A-Z Diabetes Boot Camp 2026

These papers were sourced and synthesized using Consensus, an AI-powered search engine for research. Try it at https://consensus.app

Oral & Non-Insulin Injectable Medications for Diabetes: Classes, Efficacy, and Clinical Considerations

A wide range of oral and non-insulin injectable medications are available for diabetes management, offering diverse mechanisms, benefits, and safety profiles. These therapies are central to modern diabetes care, especially for type 2 diabetes, and are increasingly used as adjuncts in type 1 diabetes.

Major Classes and Mechanisms

Figure 1: Summary of oral and non-insulin injectable diabetes medications, mechanisms, and risks.

Efficacy and Clinical Outcomes

• GLP-1 Receptor Agonists (GLP-1 RAs): Highly effective for lowering HbA1c, reducing body weight, and lowering cardiovascular risk. Newer agents (e.g., semaglutide, tirzepatide) show the greatest efficacy for glycemic control and weight loss. Oral semaglutide is now available and effective (Nauck et al., 2020; Yao et al., 2024; Sibony et al., 2023; Drucker & Nauck, 2006; Edwards et al., 2022; Fadini et al., 2024; Nauck et al., 2017; Brown et al., 2021; Palmer et al., 2021).
• SGLT2 Inhibitors: Lower glucose, reduce heart failure and kidney disease risk, and lower cardiovascular mortality, especially in patients with established cardiorenal disease (Savarese et al., 2021; Sibony et al., 2023; Van Baar et al., 2018; Brown et al., 2021; Palmer et al., 2021).
• DPP-4 Inhibitors: Modest glucose lowering, weight neutral, low risk of hypoglycemia, but no proven cardiovascular benefit (Drucker & Nauck, 2006; Tran et al., 2015; Nauck et al., 2017; Krentz & Bailey, 2012).
• Metformin: Remains first-line for most, with proven efficacy, safety, and cardiovascular benefit (Sibony et al., 2023; Tran et al., 2015; Krentz & Bailey, 2012).
• Sulfonylureas/Thiazolidinediones: Effective for glycemic control but associated with hypoglycemia, weight gain, and other risks (Tran et al., 2015; Krentz & Bailey, 2012).

Special Populations and Adjunctive Use

• Type 1 Diabetes: Some non-insulin agents (GLP-1 RAs, SGLT2 inhibitors, metformin, amylin analogs) are used off-label as adjuncts to insulin, offering benefits in weight, insulin dose reduction, and glycemic variability, but with increased risk of diabetic ketoacidosis (DKA) for SGLT2 inhibitors (Nabi-Afjadi et al., 2024; Edwards et al., 2022).
• Cardiorenal Disease: GLP-1 RAs and SGLT2 inhibitors are prioritized for patients with cardiovascular or kidney disease due to proven outcome benefits (Savarese et al., 2021; Sibony et al., 2023; Van Baar et al., 2018; Brown et al., 2021; Palmer et al., 2021).

Safety and Tolerability

• GLP-1 RAs: Main side effects are gastrointestinal (nausea, vomiting), with rare risk of pancreatitis. Contraindicated in certain thyroid cancers (Nauck et al., 2020; Yao et al., 2024; Sibony et al., 2023; Drucker & Nauck, 2006; Edwards et al., 2022; Fadini et al., 2024; Nauck et al., 2017; Brown et al., 2021; Palmer et al., 2021).
• SGLT2 Inhibitors: Risk of genital infections and DKA, especially in type 1 diabetes (Savarese et al., 2021; Sibony et al., 2023; Van Baar et al., 2018; Brown et al., 2021; Palmer et al., 2021).
• DPP-4 Inhibitors: Generally well-tolerated, rare risk of pancreatitis and joint pain (Drucker & Nauck, 2006; Tran et al., 2015; Nauck et al., 2017; Krentz & Bailey, 2012).

Summary

Oral and non-insulin injectable medications provide effective, individualized options for diabetes management, with GLP-1 RAs and SGLT2 inhibitors offering the greatest benefits for glycemic control, weight loss, and cardiorenal protection. Drug choice should be tailored to patient comorbidities, preferences, and risk profiles (Nauck et al., 2020; Yao et al., 2024; Savarese et al., 2021; Sibony et al., 2023; Drucker & Nauck, 2006; Edwards et al., 2022; Tran et al., 2015; Van Baar et al., 2018; Fadini et al., 2024; Nauck et al., 2017; Brown et al., 2021; Krentz & Bailey, 2012; Palmer et al., 2021).

These papers were sourced and synthesized using Consensus, an AI-powered search engine for research. Try it at https://consensus.app

References

Nauck, M., Quast, D., Wefers, J., & Meier, J. (2020). GLP-1 receptor agonists in the treatment of type 2 diabetes – state-of-the-art. Molecular Metabolism, 46. https://doi.org/10.1016/j.molmet.2020.101102

Yao, H., Zhang, A., Li, D., Wu, Y., Wang, C., Wan, J., & Yuan, C. (2024). Comparative effectiveness of GLP-1 receptor agonists on glycaemic control, body weight, and lipid profile for type 2 diabetes: systematic review and network meta-analysis. The BMJ, 384. https://doi.org/10.1136/bmj-2023-076410

Savarese, G., Butler, J., Lund, L., Bhatt, D., & Anker, S. (2021). CARDIOVASCULAR EFFECTS OF NON-INSULIN GLUCOSE-LOWERING AGENTS: A COMPREHENSIVE REVIEW OF TRIAL EVIDENCE AND POTENTIAL CARDIOPROTECTIVE MECHANISMS.. Cardiovascular research. https://doi.org/10.1093/cvr/cvab271

Sibony, R., Segev, O., Dor, S., & Raz, I. (2023). Drug Therapies for Diabetes. International Journal of Molecular Sciences, 24. https://doi.org/10.3390/ijms242417147

Drucker, D., & Nauck, M. (2006). The incretin system: glucagon-like peptide-1 receptor agonists and dipeptidyl peptidase-4 inhibitors in type 2 diabetes. The Lancet, 368, 1696-1705. https://doi.org/10.1016/s0140-6736(06)69705-5

Nabi-Afjadi, M., Ostadhadi, S., Liaghat, M., Pasupulla, A., Masoumi, S., Aziziyan, F., Zalpoor, H., Abkhooie, L., & Tarhriz, V. (2024). Revolutionizing type 1 diabetes management: Exploring oral insulin and adjunctive treatments.. Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie, 176, 116808. https://doi.org/10.1016/j.biopha.2024.116808

Edwards, K., Li, X., & Lingvay, I. (2022). Clinical and Safety Outcomes with GLP-1 Receptor Agonists and SGLT2 Inhibitors in Type 1 Diabetes: A Real-World Study.. The Journal of clinical endocrinology and metabolism. https://doi.org/10.1210/clinem/dgac618

