Management Of Diabetic Patients Research Articles

Current status of percutaneous coronary interventions in diabetics with multivessel disease - is it time to challenge FREEDOM?

Diabetes mellitus (DM) and coronary artery disease (CAD) are the leading causes of death in the world. Over the last two decades, clinical trials have indicated that DM patients with CAD have poorer cardiac outcomes than non-diabetic patients with CAD. The pivotal findings of the FREEDOM trial greatly impacted the way clinicians approached revascularisation in diabetic patients with multivessel disease (MVD). However, since the publication of the FREEDOM trial, much has changed both in percutaneous coronary intervention (PCI) technology, as well as in the management of diabetes. This review provides insights into advancements in stent technology, enhanced patient management strategies, improved clinical outcomes with newer hypoglycaemic agents, current approaches to antiplatelet therapy, and advances in lipid management in diabetic patients. The influence of patient-specific factors such as comorbidities and anatomical complexities on treatment decisions in diabetic patients with MVD is also discussed. The ongoing TUXEDO-2 India trial was designed to primarily compare the clinical outcomes of PCI with the new-generation ultrathin-strut Supraflex Cruz stent, compared to the second-generation XIENCE stent in the setting of contemporary optimal medical therapy in Indian diabetic patients with MVD. The secondary objective of this study is to compare clinical outcomes in the combined group from both study arms against a performance goal derived from the coronary artery bypass grafting (CABG) arm of the FREEDOM trial (historical cohort). The tertiary objective is to compare the efficacy and safety of ticagrelor versus prasugrel in diabetic patients with MVD. In view of recent advances in PCI and medical therapy since the FREEDOM trial, now is an appropriate time to revisit the results of CABG versus PCI in diabetic patients with MVD.

Impact of physical activity and diet counseling on the management of Type-2 Diabetic patients undergoing vitamin D supplementation: A Follow-up Study

Impact of physical activity and diet counseling on the management of Type-2 Diabetic patients undergoing vitamin D supplementation: A Follow-up Study

Continuous Glucose Monitoring in Intensive Care Unit Patients with Diabetes: Insights and Outcomes from a Single-center Study in India

Abstract Introduction: The use of continuous glucose monitoring (CGM) for in-hospital glucose control has been widely studied. However, its application in intensive care unit (ICU) settings is debatable owing to its perceived limitations. In ICU patients with diabetes, glycemic excursions, including frequent hypoglycemic episodes, are more prevalent. This retrospective study was undertaken to evaluate the utility of CGM in the management of diabetes patients admitted to the ICU. Methods: We collected data of patients with diabetes mellitus who were admitted to the ICU at our institution and were advised CGM by the intensivist. A retrospective analysis was conducted, examining demographic, clinical, and laboratory data, along with glucose meter readings and CGM data. The results are presented as numbers, percentages, or median values, as appropriate. Results: Out of 65 patients in the ICU, the median values of percentage time in range, time below range, and time above range were 59%, 2%, and 36%, respectively. The median HbA1C and capillary glucose on admission were 8.8% and 246 mg/dl, respectively. During the ICU stay, the CGM derived average glucose level was 167 mg/dl (percent coefficient of variation [%CV] =25.96) and the glucose management indicator was 7%. In total, 65 episodes of hypoglycemia were detected, all confirmed by capillary glucose tests. A total of 27 patients experienced hypoglycemia, of which 12 had nocturnal hypoglycemia. Conclusion: The use of CGM in the ICU improved glycemic control and helped to detect hypoglycemia, particularly nocturnal with acceptably low glycemic variability as measured by percentage CV. Further studies are required to corroborate and confirm these findings.

The Impact of Hand Strength on HbA1c, Body Mass Index and Body Composition by Group According to Sedentary Behaviour: Cross-Sectional Study in Japanese Patients with Type 2 Diabetes Mellitus.

