GQD) is frequently used as an adjunctive therapy to metformin for type 2 diabetes mellitus (T2DM), but the certainty and consistency of the supporting clinical evidence remain unclear.<h4>Methods</h4>We searched CNKI, Wanfang Data, PubMed, EMBASE, Web of Science, and the Cochrane Central Register of Controlled Trials from database inception to January 31, 2026. Randomized controlled trials comparing GQD plus metformin with metformin alone in adults with T2DM were included. The primary outcome was glycated hemoglobin (HbA1c), and secondary outcomes were fasting plasma glucose (FPG) and 2-hour postprandial glucose (2hPG). Risk of bias was assessed using the Cochrane RoB 2 tool, and the certainty of evidence was evaluated using the GRADE framework. Random-effects meta-analyses were performed, with the primary analyses based on change-from-baseline values.<h4>Results</h4>Eight randomized controlled trials involving 725 participants were included. In the primary change-score analysis, GQD plus metformin did not show a statistically significant reduction in HbA1c compared with metformin alone (mean difference [MD] = -1.92, 95% confidence interval [CI]: -4.43 to 0.59, P = 0.13). Statistically significant reductions were observed for FPG (MD = -1.08, 95% CI: -1.71 to -0.44, P = 0.0009) and 2hPG (MD = -1.73, 95% CI: -3.05 to -0.42, P = 0.010). However, substantial heterogeneity was present across analyses (I² = 85%-100%), and the certainty of evidence was rated as very low because of risk of bias, inconsistency, and imprecision. Post-treatment sensitivity analyses using all eight trials showed statistically significant reductions in HbA1c, FPG, and 2hPG, but these analyses were also affected by substantial heterogeneity and high risk of bias across the included trials.<h4>Conclusion</h4>Current evidence is insufficient to confirm a reliable clinical benefit of GQD as an adjunct to metformin for T2DM. Although reductions in FPG and Methods: We searched CNKI, Wanfang Data, PubMed, EMBASE, Web of Science, and the Cochrane Central Register of Controlled Trials from database inception to January 31, 2026. Randomized controlled trials comparing GQD plus metformin with metformin alone in adults with T2DM were included. The primary outcome was glycated hemoglobin (HbA1c), and secondary outcomes were fasting plasma glucose (FPG) and 2-hour postprandial glucose (2hPG). Risk of bias was assessed using the Cochrane RoB 2 tool, and the certainty of evidence was evaluated using the GRADE framework. Random-effects meta-analyses were performed, with the primary analyses based on change-from-baseline values. Therefore, the primary analysis did not provide suf ficient evidence to con firm a reliable additional effect of GQD on HbA1c. For the secondary outcomes, the change-score analyses favored GQD plus metformin. Statistically signi ficant reductions were observed for FPG (MD = -1.08, 95% CI -1.71 to -0.44; P = 0.0009) and 2hPG (MD = -1.73, 95% CI -3.05 to -0.42; P = 0.010). These findings were consistent across the tested TABLE 1 Characteristics of the included randomized controlled trials. See Appendix S3 for details GQD, Gegen Qinlian Decoction; I/C, intervention group/control group; HbA1c, glycated hemoglobin; FPG, fasting plasma glucose; 2hPG, 2-hour postp randial glucose. All included studies were conducted in China and reported HbA1c, FPG, and 2hPG. NR, not reported. He et al. 10.3389/fendo.2026.1837588 Frontiers in Endocrinology frontiersin.org06 correlation coefficients. However, heterogeneity remained substan- tial to extreme (I² = 85% –96%), and the analyses were based on a small number of trials. Accordingly, the FPG and 2hPG findings were interpreted as suggestive rather than con firmatory evidence. FIGURE 5 Forest