Tran, L., Zielinski, A., Roach, A., Jende, J., Householder, A., Cole, E., Atway, S., Amornyard, M., Accursi, M., Shieh, S., & Thompson, E. (2015). Pharmacologic Treatment of Type 2 Diabetes. Annals of Pharmacotherapy, 49, 540 - 556. https://doi.org/10.1177/1060028014558289

Van Baar, M., Van Ruiten, C., Muskiet, M., Van Bloemendaal, L., IJzerman, R., & Van Raalte, D. (2018). SGLT2 Inhibitors in Combination Therapy: From Mechanisms to Clinical Considerations in Type 2 Diabetes Management. Diabetes Care, 41, 1543 - 1556. https://doi.org/10.2337/dc18-0588

Fadini, G., Bonora, B., Ghiani, M., Anichini, R., Melchionda, E., Fattor, B., Fazion, S., Meregalli, G., Giaccari, A., Avogaro, A., & Consoli, A. (2024). Oral or injectable semaglutide for the management of type 2 diabetes in routine care: A multicentre observational study comparing matched cohorts. Diabetes, 26, 2390 - 2400. https://doi.org/10.1111/dom.15554

Nauck, M., Meier, J., Cavender, M., Aziz, M., & Drucker, D. (2017). Cardiovascular Actions and Clinical Outcomes With Glucagon-Like Peptide-1 Receptor Agonists and Dipeptidyl Peptidase-4 Inhibitors. Circulation, 136, 849–870. https://doi.org/10.1161/circulationaha.117.028136

Brown, E., Heerspink, H., Cuthbertson, D., & Wilding, J. (2021). SGLT2 inhibitors and GLP-1 receptor agonists: established and emerging indications. The Lancet, 398, 262-276. https://doi.org/10.1016/s0140-6736(21)00536-5

Krentz, A., & Bailey, C. (2012). Oral Antidiabetic Agents. Drugs, 65, 385-411. https://doi.org/10.2165/00003495-200565030-00005

Palmer, S., Tendal, B., Mustafa, R., et al. (2021). Sodium-glucose cotransporter protein-2 (SGLT-2) inhibitors and glucagon-like peptide-1 (GLP-1) receptor agonists for type 2 diabetes: systematic review and network meta-analysis of randomised controlled trials. The BMJ, 372. https://doi.org/10.1136/bmj.m4573

These papers were sourced and synthesized using Consensus, an AI-powered search engine for research. Try it at https://consensus.app

Insulin: Uses, Mechanisms of Action, and Clinical Advances

Insulin is a vital hormone for glucose regulation and a cornerstone of diabetes therapy. Its clinical use, molecular actions, and evolving formulations have transformed diabetes management for nearly a century.

Physiological Role and Mechanism of Action

• Insulin is secreted by pancreatic β-cells and acts as a key anabolic hormone, lowering blood glucose by promoting glucose uptake in muscle and adipose tissue, stimulating glycogen synthesis in the liver, and inhibiting hepatic glucose production (Rahman et al., 2021; Hirsch et al., 2020).
• Insulin also regulates lipid and protein metabolism, suppresses lipolysis, and promotes fat storage, while coordinating with glucagon to maintain metabolic balance (Rahman et al., 2021; Hirsch et al., 2020).
• Insulin signaling involves binding to the insulin receptor, activating intracellular pathways (notably IRS proteins and Akt), and orchestrating metabolic effects in classic (liver, muscle, adipose) and non-classic (brain, endothelium) tissues (White & Kahn, 2021; Rahman et al., 2021).

Clinical Uses of Insulin

• Type 1 Diabetes: Insulin is essential and lifesaving, replacing the absent endogenous hormone (Sims et al., 2021; Mathieu et al., 2021; Rafi et al., 2025).
• Type 2 Diabetes: Used when oral/non-insulin therapies are insufficient, or in cases of severe hyperglycemia, catabolic states, or during acute illness (Rafi et al., 2025; Cahn et al., 2015).
• Other Indications: Insulin is used in gestational diabetes, steroid-induced hyperglycemia, and critical illness (Rafi et al., 2025; Cahn et al., 2015).

Types and Formulations

• Basal Insulins: Provide steady, long-acting coverage (e.g., glargine, detemir, degludec) to mimic background insulin secretion. Newer analogues offer longer duration, less variability, and reduced hypoglycemia risk (Heise & Mathieu, 2016; Tibaldi, 2014; Owens & Bolli, 2008).
• Prandial (Bolus) Insulins: Rapid- and short-acting insulins (e.g., lispro, aspart, glulisine) control post-meal glucose spikes. Ultra-rapid formulations further improve postprandial control (Owens & Bolli, 2020; De Block et al., 2022; Home, 2012; Heise et al., 2022).
• Premixed and Concentrated Insulins: Combine basal and bolus effects or provide higher doses for severe insulin resistance (Tibaldi, 2014; Sims et al., 2021).
• Innovative Delivery: Inhaled, oral, and once-weekly insulins are in development to improve convenience and mimic physiological patterns (Sims et al., 2021; Cahn et al., 2015).

Advances and Challenges

• Mimicking Physiology: Modern analogues and delivery systems aim to replicate natural insulin secretion, improving glycemic control and reducing hypoglycemia (Heise & Mathieu, 2016; Tibaldi, 2014; Sims et al., 2021; Mathieu et al., 2021; Owens & Bolli, 2008).
• Insulin Resistance: Even in type 1 diabetes, insulin resistance can develop, influenced by lifestyle, exogenous insulin, and metabolic factors. Addressing resistance is key for optimal outcomes (Apostolopoulou et al., 2025; Petersen & Shulman, 2018; White & Kahn, 2021).
• Non-Glycemic Effects: Insulin impacts bone, brain, cardiovascular, and other systems, with research ongoing into its broader physiological and therapeutic roles (White & Kahn, 2021; Rahman et al., 2021).

Types of Insulin and Their Clinical Features

Figure 1: Comparison of insulin types, uses, and clinical features.

Summary

Insulin remains central to diabetes care, with ongoing innovations in formulation and delivery enhancing its ability to mimic natural physiology, improve outcomes, and reduce side effects. Its actions extend beyond glucose control, influencing multiple organ systems and disease processes.

