A Decade of InsulinAPP: Validation Using COSMIN and Clinical Advancements Since Its Initial Publication

A Decade of InsulinAPP: Validation Using COSMIN and Clinical Advancements Since Its Initial Publication | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF correspondence A Decade of InsulinAPP: Validation Using COSMIN and Clinical Advancements Since Its Initial Publication Marcos Tadashi Kakitani Toyoshima, Julia Mandaro Lavinas-Jones, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5844918/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 May, 2025 Read the published version in Diabetology & Metabolic Syndrome → Version 1 posted 7 You are reading this latest preprint version Abstract This correspondence marks the 10-year milestone of InsulinAPP, a Brazilian-developed electronic glycemic management system (eGMS) designed to support inpatient insulin therapy. Initially published in 2015, InsulinAPP was developed to assist non-specialist physicians in applying evidence-based insulin protocols in hospital settings. Over the past decade, it has evolved into a validated clinical decision-support tool with demonstrated impact across multiple care contexts. In this manuscript, we present a structured overview of its validation using the COSMIN (COnsensus-based Standards for the selection of health Measurement INstruments) framework, assessing five core domains: cross-cultural adaptation, content validity, criterion validity, reliability, and construct validity. Usability testing showed high acceptance (mean Likert score 4.8/5), and expert consensus on content validity was strong (Content Validity Index = 0.95). The tool also demonstrated high reproducibility (intraclass correlation coefficient = 0.98), and in a randomized trial, glycemic control with InsulinAPP was comparable to endocrinologist-led care, with low hypoglycemia rates. Compared to other eGMS solutions, InsulinAPP stands out for its simplicity, independence from electronic health record integration, and adaptability to low-resource environments. Its protocol anticipated updates later adopted by the Endocrine Society and the Brazilian Diabetes Society, particularly regarding stratified insulinization for patients with mild-to-moderate hyperglycemia. Together, these findings confirm InsulinAPP’s scientific soundness, safety, and real-world applicability. Broader implementation and multicenter studies are warranted to further explore its impact in diverse healthcare systems and improve access to safe inpatient glycemic management. InsulinAPP Glycemic management system COSMIN validation Diabetes mellitus Inpatient glycemic control Construct validity Digital health tools Non-specialist physicians Hypoglycemia prevention Electronic glycemic management Figures Figure 1 Introduction Hospital hyperglycemia (HH) is a common and often underestimated challenge in inpatient care. In 2015, InsulinAPP was introduced as a digital decision-support tool to assist in insulin dose calculations for hospitalized patients with diabetes mellitus (DM) or stress hyperglycemia [ 1 ]. Over the past decade, InsulinAPP has evolved into a comprehensive electronic glycemic management system (eGMS), offering support to non-specialist physicians in applying basal-bolus insulin therapy protocols. The objective of this article is to highlight the advances achieved with InsulinAPP during its first decade of development and implementation, and to present its formal validation using the CO nsensus-based S tandards for the selection of health M easurement IN struments ( COSMIN ) framework —a methodology increasingly used to assess the quality of digital health tools [ 2 ], including those designed for diabetes care [ 3 , 4 ]. Adittionally, we highlight the key developments and clinical advancements achieved during the first ten years of InsulinAPP’s use. Methods We conducted a single-center study in Salvador, Brazil, approved by the local Ethics Committee for National Research (CAAE: 59018616.0.0000.5520). The COSMIN framework was applied to guide the validation process across five dimensions, using the following methods: Cross-Cultural Adaptation and Content Validity : Structured usability testing was conducted with a diverse group of healthcare professionals (including endocrinologists, surgeons, hospitalists and internal medicine doctors) using both