plot for HbA1c (change scores; r = 0.25).Sensitivity analysis of HbA1c change scores using a conservative correlation coef ficient (r) of 0.25 to assess the robustness of the primary outcome. FIGURE 4 Forest plot for HbA1c (change scores; r = 0.50). Meta-analysis of changes from baseline in glycated hemoglobin levels between the combination therapy group and the metformin monotherapy group, assuming a correlation coef ficient (r) of 0.50. He et al. 10.3389/fendo.2026.1837588 Frontiers in Endocrinology frontiersin.org07 tions or hypoglycemic episodes, but the de finitions, timing, severity, causality assessment, and denominators for safety events were not consistently provided. To maintain a focused clinical question, we restricted the review to randomized controlled trials comparing GQD plus metformin with metformin alone and excluded studies involving additional hypoglycemic drugs. Overall, the findings suggest possible improvements in some glycemic parameters, particularly FPG and 2hPG, but the certainty of evidence remains very low because of methodological limitations, substantial heterogeneity, and imprecision. The primary analysis was based on change-from-baseline values and was limited to two trials with sufficient baseline and post-treatment data. HbA1c, glycated hemoglobin; FPG, fasting plasma glucose; 2hPG, 2-hour postprandial glucose; MD, mean difference; CI, con fidence interval; GQD, Gegen Qinlian Decoction; T2DM, type 2 diabetes mellitus; RCTs, randomized controlled trials; GRADE, Grading of Recommendations Assessment, Development and Evaluation. The certainty of evidence was downgraded for risk of bias because of high overall risk-of-bias judgments across the included trials, mainly related t o insufficient reporting of randomization, lack of blinding or placebo control, and absence of prospectively registered protocols. Effect of Gegen Qinlian Decoction on the regulation of gut microbiota and metabolites in type II diabetic rats. Front Microbiol. (2024) 15:1429360. doi: 10.3389/fmicb.2024.1429360 He et al. 10.3389/fendo.2026.1837588 Frontiers in Endocrinology frontiersin.org11

The world has changed tremendously for patients suffering from diabetes mellitus with the development of cutting-edge technologies like continuous glucose monitoring and flash glucose monitoring systems. Now, the details of constant fluctuations of glucose in their blood can be monitored not only by medical professionals but also by patients, and this is called glycemic variability (GV). Traditional metrics of glycemic control measurement, such as glycated hemoglobin (HbA1c), fail to reflect various short-term glycemic changes like postprandial hyperglycemia and hypoglycemic episodes, paving the way to the occurrence of various diabetic complications even in asymptomatic, well-controlled diabetic patients. This need for advanced management of diabetes and effective monitoring of these swings in blood glucose can be met by using a continuous glucose monitoring system (CGMS).To evaluate the extent of GV in well-controlled type 2 diabetes mellitus (T2DM) patients using a flash CGMS and to assess the correlation between GV and HbA1c.A hospital-based prospective observational study was carried out from May 2020 to Oct 2021 at the Department of Medicine, SMS Hospital, Jaipur, Rajasthan (India), after approval from the Ethics Committee of the institution. A total of 30 patients with well-controlled T2DM (HbA1c was ≥6.5, but ≤7.5) were included in the study using simple random techniques after written informed consent from patients. Patients were studied for glycemic excursions over Home | JAPI Title Service Example --> Submit an Article Editor-in-Chief Prof. Dr. Jyotirmoy Pal Vol 74 Issue 8 August 2026 ISSN: 0004-5772 