These papers were sourced and synthesized using Consensus, an AI-powered search engine for research. Try it at https://consensus.app

References

Apostolopoulou, M., Lambadiari, V., Roden, M., & Dimitriadis, G. (2025). Insulin Resistance in Type 1 Diabetes: Pathophysiological, Clinical, and Therapeutic Relevance. Endocrine Reviews, 46, 317 - 348. https://doi.org/10.1210/endrev/bnae032

Heise, T., & Mathieu, C. (2016). Impact of the mode of protraction of basal insulin therapies on their pharmacokinetic and pharmacodynamic properties and resulting clinical outcomes. Diabetes, Obesity & Metabolism, 19, 3 - 12. https://doi.org/10.1111/dom.12782

Owens, D., & Bolli, G. (2020). The continuing quest for better subcutaneously administered prandial insulins: a review of recent developments and potential clinical implications. Diabetes, Obesity & Metabolism, 22, 743 - 754. https://doi.org/10.1111/dom.13963

De Block, C., Van Cauwenberghe, J., Bochanen, N., & Dirinck, E. (2022). Rapid-Acting Insulin Analogues: Theory and Best Clinical Practice in Type 1 and Type 2 Diabetes. Diabetes, obesity & metabolism. https://doi.org/10.1111/dom.14713

Petersen, M., & Shulman, G. (2018). Mechanisms of Insulin Action and Insulin Resistance. Physiological reviews, 98 4, 2133-2223. https://doi.org/10.1152/physrev.00063.2017

Home, P. (2012). The pharmacokinetics and pharmacodynamics of rapid‐acting insulin analogues and their clinical consequences. Diabetes, 14. https://doi.org/10.1111/j.1463-1326.2012.01580.x

Tibaldi, J. (2014). Evolution of insulin: from human to analog. The American journal of medicine, 127 10 Suppl, S25-38. https://doi.org/10.1016/j.amjmed.2014.07.005

Hirsch, I., Juneja, R., Beals, J., Antalis, C., & Wright, E. (2020). The Evolution of Insulin and How it Informs Therapy and Treatment Choices. Endocrine Reviews, 41, 733 - 755. https://doi.org/10.1210/endrev/bnaa015

White, M., & Kahn, C. (2021). Insulin action at a molecular level – 100 years of progress. Molecular Metabolism, 52. https://doi.org/10.1016/j.molmet.2021.101304

Sims, E., Carr, A., Oram, R., Dimeglio, L., & Evans-Molina, C. (2021). 100 years of insulin: celebrating the past, present and future of diabetes therapy. Nature Medicine, 27, 1154 - 1164. https://doi.org/10.1038/s41591-021-01418-2

Mathieu, C., Martens, P., & Vangoitsenhoven, R. (2021). One hundred years of insulin therapy. Nature Reviews Endocrinology, 17, 715 - 725. https://doi.org/10.1038/s41574-021-00542-w

Rafi, E., Tranchito, L., & Hatipoglu, B. (2025). Navigating Insulin Options for Diabetes Management. The Journal of clinical endocrinology and metabolism, 110 Supplement_2, S159-S164. https://doi.org/10.1210/clinem/dgae790

Rahman, M., Hossain, K., Das, S., Kundu, S., Adegoke, E., Rahman, M., Hannan, M., Uddin, M., & Pang, M. (2021). Role of Insulin in Health and Disease: An Update. International Journal of Molecular Sciences, 22. https://doi.org/10.3390/ijms22126403

Heise, T., De Oliveira, C., Juneja, R., Ribeiro, A., Chigutsa, F., & Blevins, T. (2022). What is the value of faster acting prandial insulin? Focus on ultra rapid lispro. Diabetes, Obesity & Metabolism, 24, 1689 - 1701. https://doi.org/10.1111/dom.14773

Cahn, A., Miccoli, R., Dardano, A., & Del Prato, S. (2015). New forms of insulin and insulin therapies for the treatment of type 2 diabetes.. The lancet. Diabetes & endocrinology, 3 8, 638-52. https://doi.org/10.1016/s2213-8587(15)00097-2

Owens, D., & Bolli, G. (2008). Beyond the era of NPH insulin--long-acting insulin analogs: chemistry, comparative pharmacology, and clinical application. Diabetes technology & therapeutics, 10 5, 333-49. https://doi.org/10.1089/dia.2008.0023

These papers were sourced and synthesized using Consensus, an AI-powered search engine for research. Try it at https://consensus.app

Insulin Plans for Diabetic Patients: Principles, Regimens, and Personalization

Developing an effective insulin plan for diabetic patients requires individualization based on diabetes type, blood glucose patterns, lifestyle, comorbidities, and patient preferences. Research consistently emphasizes the need for tailored regimens, careful titration, and ongoing adjustment to optimize glycemic control and minimize risks.

Principles of Insulin Planning

• Individualization: Insulin regimens should be customized to each patient’s blood glucose profile, daily routine, and response to therapy. This approach is critical for both type 1 and type 2 diabetes, as patients exhibit diverse patterns of hyperglycemia and insulin sensitivity (Mooradian et al., 2006; Moghissi & King, 2014; Home et al., 2014; Carr et al., 2022).
• Types of Insulin: Modern plans use a combination of basal (long-acting) and bolus (rapid- or short-acting) insulins to mimic physiological insulin secretion. The choice of insulin type and timing is guided by pharmacokinetic properties and patient needs (Mooradian et al., 2006; De Block et al., 2022; Rafi et al., 2025; Dodek et al., 2024; Sugumar et al., 2022; Cahn et al., 2015).
• Initiation and Intensification: Insulin is initiated in type 1 diabetes at diagnosis and in type 2 diabetes when oral agents fail or in cases of severe hyperglycemia, acute illness, or pregnancy. Early and appropriate initiation is associated with better long-term outcomes (Rafi et al., 2025; Moghissi & King, 2014; Lasserson et al., 2009; Home et al., 2014).

Common Insulin Regimens

Figure 1: Comparison of insulin regimens and their clinical features.

Titration and Monitoring

• Dose Adjustment: Insulin doses are titrated based on self-monitored blood glucose or continuous glucose monitoring, with frequent reassessment to achieve individualized glycemic targets and minimize hypoglycemia (Mooradian et al., 2006; Rafi et al., 2025; Lasserson et al., 2009; Korytkowski et al., 2022; Home et al., 2014).
• Technology Integration: Digital tools and AI-based algorithms are emerging to support insulin titration, offering real-time recommendations and potentially improving glycemic control (Wang et al., 2023; Shifrin & Siegelmann, 2020; Kerr et al., 2022).

Special Populations and Considerations

• Children/Adolescents: Basal-bolus regimens with rapid-acting analogues are preferred for flexibility and optimal control (Petersen et al., 2025).
• Pregnancy: Personalized regimens are essential to meet pregnancy-specific glucose targets and accommodate physiological changes (Valent & Barbour, 2024).
• Hospitalized Patients: Insulin is the mainstay for inpatient hyperglycemia, with protocols adapted to clinical context (Pasquel et al., 2021; Korytkowski et al., 2022).