real and simulated scenarios. The assessment focused on six key domains: (1) Accessibility of the application, (2) Comprehension of the Portuguese language, (3) Understanding of acronyms, (4) Ease of use, (5) Objectivity, and (6) Perceived usefulness of the application. The evaluation instrument consisted of 144 multiple choice questions, divided into four sections: Initial Evaluation, Inpatient Follow-Up, Hospital Discharge, and General Evaluation of the Application. A 5-point Likert scale and the Content Validity Index (CVI) were used to assess the clarity, usability, and relevance of the tool’s content. Criterion Validity : The criterion validity of the InsulinAPP was assessed by five endocrinologists who independently evaluated five hypothetical clinical cases involving the management of inpatient hyperglycemia. Each expert provided insulin prescriptions using both the InsulinAPP and their own clinical judgement based on the guidelines of the American Diabetes Association [ 5 ] and the Endocrine Society [ 6 ]. Lin’s concordance correlation coefficient was used to analyze agreement between the insulin regimens suggested by the application and those proposed by the endocrinologists and values below 0.90 indicate poor concordance. Reliability : Intra-observer reliability of InsulinAPP was assessed by three endocrinologists who independently used the application to simulate the management of five standardized hypothetical patients. For each case, insulin prescriptions were generated at three time points: hospital admission, 24 hours, and 48 hours. Notably, two out of five cases were intentionally designed to be identical but assessed at different time intervals. Inter-observer reliability was evaluated by three physicians from different specialties -a hospitalist, a surgeon, and an endocrinologist—who independently used InsulinAPP to manage the same hypothetical patient at the same three time points. To quantify agreement, the Intraclass Correlation Coefficient (ICC) was calculated for both intra- and inter-observer assessments, with values closer to 1.0 indicating stronger reliability. The ICC estimates were based on a two-way random-effects model with absolute agreement. Construct Validity : Construct validity was assessed in a randomized controlled trial (RCT) that compared glycemic outcomes between two groups of hospitalized patients with diabetes or stress hyperglycemia: one managed by non-specialist physicians using InsulinAPP and another by endocrinologists using standard care protocols. The study involved 75 patients and measured the difference in mean blood glucose levels from admission to discharge, as well as hypoglycemia rates and insulin dosing. Further methodological details and subgroup analyses related to construct validity are provided in a separate manuscript [ 7 ]. Results The validation of InsulinAPP using the COSMIN framework confirmed its performance across all five core measurement domains, with results summarized in Table 1 : Table 1 Summary of COSMIN-Based Validation of InsulinAPP COSMIN Key Domain Objective Key Findings Cross-Cultural Adaptation and Content Validity Assess usability, cultural alignment, and content clarity Usability testing showed strong acceptance (Likert 4.8/5); CVI = 0.95 Criterion Validity Compare InsulinAPP recommendations to expert prescriptions Lin’s coefficient: 0.90 for monitoring and structure Reliability Assess intra- and inter-user consistency ICC = 0.98 (95% CI: 0.96–0.99), showing high reproducibility Construct Validity Evaluate clinical effectiveness in real-world practice RCT showed comparable glycemic control and hypoglycemia rates (1.4%) vs. standard care Abbreviatures: CI – confidence interval; CVI - Content Validity Index; ICC - intraclass correlation coefficient; RCT – randomized controlled trial Cross-Cultural Adaptation and Content Validity: Usability testing with different healthcare professionals—including endocrinologists, hospitalists, and nurses—demonstrated strong user acceptance. The average Likert score was 4.8/5, indicating excellent clarity, cultural appropriateness, and ease of use across different professional backgrounds. The CVI was 0.95, reflecting strong expert agreement with the tool's clinical recommendations. Criterion Validity: All Lin's concordance correlation coefficients for insulin doses and regimens