Journal of the Association of Physicians of India is a monthly scientific journal started in 1952. The journal reaches over 23000 members of the Association of Physicians of India every month and benefits millions through the online version. Links About Current Issue Archive APICON Subscribe Social Media Twitter Facebook Instagram Youtube Contact Info Journal of the Association of Physicians of India Unit No. 3301, Tower “D” Prestige Turf Estate, Shakti Mills Compound, Dr. E. Moses Road, Mahalaxmi West, Mumbai – 400011 Maharashtra. Tel: +91 7710020034 Tel: +91 7710029211 Email: onlinejapi@gmail.com © 2025 - japi.org | All Rights Reserved Powered by

<h4>Background</h4>The global prevalence of diabetes among adults aged 29-79 years was found to be 10.5%. It is a global public health threat with a rising trend in morbidity and mortality. Poor glycemic control (GC) among patients with type 2 diabetes mellitus (T2DM) is a major determinant of diabetes-related complications. There are limited data on GC and associated factors among patients with T2DM in South West Region, Cameroon.<h4>Aim</h4>To assess GC and identify contributing factors among patients with T2DM in a regional hospital in South West Region, Cameroon.<h4>Methods</h4>A cross-sectional study was conducted from February 2022 to July 2022 among 131 participants in Limbe Regional Hospital who were selected by convenience. Glycated hemoglobin (HbA1c) was measured by ion-exchange chromatography. Sociodemographic, clinical, and lifestyle data were collected, entered into Excel, and exported to Statistical Package for Social Sciences version 22 for analysis. A multivariate logistic regression analysis was conducted to assess the association between explanatory variables and GC. The level of significance was set at <i>P</i> < 0.05.<h4>Results</h4>The mean age was 56 ± 5.1 years. Eighty-eight (67.2%) patients were female. The mean HbA1c was 8.8% ± 1.8%. Poor GC (HbA1c ≥ 7%) was registered in 106 (80.9%; 95% confidence interval: 73.1%-87.3%) participants. Lack of self-monitoring of blood glucose at home was associated with poor GC (adjusted odds ratio: 3.858, 95% confidence interval: 1.262-11.800; <i>P</i> = 0.018).<h4>Conclusion</h4>The majority of patients with T2DM had poor GC. Absence of self-monitoring of blood glucose at home was the main contributing factor for poor GC. Poor glycemic control (GC) among patients with type 2 diabetes mellitus (T2DM) is a major determinant of diabetes-related complications. There are limited data on GC and associated factors among patients with T2DM in South West Region, Cameroon. AIM To assess GC and identify contributing factors among patients with T2DM in a regional hospital in South West Region, Cameroon. METHODS A cross-sectional study was conducted from February 2022 to July 2022 among 131 participants in Limbe Regional Hospital who were selected by convenience. Glycated hemoglobin (HbA1c) was measured by ion-exchange chromatography. Core Tip: Data on glycemic control (GC) in developing countries, particularly South West Region, Cameroon, are scarce. GC was assessed by measuring glycated hemoglobin and fasting plasma glucose recommended for settings limited in resources. Poor GC was recorded in more than half of the patients with type 2 diabetes mellitus. The findings from this study support clinical practice guidelines recommending the reinforcement of self-monitoring of blood glucose to avoid or lessen the complications of suboptimal GC. Future case-control and longitudinal studies are needed. Type 1 diabetes mellitus is due to inadequate or lack of insulin, and type 2 diabetes mellitus (T2DM) is due to insulin resistance. Glycemic control (GC) refers to the maintenance of blood glucose concentration in a patient