The impact of hand strength in consideration of sedentary behaviour on diabetes management in patients with type 2 diabetes mellitus (T2DM) is unclear. The purpose of this study was to examine the impact of hand strength on HbA1c, body mass index (BMI) and body composition by group according to the duration of sedentary behaviour in Japanese patients with T2DM. In this retrospective, cross-sectional, single-centre study, hand strength standardised by bodyweight (GS) and sedentary time (ST), were obtained and analysed in a total of 270 Japanese T2DM outpatients in 2021. After dividing the patients into four categories of median values (high and low GS, and long and short ST), odds ratios (ORs) for good control of HbA1c, BMI, waist circumference (WC) and intra-abdominal fat (IAF) were investigated using logistic regression models. The high GS/short ST group was found to have a significantly higher (OR = 2.01; 95% CI: 1.00, 4.03; P = 0.049) for controlled HbA1c compared with that of the low GS/long ST group. The high GS/short ST and the high GS/long ST groups had significantly higher ORs for controlled BMI, WC and IAF compared with the OR of the low GS/long ST group. In addition, the ORs were significantly increased with a positive trend in order from low GS/long ST, low GS/short ST, high GS/long ST, to high GS/short ST in all models (P < 0.001 for trend). Hand strength, with modest effects from sedentary behaviour, could be helpful for diabetes management in T2DM patients.

Recent Advances in Glycemic Management for Hospitalized Diabetic Patients

With the increase in the number of diabetic patients, hospitalized diabetes management has become very important. During hospitalization, diabetic patients are prone to high or low blood glucose levels, which pose significant risks and challenges for treatment and recovery. Therefore, glycemic management of diabetic patients during hospitalization is critical. This article reviews the latest research progress in glycemic management of hospitalized diabetic patients from several aspects, develops individualized treatment plans, and uses various methods to manage and control blood glucose in hospitalized diabetic patients.

Network of doctors for multimorbidity and diabetes — the NOMAD intervention: protocol for feasibility trial of multidisciplinary team conferences for people with diabetes and multimorbidity

BackgroundThe prevalence of diabetes and coexisting multimorbidity rises worldwide. Treatment of this patient group can be complex. Providing an evidence-based, coherent, and patient-centred treatment of patients with multimorbidity poses a challenge in healthcare systems, which are typically designed to deliver disease-specific care. We propose an intervention comprising multidisciplinary team conferences (MDTs) to address this issue. The MDT consists of medical specialists in five different specialities meeting to discuss multimorbid diabetes patients. This protocol describes a feasibility test of MDTs designed to coordinate care and improve quality of life for people with diabetes and multimorbidity.MethodsA mixed-methods one-arm feasibility test of the MDT. Feasibility will be assessed through prospectively collected data. We will explore patient perspectives through patient-reported outcomes (PROs) and assess the feasibility of electronic questionnaires. Feasibility outcomes are recruitment, PRO completion, technical difficulties, impact of MDT, and doctor preparation time. During 17 months, up to 112 participants will be recruited. We will report results narratively and by the use of descriptive statistics. The collected data will form the basis for a future large-scale randomised trial.DiscussionA multidisciplinary approach focusing on better management of diabetic patients suffering from multimorbidity may improve functional status, quality of life, and health outcomes. Multimorbidity and diabetes are highly prevalent in our healthcare system, but we lack a solid evidence-based approach to patient-centred care for these patients. This study represents the initial steps towards building such evidence. The concept can be efficiency tested in a randomised setting, if found feasible to intervention providers and receivers. If not, we will have gained experience on how to manage diabetes and multimorbidity as well as organisational aspects, which together may generate hypotheses for research on how to handle multimorbidity in the future.Administrative informationProtocol version: 01Trial registrationNCT05913726 — registration date: 21 June 2023