Summary

An optimal insulin plan is highly individualized, combining the right insulin types, dosing schedules, and titration strategies to match each patient’s needs. Ongoing monitoring, patient education, and the use of new technologies are key to achieving safe and effective glycemic control (Mooradian et al., 2006; De Block et al., 2022; Rafi et al., 2025; Wang et al., 2023; Shifrin & Siegelmann, 2020; Moghissi & King, 2014; Pasquel et al., 2021; Valent & Barbour, 2024; Lasserson et al., 2009; Korytkowski et al., 2022; Home et al., 2014; Kerr et al., 2022; Fritsche et al., 2003; Carr et al., 2022; Sugumar et al., 2022; Cahn et al., 2015).

These papers were sourced and synthesized using Consensus, an AI-powered search engine for research. Try it at https://consensus.app

References

Mooradian, A., Bernbaum, M., & Albert, S. (2006). Narrative Review: A Rational Approach to Starting Insulin Therapy. Annals of Internal Medicine, 145, 125-134. https://doi.org/10.7326/0003-4819-145-2-200607180-00010

Petersen, J., Juul, S., Kamp, C., Faltermeier, P., Sillassen, C., Santos, T., & Jakobsen, J. (2025). Regular human insulins versus rapid-acting insulin analogues in children and adolescents with type 1 diabetes: a protocol for a systematic review with meta-analysis and Trial Sequential Analysis. Systematic Reviews, 14. https://doi.org/10.1186/s13643-024-02729-4

De Block, C., Van Cauwenberghe, J., Bochanen, N., & Dirinck, E. (2022). Rapid-Acting Insulin Analogues: Theory and Best Clinical Practice in Type 1 and Type 2 Diabetes. Diabetes, obesity & metabolism. https://doi.org/10.1111/dom.14713

Rafi, E., Tranchito, L., & Hatipoglu, B. (2025). Navigating Insulin Options for Diabetes Management. The Journal of clinical endocrinology and metabolism, 110 Supplement_2, S159-S164. https://doi.org/10.1210/clinem/dgae790

Wang, G., Liu, X., Ying, Z., Yang, G., Chen, Z., Liu, Z., Zhang, M., Yan, H., Lu, Y., Gao, Y., Xue, K., Li, X., & Chen, Y. (2023). Optimized glycemic control of type 2 diabetes with reinforcement learning: a proof-of-concept trial. Nature Medicine, 29, 2633 - 2642. https://doi.org/10.1038/s41591-023-02552-9

Shifrin, M., & Siegelmann, H. (2020). Near-optimal insulin treatment for diabetes patients: A machine learning approach. Artificial intelligence in medicine, 107, 101917. https://doi.org/10.1016/j.artmed.2020.101917

Dodek, M., Miklovičová, E., & Halás, M. (2024). Improving the insulin therapy for diabetic patients using optimal impulsive disturbance rejection: Continuous time approach. Biocybernetics and Biomedical Engineering. https://doi.org/10.1016/j.bbe.2024.05.003

Moghissi, E., & King, A. (2014). Individualizing insulin therapy in the management of type 2 diabetes. The American journal of medicine, 127 10 Suppl, S3-10. https://doi.org/10.1016/j.amjmed.2014.07.002

Pasquel, F., Lansang, M., Dhatariya, K., & Umpierrez, G. (2021). Management of diabetes and hyperglycaemia in the hospital. The lancet. Diabetes & endocrinology. https://doi.org/10.1016/s2213-8587(20)30381-8

Valent, A., & Barbour, L. (2024). Insulin Management for Gestational and Type 2 Diabetes in Pregnancy. Obstetrics & Gynecology, 144, 633 - 647. https://doi.org/10.1097/aog.0000000000005640

Lasserson, D., Glasziou, P., Perera, R., Holman, R., & Farmer, A. (2009). Optimal insulin regimens in type 2 diabetes mellitus: systematic review and meta-analyses. Diabetologia, 52, 1990-2000. https://doi.org/10.1007/s00125-009-1468-7

Korytkowski, M., Muniyappa, R., Antinori-Lent, K., Donihi, A., Drincic, A., Hirsch, I., Luger, A., McDonnell, M., Murad, M., Nielsen, C., Pegg, C., Rushakoff, R., Santesso, N., & Umpierrez, G. (2022). Management of Hyperglycemia in Hospitalized Adult Patients in Non-Critical Care Settings: An Endocrine Society Clinical Practice Guideline. The Journal of clinical endocrinology and metabolism. https://doi.org/10.1210/clinem/dgac278

Home, P., Riddle, M., Cefalu, W., Bailey, C., Bretzel, R., Del Prato, S., Leroith, D., Schernthaner, G., Van Gaal, L., & Raz, I. (2014). Insulin Therapy in People With Type 2 Diabetes: Opportunities and Challenges? Diabetes Care, 37, 1499 - 1508. https://doi.org/10.2337/dc13-2743

Kerr, D., Edelman, S., Vespasiani, G., & Khunti, K. (2022). New digital health technologies for insulin initiation and optimization for people with type 2 diabetes.. Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists. https://doi.org/10.1016/j.eprac.2022.04.006

Fritsche, A., Schweitzer, M., & Hring, H. (2003). Glimepiride Combined with Morning Insulin Glargine, Bedtime Neutral Protamine Hagedorn Insulin, or Bedtime Insulin Glargine in Patients with Type 2 Diabetes. Annals of Internal Medicine, 138, 952-959. https://doi.org/10.7326/0003-4819-138-12-200306170-00006

Carr, A., Evans-Molina, C., & Oram, R. (2022). Precision medicine in type 1 diabetes. Diabetologia, 65, 1854 - 1866. https://doi.org/10.1007/s00125-022-05778-3

Sugumar, V., Ang, K., Alshanon, A., Sethi, G., Yong, P., Looi, C., & Wong, W. (2022). A Comprehensive Review of the Evolution of Insulin Development and Its Delivery Method. Pharmaceutics, 14. https://doi.org/10.3390/pharmaceutics14071406

Cahn, A., Miccoli, R., Dardano, A., & Del Prato, S. (2015). New forms of insulin and insulin therapies for the treatment of type 2 diabetes. The lancet. Diabetes & endocrinology, 3 8, 638-52. https://doi.org/10.1016/s2213-8587(15)00097-2

These papers were sourced and synthesized using Consensus, an AI-powered search engine for research. Try it at https://consensus.app

Screening for Type 1 Diabetes: Methods, Benefits, and Evolving Strategies

Screening for type 1 diabetes (T1DM) is rapidly advancing, with growing evidence supporting early detection through islet autoantibody and genetic testing. Early identification of presymptomatic T1DM can reduce diabetic ketoacidosis (DKA) at diagnosis, enable timely intervention, and potentially delay disease progression.