with diabetes[ 4 ]. Glycated hemoglobin (HbA1c), postprandial glucose, and fasting plasma glucose (FPG) are markers of GC in patients with T2DM, but HbA1c is the gold standard of GC estimation because it gives the average blood glucose level over the past 3-4 months and indicates whether the treatment plan is working. Higher HbA1c values give an indication of the risk of developing diabetes complications. Table 1 Logistic regression model fit according to Hosmer-Lemeshow test Parameter χ 2 df P value Age 0.000 1 1.000 BMI 0.000 0 Adherence to diet or eating plan 0.000 0 Adherence to diabetic medication 0.000 0 Duration of diabetes mellitus 0.000 0 SMBG 0.000 0 BMI: Body mass index; df : Degrees of freedom; SMBG: Self-monitoring of blood glucose. RESULTS Sociodemographic characteristics of study participants One hundred and thirty-one patients with T2DM were enrolled for this study, 88 (67.2%) of whom were female. The mean age of the respondents was 56 ± 5.1 years. Table 2 Sociodemographic characteristics of patients with type 2 diabetes mellitus attending the Limbe Regional Hospital Parameter Category n (%) Age in years 30-39 9 (6.9) 40-49 33 (25.2) 50-59 30 (22.9) ≥ 60 59 (45.0) Total 131 (100) Marital status Single 23 (17.6) Married 91 (69.5) Divorce 5 (3.8) Widow/widower 12 (9.1) Total 131 (100) Sex Female 88 (67.2) Male 43 (32.8) Total 131 (100) Occupation Formal 13 (9.9) Retired 18 (13.7) Self-employed 96 (73.3) Unemployed 4 (3.1) Total 131 (100) Level of education Primary 48 (36.6) Secondary 58 (44.3) Tertiary 17 (13.0) Informal 8 (6.1) Total 131 (100) Estimated monthly income in CFA franc 5001-10000 1 (0.8) 10001-15000 9 (6.8) 15001-20000 15 (11.5) 20001-25000 79 (60.3) > 25000 27 (20.6) CFA: Communaute Financiere Africaine. Table 4 Factors associated with poor glycemic control among patients with type 2 diabetics attending the Limbe Regional Hospital Parameter Poor GC Good GC Bivariate logistic regression Multivariate logistic regression UOR (95%CI) P value AOR (95%CI) P value Age, years 30-49 28 14 1 1 50-69 65 11 0.230 (0.074-0.711) 0.011 2.819 (0.742-10.718) 0.128 ≥ 70 13 0 0.313 (0.106-0.919) 0.034 2.543 (0.725-8.911) 0.145 Total 106 25 Adherence to diabetic medication(s) Yes 73 23 1 1 No 33 2 0.192 (0.043-0.864) 0.032 3.327 (0.582-19.020) 0.117 Total 106 25 Duration of diabetes mellitus, years 1-11 73 24 1 12-22 33 1 0.092 (0.012-0.710) 0.022 6.527 (0.726-58.667) 0.094 Total 106 25 SMBG Yes 19 11 1 1 No 87 14 0.278 (0.109-0.706) 0.007 3.858 (1.261-11.800) 0.018 Total 106 25 Adherence to diet/eating plan Yes 43 20 1 1 No 63 5 0.171 (0.059-0.490) 0.001 3.437 (0.941-12.559) 0.062 Total 106 25 BMI, kg/m 2 18.5-24.9 17 7 1 1 ≥ 25 89 18 0.491 (0.178-1.356) 0.170 1.483 (0.421-5.228) 0.540 Total 106 25 GC: Glycemic control; UOR: Unadjusted odds ratio; CI: Confidence interval; BMI: Body mass index; SMBG:

Glycation of platelet protein in diabetes mellitus: lack of correlation with platelet function. The relationship of nonenzymatic glycation of platelet proteins to altered platelet function was studied in 33 diabetic patients. Platelets isolated from diabetic patients were glycated to a greater extent than those isolated from nondiabetic controls. No relationship was found between the level of glycation of platelets in diabetics to parameters commonly used to monitor glycemic control (glycated hemoglobin, glycated albumin, fasting blood glucose). Platelets isolated from diabetics did not show an increased level of aggregation and Thromboxane B2 production as compared to nondiabetic controls. No significant relationship was found between the level of glycation and percent aggregation of platelets. The lack of a relationship between glycation and aggregation suggests that the former may not be responsible for the functional changes in platelets seen in diabetics. Published in Clinical biochemistry (1987)