Multifunctional nanomaterials for smart wearable diabetic healthcare devices

Wearable diabetic healthcare devices have attracted great attention for real-time continuous glucose monitoring (CGM) using biofluids such as tears, sweat, saliva, and interstitial fluid via noninvasive ways. In response to the escalating global demand for CGM, these devices enable proactive management and intervention of diabetic patients with incorporated drug delivery systems (DDSs). In this context, multifunctional nanomaterials can trigger the development of innovative sensing and management platforms to facilitate real-time selective glucose monitoring with remarkable sensitivity, on-demand drug delivery, and wireless power and data transmission. The seamless integration into wearable devices ensures patient's compliance. This comprehensive review evaluates the multifaceted roles of these materials in wearable diabetic healthcare devices, comparing their glucose sensing capabilities with conventionally available glucometers and CGM devices, and finally outlines the merits, limitations, and prospects of these devices. This review would serve as a valuable resource, elucidating the intricate functions of nanomaterials for the successful development of advanced wearable devices in diabetes management.

Influence of sleep quality and other associated factors on glycemic control among diabetic patients: A hospital-based study

The glycemic control of diabetes patients is influenced by a variety of risk factors, some of which are adjustable and others of which are not. Diabetes and sleep quality are most frequently correlated in both directions. To evaluate the quality of sleep and pinpoint the risk factors for inadequate glycemic control in individuals with diabetes. : This cross-sectional study included seventy consecutive patients who met the inclusion criteria. The Pittsburgh Sleep Quality Index (PSQI) scale was used to evaluate the quality of sleep. Siemens- ID 29984, dimension RxL Max, Architect plus ABBOT (ci 4100), completely automatic seven-part cell-counter by Horiba Pentra Dx and Siemens ADVIA Centaur XPT (Immonoassay system) were utilized for the biochemical tests.: Of the 70 participants in the study, 22 patients [31.4%] reported having good sleep quality, while 15 patients [21.4%] had average sleep quality and 33 patients [47.1%] had poor sleep quality. Patients with managed and uncontrolled blood sugar showed varying degrees of sleep quality; 48.4% and 17.9% showed good sleep quality, 29% and 15.4% showed moderate sleep quality, and 22.6% and 66.7% showed poor sleep quality. A statistically significant difference (p&amp;#60;0.001) was seen in the sleep quality of the two groups. : In summary, the results of our study suggested that diabetics with poor sleep quality are more likely to have poor glycemic control. A significant modifiable risk factor for improved glycemic management in diabetic patients is sleep quality.

Healthcare utilisation by diabetic patients in Denmark: the role of primary care in reducing emergency visits

Improving the management of diabetic patients is receiving increasing attention in the health policy agenda due to increasing prevalence in the population and raising pressure on healthcare resources. This paper examines the determinants of healthcare services utilisation in patients with type-2 diabetes, investigating the potential substitution effect of general practice visits on the utilisation of emergency department visits. By using rich longitudinal data from Denmark and a bivariate econometric model, our analysis highlights primary care services that are more effective in preventing emergency department visits and socioeconomic groups of patients with a weak substitution response. Our results suggest that empowering primary care services, such as preventive assessment visits, may contribute to reducing emergency department visits significantly. Moreover, special attention should be devoted to vulnerable groups, such as patients from low socioeconomic background and older patients, who may find more difficult achieving a large substitution response.

The Effect of Glucagon-Like Peptide-1 Receptor Agonists on Diabetic Retinopathy at a Tertiary Care Center