were below 0.90, whereas those related to monitoring frequency and overall treatment structure were above 0.90. These results suggest that although InsulinAPP and endocrinologist prescriptions may differ slightly in dosing, they are aligned in terms of clinical logic and recommended monitoring routines. Reliability: The intra-observer reliability was strong, as the insulin regimens and doses prescribed using InsulinAPP for the two identical cases were exactly the same across all evaluated time points. The ICC was 0.98 (95% CI: 0.96–0.99), confirming the tool’s reproducibility and consistent performance across different users and time points. Construct Validity: In a randomized controlled trial, glycemic outcomes achieved by non-specialist physicians using InsulinAPP were comparable to those under endocrinologist-led protocols, supporting its use as a decision-support tool in settings where specialist input is limited. Hypoglycemia rates were similarly low (less than 2%). These findings confirm the clinical safety and effectiveness of InsulinAPP in real-world hospital settings. Full results are detailed in Lavinas-Jones et al. (2025) [ 7 ]. Discussion To our knowledge, InsulinAPP is the first electronic glycemic management tool developed for inpatient use to undergo formal validation using the COSMIN framework. Originally designed to support non-specialist physicians in applying evidence-based insulin protocols, InsulinAPP demonstrated strong performance across all five COSMIN domains—cross-cultural adaptation, content validity, criterion validity, reliability, and construct validity—reinforcing its scientific robustness and real-world usability. The COSMIN methodology, traditionally applied to health measurement instruments, proved both suitable and adaptable for evaluating a digital clinical decision-support tool [ 2 ]. By offering consistent, guideline-based insulin recommendations, InsulinAPP has the potential to overcome key barriers to glycemic control in resource-limited hospital environments, particularly where endocrinologists support is limited or absent. Brazil has approximately 5,210 endocrinologists [ 8 ], although data on how many are actively involved in inpatient care remain scarce. This shortage is particularly concerning given the high prevalence of inpatient hyperglycemia. While most cases do not require direct specialist management, many non-specialist physicians encounter barriers such as insufficient training and lack of confidence when initiating or adjusting insulin therapy. As a result, inpatient hyperglycemia is often underdiagnosed or inadequately managed. In this context, InsulinAPP emerges as a scalable, validated solution that empowers non-specialists to deliver safe, evidence-based glycemic care. Importantly, the tool is not intended to replace the role of endocrinologists, but rather to extend best practices to settings where specialist input is unavailable or insufficient. Although criterion validity showed moderate agreement between InsulinAPP and endocrinologist prescribed insulin doses, complete concordance was observed for blood glucose monitoring frequency and treatment structure. These discrepancies may be attributed to differences between the InsulinAPP algorithm and the clinical guidelines available at the time of validation [ 5 , 6 ]. Since then, the 2022 Endocrine Society guideline [ 9 ] and the 2024 Brazilian Diabetes Society guideline [ 10 ] have introduced a stratified insulinization approach for patients with mild-to-moderate hyperglycemia or those on low-dose outpatient insulin therapy—an approach InsulinAPP had already incorporated from its inception [ 1 ]. This alignment underscores the tool’s foresight and ongoing relevance. The development of InsulinAPP followed a multi-phase process involving early publication [ 1 ], clinical validation, and progressive real-world implementation. Figure 1 summarizes the main milestones, including the COSMIN-based validation study in clinical inpatients, a retrospective analysis in surgical patients [ 11 ], and a randomized controlled trial in cardiac patients that demonstrated both clinical efficacy and cost reduction [ 12 ]. Beyond the validation study, InsulinAPP has demonstrated positive impacts in diverse inpatient populations. In São Paulo, complementary studies in surgical and cardiac cohorts