Screening Methods and Strategies

• Islet Autoantibody Screening: The primary method for early detection involves testing for multiple islet autoantibodies (against insulin, GAD65, IA-2, and ZnT8). Presence of two or more autoantibodies indicates high risk for progression to clinical T1DM (Hoffmann et al., 2025; Bonifacio & Ziegler, 2025; Leichter et al., 2025; Ghalwash et al., 2022; Phillip et al., 2024; Mallone et al., 2024; Sundheim et al., 2025; Ghalwash et al., 2023).
• Optimal Timing: Screening at two ages (e.g., 2 and 6 years) in childhood achieves high sensitivity (up to 82%) and positive predictive value for future T1DM, with most seroconversions occurring before age 6 (Ghalwash et al., 2022). In adolescents, a single screening at age 10 is highly effective, with sensitivity up to 90% (Ghalwash et al., 2023).
• Genetic Risk Scores: Genetic pre-screening (using polygenic risk scores or HLA typing) can identify high-risk individuals for targeted autoantibody testing, though its real-world benefit and cost-effectiveness are still being evaluated (Bonifacio et al., 2025; Mendizabal et al., 2024; Guertin et al., 2024; Qu et al., 2022).
• Combined Approaches: Integrating genetic and autoantibody screening improves predictive accuracy, especially in high-risk or diverse populations (Bonifacio et al., 2025; Ferrat et al., 2020; Qu et al., 2022).

Benefits and Clinical Impact

• Reduced DKA and Improved Outcomes: Early detection through screening programs significantly lowers the risk of DKA at diagnosis and allows for better initial glycemic control, which is linked to improved long-term outcomes (Hoffmann et al., 2025; Phillip et al., 2024; Mallone et al., 2024; Sundheim et al., 2025; Ghalwash et al., 2023).
• Access to Disease-Modifying Therapies: The approval of teplizumab for delaying T1DM onset in stage 2 disease has increased the value of early screening, as eligible individuals can benefit from interventions that slow progression (Bonifacio & Ziegler, 2025; Leichter et al., 2025; Phillip et al., 2024; Simmons & Sims, 2023).
• Education and Monitoring: Screening enables education for families and regular monitoring, which can further reduce complications and support psychosocial well-being (Phillip et al., 2024; Sundheim et al., 2025).

Implementation and Challenges

• Population vs. Targeted Screening: While most new T1DM cases occur in individuals without a family history, targeted screening of first-degree relatives is more efficient but misses the majority of cases. Universal or school-based screening is being piloted in several countries (Hoffmann et al., 2025; Sims et al., 2022; Mallone et al., 2024; Sundheim et al., 2025).
• Barriers: Challenges include cost, infrastructure, participation rates, and the need for standardized protocols and follow-up care (Hoffmann et al., 2025; Bonifacio & Ziegler, 2025; Bonifacio et al., 2025; Sims et al., 2022; Phillip et al., 2024; Guertin et al., 2024; McQueen et al., 2020).
• Monitoring After Positive Screens: Consensus guidelines recommend confirmation of positive results, regular glucose monitoring, education, and psychosocial support for those with early-stage T1DM (Phillip et al., 2024).

Screening Approaches and Outcomes in T1DM

Figure 1: Comparison of T1DM screening methods, populations, and outcomes.

Summary

Screening for T1DM using islet autoantibody and genetic testing is effective for early detection, reducing DKA, and enabling preventive interventions. Ongoing research is refining strategies for broader, cost-effective, and equitable implementation (Hoffmann et al., 2025; Bonifacio & Ziegler, 2025; Bonifacio et al., 2025; Leichter et al., 2025; Ghalwash et al., 2022; Sims et al., 2022; Phillip et al., 2024; Mallone et al., 2024; Guertin et al., 2024; Sundheim et al., 2025; Ghalwash et al., 2023; Ferrat et al., 2020; Qu et al., 2022; McQueen et al., 2020).

These papers were sourced and synthesized using Consensus, an AI-powered search engine for research. Try it at https://consensus.app

References

Hoffmann, L., Kohls, M., Arnolds, S., et al. (2025). EDENT1FI Master Protocol for screening of presymptomatic early-stage type 1 diabetes in children and adolescents. BMJ Open, 15. https://doi.org/10.1136/bmjopen-2024-088522

Bonifacio, E., & Ziegler, A. (2025). Type 1 diabetes risk factors, risk prediction and presymptomatic detection: Evidence and guidance for screening. Diabetes, Obesity & Metabolism, 27, 28 - 39. https://doi.org/10.1111/dom.16354

Bonifacio, E., Coelho, R., Ewald, D., Gemulla, G., Hubmann, M., Jarosz-Chobot, P., Kohls, M., Kordonouri, O., Lampasona, V., Narendran, P., Pociot, F., Šumník, Z., Szypowska, A., Zapardiel-Gonzalo, J., & Ziegler, A. (2025). The efficacy of islet autoantibody screening with or without genetic pre-screening strategies for the identification of presymptomatic type 1 diabetes. Diabetologia, 68, 1101 - 1107. https://doi.org/10.1007/s00125-025-06408-4

Leichter, S., Felton, J., Rasmussen, C., Rizzuto, P., Bellini, N., Ebekozien, O., & Schulman-Rosenbaum, R. (2025). Establishing Screening Programs for Presymptomatic Type 1 Diabetes: Practical Guidance for Diabetes Care Providers. The Journal of Clinical Endocrinology and Metabolism, 110, 2371 - 2382. https://doi.org/10.1210/clinem/dgaf194

Mendizabal, L., Saso-Jiménez, L., Apaolaza, N., Martínez, R., Zulueta, M., Urrutia, I., Simón, L., & Castano, L. (2024). 2002-LB: New Model for Type 1 Diabetes Differential Screening. Diabetes. https://doi.org/10.2337/db24-2002-lb

Ghalwash, M., Dunne, J., Lundgren, M., Rewers, M., Ziegler, A., Anand, V., Toppari, J., Veijola, R., & Hagopian, W. (2022). Two-age islet-autoantibody screening for childhood type 1 diabetes: a prospective cohort study.. The lancet. Diabetes & endocrinology. https://doi.org/10.1016/s2213-8587(22)00141-3

Sims, E., Besser, R., Dayan, C., et al. (2022). Screening for Type 1 Diabetes in the General Population: A Status Report and Perspective.. Diabetes, 71 4, 610-623. https://doi.org/10.2337/dbi20-0054

Phillip, M., Achenbach, P., Addala, A., et al. (2024). Consensus guidance for monitoring individuals with islet autoantibody-positive pre-stage 3 type 1 diabetes. Diabetologia, 67, 1731 - 1759. https://doi.org/10.1007/s00125-024-06205-5