The potential association between diabetic retinopathy (DR) worsening and glucagon-like peptide-1 receptor agonists (GLP-1RA) has affected therapeutic management of diabetic patients but remains controversial. This study compared rates of DR development or progression in patients on GLP-1RA to those on SGLT-2 inhibitors (SGLT-2I). Retrospective cohort study. Nine hundred eighty-one patients with diabetes mellitus taking GLP-1RA or SGLT-2I, the latter serving as controls, between 2012 and2023. Patients were one-to-one greedy matched by propensity scores on race/ethnicity, age, smoking status, baseline body mass index and hemoglobin A1c %, type of diabetes mellitus, baseline DR status and history of DR procedures, duration of drug use, whether they had taken both drug types, and change in hemoglobin A1c % after 1year on the drug. The primary outcome was clinical DR development or progression (termed "worsening") detected by International Classification of Diseases (ICD), 10th edition codes, confirmed by manual review, on GLP-1RA compared with SGLT-2I after propensity score matching. Secondary outcomes included DR worsening indicated by need for procedures due to complications, and time-to-first DR worsening event. The study included 692 GLP-1RA users and 289 SGLT-2I users. The mean follow-up periods for GLP-1RA versus SGLT-2I use were 1.54 (standard deviation [SD] 1.82) years and 1.38 (SD 1.56) years, respectively. The rates of clinical worsening were 2.3% and 2.8%, respectively. After propensity score matching, an association was not identified between GLP1-RA and DR worsening neither clinically by ICD-10 codes (odds ratio [OR]=0.33, 95% confidence interval [CI]: 0.11-1.03) nor by indication for procedures (OR=0.50, 95% CI 0.13-2.00). Time-to-first DR worsening did not differ between the groups in Kaplan-Meier analysis. The most common type of clinical worsening event for both drug types was vitreous hemorrhage (43.7% and 50% of worsening events in GLP-1RA and SGLT-2I users, respectively). The most common DR procedure indicated was anti-VEGF injections (34% and 35% of GLP-1RA and SGLT-2I events, respectively). Diabetic retinopathy worsening, either clinically or by procedures, was not associated with GLP-1RA compared with SGLT-2I, both before and after propensity score matching on all analyses, including time-to-first worsening event. Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

A Scoping Review of Studies Using Artificial Intelligence Identifying Optimal Practice Patterns for Inpatients With Type 2 Diabetes That Lead to Positive Healthcare Outcomes

The objective of this scoping review was to survey the literature on the use of AI/ML applications in analyzing inpatient EHR data to identify bundles of care (groupings of interventions). If evidence suggested AI/ML models could determine bundles, the review aimed to explore whether implementing these interventions as bundles reduced practice pattern variance and positively impacted patient care outcomes for inpatients with T2DM. Six databases were searched for articles published from January 1, 2000, to January 1, 2024. Nine studies met criteria and were summarized by aims, outcome measures, clinical or practice implications, AI/ML model types, study variables, and AI/ML model outcomes. A variety of AI/ML models were used. Multiple data sources were leveraged to train the models, resulting in varying impacts on practice patterns and outcomes. Studies included aims across 4 thematic areas to address: therapeutic patterns of care, analysis of treatment pathways and their constraints, dashboard development for clinical decision support, and medication optimization and prescription pattern mining. Multiple disparate data sources (i.e., prescription payment data) were leveraged outside of those traditionally available within EHR databases. Notably missing was the use of holistic multidisciplinary data (i.e., nursing and ancillary) to train AI/ML models. AI/ML can assist in identifying the appropriateness of specific interventions to manage diabetic care and support adherence to efficacious treatment pathways if the appropriate data are incorporated into AI/ML design. Additional data sources beyond the EHR are needed to provide more complete data to develop AI/ML models that effectively discern meaningful clinical patterns. Further study is needed to better address nursing care using AI/ML to support effective inpatient diabetes management.

Physicians’ Knowledge from Different Religious Background on Management of Diabetic Patients during Ramadan Fasting in Saudi Arabia

The objective of this study is to assesses the knowledge of physicians about basic facts of Ramadan and their ability to give health guidance for diabetic patients to people who are funding and changing their wishing to fast during Ramadan. We studied the knowledge of physicians on Ramadan fasting as a religious duty and impact of some social practices on the fasting diabetic patients. The sample included all the non-Muslim physicians working in different hospitals and health care centers in Najran. Data was collected over a period of one month. This was a quasi-experimental study where non-Muslim physicians were questioned on their knowledge and advice they give to diabetic patients and professional practice of physicians, pre and post a focus group intervention. There were 52 non-Muslim physicians most of the respondents (55.8%) see more than five diabetic patients per week in Ramadan, who had some enquires relevant to Ramadan fasting. Major source of information on Ramadan fasting was through personal communication with Muslim colleagues. Factors that impair diabetic control include cessation of medications, self-modification of dose, increase in consumption of sugar and increased physical activity. We conclude that physicians in Saudi Arabia lack basic religious knowledge on Ramadan that influences health and disease. By simple measures such as distributing written teaching materials or focused group discussions, we can empower their abilities to provide efficient advice to diabetic patients wishing to observe Ramadan fasting.