<h4>Objective</h4>The International Diabetes Federation has proposed 1-hour plasma glucose (1-h PG) as a potential indicator for the diagnosis of type 2 diabetes mellitus (T2DM). This study aimed to systematically compare the diagnostic performance of 1-h PG, glycated albumin (GA), fasting plasma glucose (FPG), glycated hemoglobin (HbA1c), and the combined HbA1c-or-FPG strategy for identifying T2DM using a network meta-analysis of diagnostic test accuracy.<h4>Methods</h4>We systematically searched PubMed, Embase, Web of Science, the Cochrane Library, Scopus, and gray literature for studies evaluating the diagnostic accuracy of 1-h PG, GA, FPG ≥126 mg/dL, HbA1c ≥6.5%, and the combined HbA1c-or-FPG strategy for identifying T2DM, with 2-hour plasma glucose (2-h PG) ≥200 mg/dL during the oral glucose tolerance test (OGTT) as the reference standard. Data extraction and quality assessment were performed independently by two reviewers according to predefined criteria. Statistical analyses were conducted using the Stan package in R and Stata 14.0.<h4>Results</h4>A total of 78 studies involving 183,902 participants were included. The network meta-analysis showed that the pooled sensitivity of 1-h PG, GA, FPG, HbA1c, and the combined HbA1c-or-FPG strategy was 0.87 [95% credible interval (CrI), 0.82-0.91], 0.53 (95% CrI, 0.36-0.71), 0.51 (95% CrI, 0.47-0.55), 0.53 (95% CrI, 0.47-0.58), and 0.64 (95% CrI, 0.54-0.73), respectively. The corresponding pooled specificity values were 0.88 (95% CrI, 0.82-0.92), 0.86 (95% CrI, 0.71-0.95), 0.96 (95% CrI, 0.95-0.97), 0.92 (95% CrI, 0.89-0.94), and 0.89 (95% CrI, 0.81-0.95). The pooled positive likelihood ratios (LR+) were 7.68 (95% CrI, 4.97-11.28) for 1-h PG, 4.39 (95% CrI, 1.86-9.30) for GA, 12.63 (95% CrI, 9.33-16.01) for FPG, 6.75 (95% CrI, 4.81-9.05) for HbA1c, and 6.28 (95% CrI, 3.25-11.26) for the combined strategy. The pooled negative likelihood ratios (LR-) were 0.15 (95% CrI, 0.11-0.20), 0.55 (95% CrI, 0.36-0.74), 0.51 (95% CrI, 0.47-0.55), 0.52 (95% CrI, 0.46-0.57), and 0.41 (95% CrI, 0.31-0.53), respectively. The pooled diagnostic odds ratios (DORs) were 52.44 (95% CrI, 30.17-84.00), 8.53 (95% CrI, 2.70-20.94), 24.94 (95% CrI, 17.90-32.30), 13.15 (95% CrI, 8.94-18.51), and 15.83 (95% CrI, 6.62-31.47), respectively. The areas under the summary receiver operating characteristic curves (SROC-AUCs) were 0.757, 0.714, 0.717, 0.706, and 0.726, respectively. Sensitivity analyses restricted to low-risk-of-bias studies and studies using a 1-h PG threshold ≥11.6 mmol/L, as well as subgroup analyses stratified by general and high-risk populations, yielded results and rankings broadly consistent with the primary analysis. Pairwise meta-analysis findings were also generally consistent with those from the network meta-analysis.<h4>Conclusions</h4>Among the evaluated diagnostic measures, 1-h PG appeared to provide the best overall diagnostic performance for T2DM, with the highest sensitivity, lowest LR-, and highest DOR. It performed better overall than GA, FPG, HbA1c, and the combined HbA1c-or-FPG strategy. By contrast, FPG showed the highest specificity and LR +. The consistency of the findings across sensitivity analyses, subgroup analyses, and pairwise meta-analysis supports the robustness of the main results. However, given the residual heterogeneity across included studies in terms of study design, population characteristics, and diagnostic thresholds, these findings should be interpreted with caution and confirmed by further large-scale, high-quality studies.<b>Systematic review registration</b>: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD420261354518.