Simmons, K., & Sims, E. (2023). Screening and prevention of type 1 diabetes: Where are we?. The Journal of clinical endocrinology and metabolism. https://doi.org/10.1210/clinem/dgad328

Mallone, R., Bismuth, E., Thivolet, C., Benhamou, P., Hoffmeister, N., Collet, F., Nicolino, M., Reynaud, R., & Beltrand, J. (2024). Screening and care for preclinical stage 1-2 type 1 diabetes in first-degree relatives: French expert position statement. Diabetes & metabolism, 101603. https://doi.org/10.1016/j.diabet.2024.101603

Guertin, K., Repaske, D., Taylor, J., Williams, E., Onengut-Gumuscu, S., Chen, W., Boggs, S., Yu, L., Allen, L., Botteon, L., Daniel, L., Keating, K., Labergerie, M., Lienhart, T., Gonzalez-Mejia, J., Starnowski, M., & Rich, S. (2024). Implementation of type 1 diabetes genetic risk screening in children in diverse communities: the Virginia PrIMeD project. Genome Medicine, 16. https://doi.org/10.1186/s13073-024-01305-8

Sundheim, B., Hirani, K., Blaschke, M., Lemos, J., & Mittal, R. (2025). Pre-Type 1 Diabetes in Adolescents and Teens: Screening, Nutritional Interventions, Beta-Cell Preservation, and Psychosocial Impacts. Journal of Clinical Medicine, 14. https://doi.org/10.3390/jcm14020383

Ghalwash, M., Anand, V., Lou, O., Martin, F., Rewers, M., Ziegler, A., Toppari, J., Hagopian, W., & Veijola, R. (2023). Islet autoantibody screening in at-risk adolescents to predict type 1 diabetes until young adulthood: a prospective cohort study. The Lancet. Child & adolescent health. https://doi.org/10.1016/s2352-4642(22)00350-9

Ferrat, L., Vehik, K., Sharp, S., et al. (2020). Author Correction: A combined risk score enhances prediction of type 1 diabetes among susceptible children. Nature Medicine, 28, 599 - 599. https://doi.org/10.1038/s41591-020-0930-4

Qu, H., Qu, J., Glessner, J., Liu, Y., Mentch, F., Chang, X., March, M., Li, J., Roizen, J., Connolly, J., Sleiman, P., & Hakonarson, H. (2022). Improved genetic risk scoring algorithm for type 1 diabetes prediction. Pediatric Diabetes, 23, 320 - 323. https://doi.org/10.1111/pedi.13310

McQueen, R., Geno, C., Waugh, K., Frohnert, B., Steck, A., Yu, L., Baxter, J., & Rewers, M. (2020). Cost and Cost-effectiveness of Large-scale Screening for Type 1 Diabetes in Colorado. Diabetes Care, 43, 1496 - 1503. https://doi.org/10.2337/dc19-2003

These papers were sourced and synthesized using Consensus, an AI-powered search engine for research. Try it at https://consensus.app

Diabetes in Special Needs Populations: Risks, Management, and Research Gaps

Diabetes disproportionately affects individuals with intellectual, developmental, and cognitive disabilities, presenting unique challenges in prevention, management, and health outcomes. Research highlights higher prevalence, increased risk of complications, and the need for tailored interventions in these populations.

Prevalence and Risk Factors

• Higher Prevalence and Risk: Individuals with intellectual and developmental disabilities (IDD) and neurodevelopmental disorders have higher rates of diabetes, obesity, hypertension, and cardiometabolic risk factors compared to the general population (Nolan et al., 2024; Pham et al., 2024; Nabors et al., 2024; Chen et al., 2020; Smith et al., 2022; Rubenstein et al., 2020).
• Complications: Comorbid neurodevelopmental disorders (e.g., ADHD, autism, intellectual disability) in type 1 diabetes are linked to poorer glycemic control and increased risk of complications such as nephropathy and retinopathy (Liu et al., 2021). Antipsychotic use in IDD populations further increases metabolic risks, including diabetes (Smith et al., 2022).

Management Challenges

• Self-Management Barriers: Cognitive impairment, learning disabilities, and physical frailty can limit self-care abilities, making diabetes management more complex (House et al., 2018; Munshi, 2017; Srikanth et al., 2020; Biessels & Whitmer, 2019; Nabors et al., 2024; Cuevas et al., 2023; Zheng et al., 2024; Koekkoek et al., 2015).
• Support Systems: Most adults with IDD rely on caregivers for diabetes management. Interventions that involve caregivers and use accessible materials (e.g., easy-read booklets) improve adherence and outcomes (House et al., 2018; Nabors et al., 2024).
• Tailored Interventions: Multidisciplinary, patient-centered programs that integrate cognitive, physical, and mental health support show promise in improving glycemic control, cognitive function, and quality of life (Shaji et al., 2025; Nabors et al., 2024; Cuevas et al., 2023).

Health Disparities and Policy

• Health Disparities: People with IDD experience higher rates of poor health, chronic conditions, and preventable deaths, often due to inadequate access to appropriate care and lack of provider training (Pham et al., 2024; Nolan et al., 2024; Rubenstein et al., 2020).
• Policy Recommendations: Community-led agendas emphasize the need for person-centered care, improved data collection, workforce training, and policies that support holistic health outcomes for people with IDD (Pham et al., 2024).

Intervention and Program Outcomes

Figure 1: Summary of interventions and outcomes in special needs diabetes populations.

Summary

Special needs populations with diabetes face higher risks and unique management challenges. Effective care requires individualized, multidisciplinary approaches, caregiver involvement, and policy changes to address disparities and support holistic health.