Assessing LDL Cholesterol Management and Statin Use in Diabetic Patients: Disparities and Outcomes in a Vietnamese Tertiary Hospital Setting

Assessing LDL Cholesterol Management and Statin Use in Diabetic Patients: Disparities and Outcomes in a Vietnamese Tertiary Hospital Setting

SGLT2i impact on HCC incidence in patients with fatty liver disease and diabetes: a nation-wide cohort study in South Korea.

This study evaluated the effect of sodium-glucose cotransporter-2 inhibitors (SGLT2i) on cancer development, particularly in hepatocellular carcinoma (HCC), in individuals with concomitant fatty liver disease (FLD) and type 2 diabetes mellitus (T2DM). Using data from Korea's Health Insurance Review and Assessment Service, we performed Kaplan-Meier and Cox regression analyses in patients with non-alcoholic fatty liver disease (NAFLD) and T2DM (NAFLD-T2DM cohort) and those with chronic viral hepatitis (CVH) alongside FLD and T2DM (FLD-T2DM-CVH cohort). In the propensity score (PS) matched NAFLD-T2DM cohort (N = 107,972), SGLT2i use was not associated with the occurrence of overall cancer, including HCC. However, old age, male sex, liver cirrhosis, and hypothyroidism were identified as independent risk factors for HCC occurrence, whereas statin and fibrate usage were associated with reduced HCC risk in this cohort in multivariate Cox analysis. In the PS-matched FLD-T2DM-CVH cohort (N = 2798), a significant decrease in HCC occurrence was observed among SGLT2i users (P = 0.03). This finding remained consistent in the multivariate Cox regression analysis (Hazard ratio = 2.21, 95% confidence interval = 1.01-4.85, P = 0.048). In conclusion, SGLT2i may be a beneficial option for diabetes management in patients with concomitant T2DM, FLD, and CVH while affirming the overall safety of SGLT2i in other types of cancer.

Continuous glucose monitoring for glycaemic control and cardiovascular risk reduction in patients with type 2 diabetes not on insulin therapy: A clinical trial.

To evaluate the impact of the Dexcom G6 continuous glucose monitoring (CGM) device on glycaemic control and cardiometabolic risk in patients with type 2 diabetes mellitus (T2DM) at high cardiovascular risk who are not on insulin therapy. Adults with T2DM with glycated haemoglobin (HbA1c) >7% and body mass index (BMI) ≥30 kg/m2 not using insulin were enrolled in a two-phase cross-over study. In phase 1, CGM data were blinded, and participants performed standard glucose self-monitoring. In phase 2, the CGM data were unblinded, and CGM, demographic and cardiovascular risk factor data were collected through 90 days of follow-up and compared using paired tests. Forty-seven participants were included (44% women; 34% Black; mean age 63 years; BMI 37 kg/m2; HbA1c 8.4%; 10-year predicted atherosclerotic cardiovascular disease risk 24.0%). CGM use was associated with a reduction in average glucose (184.0 to 147.2 mg/dl, p < .001), an increase in time in range (57.8 to 82.8%, p < .001) and a trend towards lower glucose variability (26.2 to 23.8%). There were significant reductions in HbA1c, BMI, triglycerides, blood pressure, total cholesterol, diabetes distress and 10-year predicted risk for atherosclerotic cardiovascular disease (p < .05 for all) and an increase in prescriptions for sodium-glucose cotransporter 2 inhibitors (36.2 to 83.0%) and glucagon-like peptide-1 receptor agonists (42.5 to 87.2%, p < .001 for both). Dexcom G6 CGM was associated with improved glycaemic control and cardiometabolic risk in patients with T2DM who were not on insulin. CGM can be a safe and effective tool to improve diabetes management in patients at high risk for adverse cardiovascular outcomes.