The HbA1c result was calculated as a ratio to total hemoglobin by HPLC (A1C%). Statistical analysis All results were shown as mean ± standard deviation. P values were based on two-sided tests with a cut off for statistical significance of 0.05. The Chi-square test, The Kolmogorov-Smirnov test and analysis of covariance test were used to evaluate values. All statistical analyses were performed with The MedCalc Statistical Software Version 10.1.6.0 Licensed ti MedCalc Turkey 020931118117. RESULTS Diabetes According to new ADA criteria; we determined 760 diabetic patients among 1814 individuals (41.8%). However, 190 diabetic patients (25.0%) met all ADA criteria. All results are shown in Tables 1 and 2 . 529 diabetic patients (69.6%) were diagnosed by A1c alone, 488 diabetic patients (64.2%) with 2-h OGTT alone, and 328 (43.2%) diabetic patients were diagnosed with FPG alone [ Table 2 ]. Differences between FPG versus 2-h OGTT, FPG versus A1c and OGTT versus A1c were statistically significant ( P &lt; 0.0001, P &lt; 0.0001 and P = 0.02, respectively). Diagnostic sensitivity of all diabetic criteria was 69.6% for A1c; 64.2% for OGTT and only 43.1% for FPG respectively. Table 2. Prediabetes and diabetes frequencies Open in a new tab IFG and glucose intolerance: According to new ADA criteria, of the 1814 subjects tested, 1094 (60,3%) were classified as having IFG, 511 (28.2%) as having IGT following OGTT and 980 (54.0%) as having IGT by A1c. In terms of diagnostic ratio of glucose intolerance; difference between A1c and OGTT was statistically significant ( P &lt; 0.0001) [Tables 2 and 3 ]. Table 3. Distribution of all diabetic patients according to FBG, 2-H OGTT and HbA1c Open in a new tab DISCUSSION An international committee of diabetes experts has recommended that the Hemoglobin A1c assay, now routinely used to monitor the course of the disease in patients with diabetes and signals the pending development of diabetic complications; should become the new “gold standard

We present the case of a 47-year-old Moroccan male with no known history of diabetes who presented with new-onset status epilepticus. His family reported a one-year history of increasing lethargy, polyuria, polydipsia, significant weight loss, and polyphagia. Initial laboratory investigations revealed severe hyperglycemia (547 mg/dL), marked ketosis, and profound metabolic acidosis (bicarbonate level of 9 mmol/L), confirming the diagnosis of severe diabetic ketoacidosis. Further investigations, including an elevated HbA1c level (15.2%), positive anti-glutamic acid decarboxylase (GAD) antibodies (280 IU/mL), and a low fasting C-peptide level (0.06 ng/mL), supported the diagnosis of new-onset latent autoimmune diabetes in adults. Neuroimaging and electroencephalography ruled out other neurological etiologies, supporting diabetic ketoacidosis-induced status epilepticus as the most likely cause. Status epilepticus as the initial manifestation of diabetic ketoacidosis secondary to latent autoimmune diabetes in adults is rare and clinically challenging. Treatment consisted of intravenous fluids, regular insulin, and phenobarbital for seizure control, leading to progressive clinical and biochemical improvement. This case highlights the importance of early metabolic evaluation in adults presenting with new-onset seizures, even in the absence of previously known diabetes, to allow timely diagnosis and prevent severe neurological complications.

Diabetic hyperglycemia provokes glycation of haemoglobin (Hb), an abundant protein in red blood cells (RBCs), by increasing its exposure to carbohydrates. Acetylsalicylic acid (ASA; Aspirin) is one of the first agents, which its antiglycation effect was witnessed. Although the precise molecular mechanism of action of ASA on protein glycation is not indisputably perceived, acetylation as its main molecular mechanism has been proposed. This report aims to unravel the meticulous mechanism of action of ASA by using two ASA analogues; benzoic acid (BA) and para-nitrobenzoic acid (NBA), despite thei