These papers were sourced and synthesized using Consensus, an AI-powered search engine for research. Try it at https://consensus.app

References

House, A., Bryant, L., Russell, A., Wright-Hughes, A., Graham, L., Walwyn, R., Wright, J., Hulme, C., O’Dwyer, J., Latchford, G., Meer, S., Birtwistle, J., Stansfield, A., Ajjan, R., & Farrin, A. (2018). Managing with Learning Disability and Diabetes: OK-Diabetes - a case-finding study and feasibility randomised controlled trial.. Health technology assessment, 22 26, 1-328. https://doi.org/10.3310/hta22260

Shaji, S., Radhakrishnan, C., & P, S. (2025). 626-P: Diab@ease—A Pilot Study on Holistic Mental Health Integration for Diabetes, Cognitive Function, and Physical Frailty. Diabetes. https://doi.org/10.2337/db25-626-p

Liu, S., Kuja-Halkola, R., Larsson, H., Lichtenstein, P., Ludvigsson, J., Svensson, A., Gudbjörnsdottir, S., Tideman, M., Serlachius, E., & Butwicka, A. (2021). Neurodevelopmental Disorders, Glycemic Control, and Diabetic Complications in Type 1 Diabetes: a Nationwide Cohort Study. The Journal of Clinical Endocrinology and Metabolism, 106, e4459 - e4470. https://doi.org/10.1210/clinem/dgab467

Munshi, M. (2017). Cognitive Dysfunction in Older Adults With Diabetes: What a Clinician Needs to Know. Diabetes Care, 40, 461 - 467. https://doi.org/10.2337/dc16-1229

Nolan, M., Asche, S., Barton, K., Benziger, C., Ekstrom, H., Essien, I., O'Connor, P., Allen, C., Freitag, L., & Kharbanda, E. (2024). Cardiometabolic Risk in Pediatric Patients with Intellectual and Developmental Disabilities.. American journal of preventive medicine. https://doi.org/10.1016/j.amepre.2024.11.013

Srikanth, V., Sinclair, A., Hill-Briggs, F., Moran, C., & Biessels, G. (2020). Type 2 diabetes and cognitive dysfunction-towards effective management of both comorbidities.. The lancet. Diabetes & endocrinology, 8 6, 535-545. https://doi.org/10.1016/s2213-8587(20)30118-2

Pham, H., Benevides, T., Andresen, M., et al.(2024). Advancing Health Policy and Outcomes for People With Intellectual or Developmental Disabilities: A Community-Led Agenda.. JAMA health forum, 5 8, e242201. https://doi.org/10.1001/jamahealthforum.2024.2201

Biessels, G., & Whitmer, R. (2019). Cognitive dysfunction in diabetes: how to implement emerging guidelines. Diabetologia, 63, 3 - 9. https://doi.org/10.1007/s00125-019-04977-9

Nabors, L., Bauer, A., Ayers, K., Workman, B., Kovacic, M., & Lee, S. (2024). A Short-Term Evaluation of the Eat and Exercise to Win Program for Adults with Intellectual and Developmental Disabilities. Nutrients, 16. https://doi.org/10.3390/nu16183124

Cuevas, H., Stuifbergen, A., Hilsabeck, R., Sales, A., Wood, S., & Kim, J. (2023). The role of cognitive rehabilitation in people with type 2 diabetes: A study protocol for a randomized controlled trial. PLOS ONE, 18. https://doi.org/10.1371/journal.pone.0285553

Chen, S., Zhao, S., Dalman, C., Karlsson, H., & Gardner, R. (2020). Association of maternal diabetes with neurodevelopmental disorders: autism spectrum disorders, attention-deficit/hyperactivity disorder and intellectual disability. International Journal of Epidemiology, 50, 459 - 474. https://doi.org/10.1093/ije/dyaa212

Zheng, Y., Rice, B., Wylie-Rosett, J., & Wu, B. (2024). A Scoping Review of Non‐pharmacological Interventions for Adults with Cognitive Impairment and Diabetes. Alzheimer's & Dementia, 20. https://doi.org/10.1002/alz.088488

Koekkoek, P., Kappelle, L., Berg, E., Rutten, G., & Biessels, G. (2015). Cognitive function in patients with diabetes mellitus: guidance for daily care. The Lancet Neurology, 14, 329-340. https://doi.org/10.1016/s1474-4422(14)70249-2

Smith, E., Stogios, N., Au, E., Maksyutynska, K., De, R., Ji, A., Sørensen, M., St. John, L., Lin, H., Desarkar, P., Lunsky, Y., Remington, G., Hahn, M., & Agarwal, S. (2022). The metabolic adverse effects of antipsychotic use in individuals with intellectual and/or developmental disability: A systematic review and meta‐analysis. Acta Psychiatrica Scandinavica, 146, 201 - 214. https://doi.org/10.1111/acps.13484

Rubenstein, E., Ehrenthal, D., Mallinson, D., Bishop, L., Kuo, H., & Durkin, M. (2020). Pregnancy complications and maternal birth outcomes in women with intellectual and developmental disabilities in Wisconsin Medicaid. PLoS ONE, 15. https://doi.org/10.1371/journal.pone.0241298

These papers were sourced and synthesized using Consensus, an AI-powered search engine for research. Try it at https://consensus.app

Diabetes Emergencies: Types, Risks, and Management

Diabetes emergencies are acute, life-threatening complications requiring rapid recognition and intervention. The most common are diabetic ketoacidosis (DKA), hyperglycemic hyperosmolar state (HHS), and severe hypoglycemia. These emergencies can occur in both type 1 and type 2 diabetes and are associated with significant morbidity, mortality, and healthcare costs.

Major Types of Diabetes Emergencies

Figure 1: Comparison of diabetes emergencies, features, mortality, and triggers.

Clinical Presentation and Outcomes

• DKA and HHS share overlapping features but differ in the degree of acidosis and dehydration. DKA is more common in younger patients and T1DM, while HHS is more frequent in older adults with T2DM and carries a much higher mortality rate (Umpierrez & Korytkowski, 2016; French et al., 2019; Dhatariya et al., 2020; Kitabchi et al., 2004; Kitabchi et al., 2006; Kitabchi et al., 2001; Kitabchi et al., 2009; Rosager et al., 2023; Pasquel & Umpierrez, 2014).
• Combined DKA-HHS presentations are associated with even higher mortality than either condition alone (Pasquel et al., 2019; Rosager et al., 2023).
• Hypoglycemia is a frequent complication of diabetes therapy, especially with insulin or sulfonylureas, and is linked to increased hospital stay and mortality (Umpierrez & Korytkowski, 2016; Virdi et al., 2023).

Management Principles

• Prompt diagnosis and treatment are critical. DKA and HHS require aggressive intravenous fluids, electrolyte replacement (especially potassium), and insulin therapy. Careful monitoring is essential to avoid complications such as hypoglycemia and hypokalemia (Umpierrez & Korytkowski, 2016; French et al., 2019; Dhatariya et al., 2020; Kitabchi et al., 2004; Barski et al., 2023; Kitabchi et al., 2006; Kitabchi et al., 2001; Kitabchi et al., 2009).
• Precipitating factors (e.g., infection, missed insulin, new-onset diabetes) must be identified and treated (Umpierrez & Korytkowski, 2016; French et al., 2019; Dhatariya et al., 2020; Kitabchi et al., 2004; Haile & Fenta, 2025).
• Prevention includes patient education, sick-day management, and access to care. Home ketone monitoring and continuous glucose monitoring can help prevent severe episodes (Umpierrez & Korytkowski, 2016; Kitabchi et al., 2001; Kitabchi et al., 2009; Virdi et al., 2023).