reported reductions in complications, hospital length of stay, and overall costs [ 11 , 12 ]. In a prospective randomized controlled study involving patients undergoing coronary artery bypass graft (CABG) surgery, the use of InsulinAPP was associated with a significant reduction in a composite outcome that included hospital-acquired infections, arrhythmias, and acute kidney injury (16% vs. 58%, p < 0.01). Additionally, it led to a shorter median length of hospital stay (7.2 vs. 10.1 days, p = 0.02) and a 18% reduction in hospitalization costs per patient, compared to conventional glycemic control [ 12 ]. Although the COSMIN validation was conducted in a single-center setting with predominantly clinical patients, these additional findings support the tool’s broader applicability. In particular, a previous study demonstrated the safety and effectiveness of InsulinAPP in a real-world inpatient population composed predominantly of surgical patients, further reinforcing its potential for widespread implementation in diverse hospital settings [ 11 ]. InsulinAPP has not yet been implemented outside Brazil. Future multicenter trials and international collaborations will be essential to assess generalizability across healthcare systems. Notably, its current independence from electronic health record (EHR) systems–which often requires complex infrastructures and full integration [ 13 , 14 ]–makes InsulinAPP particularly well-suited for low-resource hospital settings. Future versions may include EHR integration, enhancing its applicability in hospitals with more advanced digital infrastructure. Finally, no adverse events or unintended consequences were reported during clinical use. Hypoglycemia events were rare, and non-specialist physicians reported high confidence in using the tool after minimal training, further supporting its feasibility and safety in routine clinical practice. Conclusion InsulinAPP has evolved over the past decade into a robust electronic glycemic management system, validated through the COSMIN framework across key domains of usability, validity, reliability, and clinical effectiveness. Its ability to support non-specialist physicians in delivering safe and guideline-based insulin therapy—without the need for electronic health record integration—makes it a particularly valuable tool in resource-limited hospital settings. By anticipating and aligning with recent international and national clinical guidelines, InsulinAPP demonstrates both clinical relevance and foresight. Advancing toward multicenter studies and broader implementation efforts will be essential to expand the reach of InsulinAPP and promote equitable access to high-quality inpatient diabetes care. Abbreviations ADA - American Diabetes Association CAAE - Certificate of Presentation of Ethical Appreciation CI - confidence interval COSMIN - CO nsensus-based S tandards for the selection of health M easurement IN struments CVI - Content Validity Index DM - diabetes mellitus eGMS - electronic glycemic management system EHR - electronic health record HH - hospital hyperglycemia ICC - intraclass correlation coefficient RCT - randomized controlled trial Declarations Ethics approval and consent to participate: This study was approved by the local Ethics Committee for National Research (CAAE: 59018616.0.0000.5520). All participants provided written informed consent prior to enrollment, in accordance with the Declaration of Helsinki and local ethical guidelines. Consent for publication: Not applicable. Availability of data and materials: The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request. Competing interests: The authors declare that they have no competing interests. Funding: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Authors' contributions: MTKT: data analysis, manuscript writing, and supervision; JMLJ: conceptualization, data collection, analysis, and manuscript drafting; ACRF: conceptualization, validation, data analysis, critical revision, and project administration; MN: supervision, critical review, and final manuscript approval. All authors have read and approved the final manuscript. Acknowledgements: The authors thank the teams at Hospital Santa Izabel da Santa Casa da Bahia for their support in conducting the study. This manuscript is part of the Master’s dissertation of JMLJ, conducted at the Bahiana School of Medicine, Salvador, Brazil. We also extend our gratitude to all healthcare professionals who contributed to the validation and implementation of InsulinAPP and to Diabetology and Metabolic Syndrome for the origin publication of InsulinAPP, which laid the foundation for its transformative journey. References Toyoshima MTK, De Souza ABC, Admoni SN, Cukier P, Lottenberg SA, Latronico AC, et al. New digital tool to facilitate subcutaneous insulin therapy orders: An inpatient insulin dose calculator. Diabetol Metab Syndr. 