The impact of diabetes on physical and mental health status and patient satisfaction after total hip and knee arthroplasty.

To assess the impact of diabetes on physical and mental health status, as well as patient satisfaction, one-year following knee and hip total joint arthroplasty (TJA) for osteoarthritis (OA). Participants were 626 hip and 754 knee TJA patients. Pre-surgery data were collected on socio-demographics and health status. The 12-item Short Form Health Survey (SF-12) was collected pre- and one year post-surgery, and physical (PCS) and mental component (MCS) summary scores computed. One-year patient satisfaction was also recorded. Four regression models tested the effect of diabetes on: 1) PCS change score; 2) MCS change score; 3) achieving minimal clinically important improvement (MCII) on PCS; and 4) patient satisfaction ('Somewhat or Very Satisfied' vs. 'Somewhat or Very Dissatisfied'). An interaction between surgical joint and diabetes was tested in each model. Self-reported diabetes prevalence was 13.0% (95% CI: 11.2%-14.7%) and was more common in knee 16.1% (95% CI: 13.4%-18.7%) than hip 9.3% (95% CI: 7.0%-11.5%) patients. In adjusted analyses, change scores were 2.3 units less on the PCS for those with diabetes compared to those without (p = 0.005). Patients with diabetes were about half as likely to achieve MCII as patients without diabetes (p = 0.004). Diabetes was not significantly associated with satisfaction or changes in MCS scores. Diabetes effects did not differ by surgical joint. Findings support that diabetes has a negative impact on improvements in physical health after TJA. Considering the growing prevalence of OA and diabetes in the population, our findings support the importance of perioperative screening and management of diabetes in patients undergoing TJA.

Painful forms of diabetic neuropathy

Diabetic neuropathy is a frequent and severe degenerative complication of diabetes. The diagnosis is easily performed in painful symptomatic patients. Sensitivity disorders responsible for numbness, tingling, and loss of feeling are part and parcel of diabetic foot syndrome and require investigation in view of preventing trophic ulcers. To date, there exists no specific treatment for diabetic neuropathy possibly preventable by careful control of metabolic disorder. Effective management of diabetic patients would make it possible to limit the dramatic consequences of diabetic neuropathy while at the same time acting on other complications.

Nursing Strategies for Diabetic Patient Management: Predicting Parameter Values Post-Exenatide Treatment with Machine Learning Algorithm

The global escalation of DM parallels the rise in obesity rates, with Turkey experiencing a prevalence of 13.7% for diabetes and 32% for obesity among adults. Managing diabetic patients necessitates a comprehensive approach due to the intertwined nature of diabetes and obesity, along with the heightened risk of additional chronic illnesses. Diabet nurses play a pivotal role in diabetic care, encompassing regular assessments, blood glucose monitoring, medication management, patient education. Incretin-mimetic glucagon-like peptide-1 receptor-agonists (GLP-1A) have demonstrated superiority in diabetes, weight control, positioning them as second-line treatments. Weight management remains fundamental in diabetes care, with Diabet nurses providing vital support through dietary guidance, physical activity promotion, and weight loss assistance for diabetic patients. Predicting patient responses to GLP-1A therapy is crucial for optimizing treatment outcomes, streamlining decisions, averting potential complications. Artificial intelligence (AI) and machine learning (ML) offer promising avenues for enhancing healthcare delivery. Our study aimed to forecast fasting blood sugar levels, HbA1C values, and weight loss outcomes in diabetic patients using exenatide, utilizing the random forest algorithm. Analyzing real patient data from the Western-Mediterranean, this study achieved substantial success rates of %99.9, %99.9 and %97.3 in predicting weight loss, fasting blood sugar levels, and HbA1C values, respectively. Our findings underscore the potential of AI-driven approaches in nursing, particularly in prognostic modeling for diabetic patient management. By leveraging ML, nurses can anticipate treatment responses, streamline decision-making, and elevate patient care quality. As AI applications evolve, integrating these technologies into nursing roles promises to advance patient-centered care and optimize health outcomes.