Risk Factors and Economic Impact

• Risk factors for emergencies include infection, non-adherence to therapy, new-onset diabetes, and comorbidities (e.g., cardiovascular disease, renal failure) (Umpierrez & Korytkowski, 2016; Haile & Fenta, 2025; Rosager et al., 2023; Everett et al., 2023; Almutairi et al., 2025; Yousif et al., 2024).
• Economic burden is substantial, with DKA and HHS accounting for billions in healthcare costs annually and significant strain in developing countries (Umpierrez & Korytkowski, 2016; Haile & Fenta, 2025; Kitabchi et al., 2001; Virdi et al., 2023).

Special Considerations

• Euglycemic DKA can occur, especially with SGLT2 inhibitors, and may be missed due to normal glucose levels (French et al., 2019; Long et al., 2021; Virdi et al., 2023).
• Pediatric and minority populations are at higher risk for adverse outcomes, and tailored prevention strategies are needed (Haile & Fenta, 2025; Everett et al., 2023; Yousif et al., 2024).

Summary

Diabetes emergencies—DKA, HHS, and severe hypoglycemia—are serious, preventable complications. Early recognition, rapid management, and prevention strategies are essential to reduce morbidity, mortality, and healthcare costs (Umpierrez & Korytkowski, 2016; French et al., 2019; Dhatariya et al., 2020; Kitabchi et al., 2004; Haile & Fenta, 2025; Kitabchi et al., 2006; Kitabchi et al., 2001; Kitabchi et al., 2009; Rosager et al., 2023; Everett et al., 2023; Almutairi et al., 2025; Pasquel & Umpierrez, 2014; Virdi et al., 2023; Yousif et al., 2024).

These papers were sourced and synthesized using Consensus, an AI-powered search engine for research. Try it at https://consensus.app

References

Umpierrez, G., & Korytkowski, M. (2016). Diabetic emergencies — ketoacidosis, hyperglycaemic hyperosmolar state and hypoglycaemia. Nature Reviews Endocrinology, 12, 222-232. https://doi.org/10.1038/nrendo.2016.15

French, E., Donihi, A., & Korytkowski, M. (2019). Diabetic ketoacidosis and hyperosmolar hyperglycemic syndrome: review of acute decompensated diabetes in adult patients. BMJ, 365. https://doi.org/10.1136/bmj.l1114

Pasquel, F., Tsegka, K., Wang, H., Cardona, S., Galindo, R., Fayfman, M., Davis, G., Vellanki, P., Migdal, A., Gujral, U., Narayan, K., & Umpierrez, G. (2019). Clinical Outcomes in Patients With Isolated or Combined Diabetic Ketoacidosis and Hyperosmolar Hyperglycemic State: A Retrospective, Hospital-Based Cohort Study. Diabetes Care, 43, 349 - 357. https://doi.org/10.2337/dc19-1168

Dhatariya, K., Glaser, N., Codner, E., & Umpierrez, G. (2020). Diabetic ketoacidosis. Nature Reviews Disease Primers, 6, 1-20. https://doi.org/10.1038/s41572-020-0165-1

Kitabchi, A., Umpierrez, G., Murphy, M., Barrett, E., Kreisberg, R., Malone, J., & Wall, B. (2004). Hyperglycemic crises in diabetes. Diabetes care, 27 Suppl 1, S94-102. https://doi.org/10.2337/diacare.27.2007.s94

Barski, L., Golbets, E., Jotkowitz, A., & Schwarzfuchs, D. (2023). Management of diabetic ketoacidosis. European journal of internal medicine. https://doi.org/10.1016/j.ejim.2023.07.005

Haile, H., & Fenta, T. (2025). Magnitude, risk factors and economic impacts of diabetic emergencies in developing countries: A systematic review. PLOS ONE, 20. https://doi.org/10.1371/journal.pone.0317653

Kitabchi, A., Umpierrez, G., Murphy, M., & Kreisberg, R. (2006). Hyperglycemic Crises in Adult Patients With Diabetes. Diabetes Care, 29, 2739 - 2748. https://doi.org/10.2337/dc06-9916

Long, B., Lentz, S., Koyfman, A., & Gottlieb, M. (2021). Euglycemic diabetic ketoacidosis: Etiologies, evaluation, and management. The American journal of emergency medicine, 44, 157-160. https://doi.org/10.1016/j.ajem.2021.02.015

Kitabchi, A., Umpierrez, G., Murphy, M., Barrett, E., Kreisberg, R., Malone, J., & Wall, B. (2001). Management of hyperglycemic crises in patients with diabetes. Diabetes care, 24 1, 131-53. https://doi.org/10.2337/diacare.24.1.131

Kitabchi, A., Umpierrez, G., Miles, J., & Fisher, J. (2009). Hyperglycemic Crises in Adult Patients With Diabetes. Diabetes Care, 32, 1335 - 1343. https://doi.org/10.2337/dc09-9032

Rosager, E., Heltø, A., Maule, C., Friis-Hansen, L., Petersen, J., Nielsen, F., Haugaard, S., & Gregersen, R. (2023). Incidence and Characteristics of the Hyperosmolar Hyperglycemic State: A Danish Cohort Study. Diabetes care. https://doi.org/10.2337/dc23-0988

Everett, E., Copeland, T., Wisk, L., & Chao, L. (2023). Risk Factors for Hyperosmolar Hyperglycemic State in Pediatric Type 2 Diabetes. Pediatric Diabetes, 2023. https://doi.org/10.1155/2023/1318136

Almutairi, T., Dargham, S., Jayyousi, A., Suwaidi, J., & Khalil, A. (2025). Diabetic ketoacidosis and hyperglycemic hyperosmolar state are associated with higher in-hospital mortality and morbidity in diabetes patients hospitalized with ST-elevation myocardial infarction, but not within 30 days of readmission. PLOS ONE, 20. https://doi.org/10.1371/journal.pone.0318774

Pasquel, F., & Umpierrez, G. (2014). Hyperosmolar Hyperglycemic State: A Historic Review of the Clinical Presentation, Diagnosis, and Treatment. Diabetes Care, 37, 3124 - 3131. https://doi.org/10.2337/dc14-0984

Virdi, N., Poon, Y., Abaniel, R., & Bergenstal, R. (2023). Prevalence, Cost, and Burden of Diabetic Ketoacidosis. Diabetes technology & therapeutics, 25 S3, S75-S84. https://doi.org/10.1089/dia.2023.0149

Yousif, M., Dolak, K., Adhikari, S., & White, P. (2024). Risk factors for adverse outcomes in children with diabetic ketoacidosis. The Journal of clinical endocrinology and metabolism. https://doi.org/10.1210/clinem/dgae500