2015;7:114. Mokkink LB, Terwee CB, Patrick DL, Alonso J, Stratford PW, Knol DL, et al. The COSMIN checklist for assessing the methodological quality of studies on measurement properties of health status measurement instruments: An international Delphi study. Qual Life Res. 2010;19:539–49. Assad Lemos C, Zago Oliveira T, Alves Cunha JP, Vieira Medeiros Costa D, Barboza Zanetti MO, Aparecida Spadoti Dantas R, et al. Instruments to assess diabetes knowledge, skills and attitudes of people living with diabetes mellitus: A COSMIN-based systematic review. Diabetes Metab Syndr. 2024;18:102974. Bottino LG, Madalosso MM, Garcia SP, Schaan BD, Teló GH. Diabetes-Specific Questionnaires Validated in Brazilian Portuguese: A Systematic Review. Arch Endocrinol Metab. 2020; American Diabetes Association. Diabetes care in the hospital: Standards of medical care in Diabetes - 2018. Diabetes Care. 2018;41:S144–51. Umpierrez GE, Hellman R, Korytkowski MT, Kosiborod M, Maynard GA, Montori VM, et al. Management of hyperglycemia in hospitalized patients in non-critical care setting: An endocrine society clinical practice guideline. J Clin Endocrinol Metab. 2012;97:16–38. Lavinas-Jones JM, Toyoshima MTK, Mesquita LA, Nery M, Feitosa ACR. Efficacy and Safety of an Electronic Glycemic Management System for Optimizing Insulin Therapy in Noncritical Patients With Diabetes: A Randomized Trial. J Diabetes Sci Technol. 2025;19(2):587-589. Scheffer M, Cassenote A, Guerra A, et al. Demografia Médica no Brasil 2020 [Internet]. São Paulo, Brazil: Faculdade de Medicina da USP, Conselho Federal de Medicina; 2020 [cited 2024 Oct 16]. p. 0–312. Available from: https://www.gov.br/saude/pt-br/composicao/sgtes/acoes-em-educacao-em-saude/cfm-e-usp/07-relatorio-demografia-medica-no-brasil_2020-5.pdf Korytkowski MT, Muniyappa R, Antinori-Lent K, et al. Management of Hyperglycemia in Hospitalized Adult Patients in Non-Critical Care Settings: An Endocrine Society Clinical Practice Guideline. J Clin Endocrinol Metab. 2022;107(8):2101-2128. Marino EC, Momesso D, Toyoshima MTK, et al. Screening and management of hospital hyperglycemia in non-critical patients: a position statement from the Brazilian Diabetes Society (SBD). Diabetol Metab Syndr. 2025;17(1):54. Toyoshima MTK, Brandes PHR, Lauterbach G da P, Moraes JRA, Paiva EF De, Umpierrez GE, et al. InsulinAPP application protocol for the inpatient management of type 2 diabetes on a hospitalist-managed ward: a retrospective study. Arch Endocrinol Metab. 2022;66:498–505. Câmara de Souza AB, Toyoshima MTK, Cukier P, Lottenberg SA, Bolta PMP, Lima EG, et al. Electronic Glycemic Management System Improved Glycemic Control and Reduced Complications in Patients With Diabetes Undergoing Coronary Artery Bypass Surgery: A Randomized Controlled Trial. J Diabetes Sci Technol. 2024;19322968241268350. Jones JML, Feitosa ACR, Hita MC, Fonseca EM, Pato RB, Toyoshima MTK. Medical software applications for in-hospital insulin therapy: A systematic review. Digit Health. 2020;6:2055207620983120. Ekanayake PS, Juang PS, Kulasa K. Review of Intravenous and Subcutaneous Electronic Glucose Management Systems for Inpatient Glycemic Control. Curr Diab Rep. 2020;20(12):68. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 10 May, 2025 Read the published version in Diabetology & Metabolic Syndrome → Version 1 posted Editorial decision: Revision requested 21 Apr, 2025 Reviews received at journal 14 Apr, 2025 Reviewers agreed at journal 14 Apr, 2025 Reviewers agreed at journal 08 Apr, 2025 Reviewers invited by journal 08 Apr, 2025 Submission checks completed at journal 03 Apr, 2025 First submitted to journal 03 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5844918","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"correspondence","associatedPublications":[],"authors":[{"id":440318331,"identity":"0d73df69-7a4c-40d2-bff7-8a3b294ed714","order_by":0,"name":"Marcos Tadashi Kakitani Toyoshima","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABE0lEQVRIie3RsWrDMBCA4TMimlS0Kji0T1AQFDyFPotMwF6KCRgyGkPAnkrX9C0S+gIGQ7K4ySrIklLw1MHg1UOPNoUOikO2UvSPRh86+QBstr+dAgJyrACcw/cH0X9eHEmAhMhLCJTnyW3++tY0HSQ8n7y30+ku4ikZLJ0sicB9PJiIV4V3w+cMhKhqz13IfSwKQrWTlTGMNtJIioCSqxSH0MojTO79JfA1ksJPRWAczNvVlLAOxI0O25bJLZKvW5LTROMtjIKQ+kG6TBY/hPSQmuBbxHBVfcyQTPxFiURty5iO1icGCxz8Y2N+vQlfWtbd+0/5nOpmlkTczYzk2O8V4HZwR6BoHzCmLhY2m832X/sEYFJbEarZ8/0AAAAASUVORK5CYII=","orcid":"","institution":"Instituto do Câncer do Estado de São Paulo - Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, Brazil","correspondingAuthor":true,"prefix":"","firstName":"Marcos","middleName":"Tadashi Kakitani","lastName":"Toyoshima","suffix":""},{"id":440318332,"identity":"ceecd08c-79bc-4868-b247-7224550d5783","order_by":1,"name":"Julia Mandaro Lavinas-Jones","email":"","orcid":"","institution":"Bahiana School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Julia","middleName":"Mandaro","lastName":"Lavinas-Jones","suffix":""},{"id":440318333,"identity":"1cd365e0-c374-4e0b-8c11-7bb5d7f3cf59","order_by":2,"name":"Alina Coutinho Rodrigues Feitosa","email":"","orcid":"","institution":"Bahiana School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Alina","middleName":"Coutinho Rodrigues","lastName":"Feitosa","suffix":""},{"id":440318334,"identity":"08778823-bc88-4be0-a29e-5a66d26d40bc","order_by":3,"name":"Marcia Nery","email":"","orcid":"","institution":"Endocrinology Service - Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Marcia","middleName":"","lastName":"Nery","suffix":""}],"badges":[],"createdAt":"2025-01-16 23:38:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5844918/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5844918/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13098-025-01717-5","type":"published","date":"2025-05-10T15:57:34+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80285870,"identity":"7f138aec-282c-4428-8895-67ce6abf24ca","added_by":"auto","created_at":"2025-04-10 06:50:18","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1934075,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eDevelopment and validation timeline of InsulinAPP.\u003c/em\u003e The figure summarizes key milestones of the InsulinAPP system, from its initial publication in 2015 to ongoing plans for international implementation. The timeline includes COSMIN-based validation in clinical patients (2017–2018), a retrospective study in surgical patients (2018–2019), and a randomized controlled trial in cardiac patients (2018–2022) demonstrating clinical benefits and cost savings.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-5844918/v1/5cc40b56dbce20824331428d.png"},{"id":82537632,"identity":"c1851b1f-49a8-426e-8c87-df08fa6156c1","added_by":"auto","created_at":"2025-05-12 16:09:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2142025,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5844918/v1/77a80a2d-afb1-4fb6-b721-9b161801dfef.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Decade of InsulinAPP: Validation Using COSMIN and Clinical Advancements Since Its Initial Publication","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHospital hyperglycemia (HH) is a common and often underestimated challenge in inpatient care. In 2015, InsulinAPP was introduced as a digital decision-support tool to assist in insulin dose calculations for hospitalized patients with diabetes mellitus (DM) or stress hyperglycemia [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Over the past decade, InsulinAPP has evolved into a comprehensive electronic glycemic management system (eGMS), offering support to non-specialist physicians in applying basal-bolus insulin therapy protocols.\u003c/p\u003e \u003cp\u003eThe objective of this article is to highlight the advances achieved with InsulinAPP during its first decade of development and implementation, and to present its formal validation using the \u003cb\u003eCO\u003c/b\u003ensensus-based \u003cb\u003eS\u003c/b\u003etandards for the selection of health \u003cb\u003eM\u003c/b\u003eeasurement \u003cb\u003eIN\u003c/b\u003estruments (\u003cb\u003eCOSMIN\u003c/b\u003e) framework \u0026mdash;a methodology increasingly used to assess the quality of digital health tools [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], including those designed for diabetes care [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Adittionally, we highlight the key developments and clinical advancements achieved during the first ten years of InsulinAPP\u0026rsquo;s use.