Using nonlinear auto-regressive with exogenous input neural network (NNARX) in blood glucose prediction

BackgroundPredicting of future blood glucose (BG) concentration is important for diabetes control. Many automatic BG monitoring or controlling systems use BG predictors. The accuracy of the prediction for long prediction time is a major factor affecting the performance of the control system. The predicted BG can be used for glycemia management in the form of early hypoglycemic/hyperglycemic alarms or adjusting insulin injections. Recent developments in continuous glucose monitoring (CGM) devices open new opportunities for glycemia management of diabetic patients. Many of those systems need prediction for long prediction horizons to avoid going through hypo or hyperglycemia.MethodsIn this article a nonlinear autoregressive exogenous input neural network (NNARX) is proposed to predict the glucose concentration for longer prediction horizons (PHs) than that was obtained previously with an established recurrent neural network (RNN). The proposed NNARX is a modified version from our previously published RNN with different initialization and building technique but has the same architecture. The modification is based on starting with building nonlinear autoregressive exogenous input model using MATLAB and train it, then close the loop to get NNARX network.ResultsThe results of using the proposed NNARX indicate that the proposed NNARX is better in prediction and stability than unmodified RNN as PH becomes higher than 45 minutes.ConclusionsModification in RNN building extends the ability of the prediction till 100 minutes. It performs statistically significant improvements in the FIT and RMSE values for 100 minutes prediction. It also decreases root mean squared error (RMSE) for both 45 and 60 minutes of prediction.

Pancreatic surgery and tertiary pancreatitis services warrant provision for support from a specialist diabetes team

Pancreatic surgery units undertake several complex operations, albeit with considerable morbidity and mortality, as is the case for the management of complicated acute pancreatitis or chronic pancreatitis. The centralisation of pancreatic surgery services, with the development of designated large-volume centres, has contributed to significantly improved outcomes. In this editorial, we discuss the complex associations between diabetes mellitus (DM) and pancreatic/periampullary disease in the context of pancreatic surgery and overall management of complex pancreatitis, highlighting the consequential needs and the indispensable role of specialist diabetes teams in support of tertiary pancreatic services. Type 3c pancreatogenic DM, refers to DM developing in the setting of exocrine pancreatic disease, and its identification and management can be challenging, while the glycaemic control of such patients may affect their course of treatment and outcome. Adequate preoperative diabetes assessment is warranted to aid identification of patients who are likely to need commencement or escalation of glucose lowering therapy in the postoperative period. The incidence of new onset diabetes after pancreatic resection is widely variable in the literature, and depends on the type and extent of pancreatic resection, as is the case with pancreatic parenchymal loss in the context of severe pancreatitis. Early involvement of a specialist diabetes team is essential to ensure a holistic management. In the current era, large volume pancreatic surgery services commonly abide by the principles of enhanced recovery after surgery, with inclusion of provisions for optimisation of the perioperative glycaemic control, to improve outcomes. While various guidelines are available to aid perioperative management of DM, auditing and quality improvement platforms have highlighted deficiencies in the perioperative management of diabetic patients and areas of required improvement. The need for perioperative support of diabetic patients by specialist diabetes teams is uniformly underlined, a fact that becomes clearly more prominent at all different stages in the setting of pancreatic surgery and the management of complex pancreatitis. Therefore, pancreatic surgery and tertiary pancreatitis services must be designed with a provision for support from specialist diabetes teams. With the ongoing accumulation of evidence, it would be reasonable to consider the design of specific guidelines for the glycaemic management of these patients.