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e We conducted a single-center study in Salvador, Brazil, approved by the local Ethics Committee for National Research (CAAE: 59018616.0.0000.5520). The COSMIN framework was applied to guide the validation process across five dimensions, using the following methods:\u003c/p\u003e \u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eCross-Cultural Adaptation and Content Validity\u003c/b\u003e: Structured usability testing was conducted with a diverse group of healthcare professionals (including endocrinologists, surgeons, hospitalists and internal medicine doctors) using both real and simulated scenarios. The assessment focused on six key domains: (1) Accessibility of the application, (2) Comprehension of the Portuguese language, (3) Understanding of acronyms, (4) Ease of use, (5) Objectivity, and (6) Perceived usefulness of the application. The evaluation instrument consisted of 144 multiple choice questions, divided into four sections: Initial Evaluation, Inpatient Follow-Up, Hospital Discharge, and General Evaluation of the Application. A 5-point Likert scale and the Content Validity Index (CVI) were used to assess the clarity, usability, and relevance of the tool\u0026rsquo;s content.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eCriterion Validity\u003c/b\u003e: The criterion validity of the InsulinAPP was assessed by five endocrinologists who independently evaluated five hypothetical clinical cases involving the management of inpatient hyperglycemia. Each expert provided insulin prescriptions using both the InsulinAPP and their own clinical judgement based on the guidelines of the American Diabetes Association [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] and the Endocrine Society [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Lin\u0026rsquo;s concordance correlation coefficient was used to analyze agreement between the insulin regimens suggested by the application and those proposed by the endocrinologists and values below 0.90 indicate poor concordance.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eReliability\u003c/b\u003e: Intra-observer reliability of InsulinAPP was assessed by three endocrinologists who independently used the application to simulate the management of five standardized hypothetical patients. For each case, insulin prescriptions were generated at three time points: hospital admission, 24 hours, and 48 hours. Notably, two out of five cases were intentionally designed to be identical but assessed at different time intervals. Inter-observer reliability was evaluated by three physicians from different specialties -a hospitalist, a surgeon, and an endocrinologist\u0026mdash;who independently used InsulinAPP to manage the same hypothetical patient at the same three time points. To quantify agreement, the Intraclass Correlation Coefficient (ICC) was calculated for both intra- and inter-observer assessments, with values closer to 1.0 indicating stronger reliability. The ICC estimates were based on a two-way random-effects model with absolute agreement.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eConstruct Validity\u003c/b\u003e: Construct validity was assessed in a randomized controlled trial (RCT) that compared glycemic outcomes between two groups of hospitalized patients with diabetes or stress hyperglycemia: one managed by non-specialist physicians using InsulinAPP and another by endocrinologists using standard care protocols. The study involved 75 patients and measured the difference in mean blood glucose levels from admission to discharge, as well as hypoglycemia rates and insulin dosing. Further methodological details and subgroup analyses related to construct validity are provided in a separate manuscript [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe validation of InsulinAPP using the COSMIN framework confirmed its performance across all five core measurement domains, with results summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e:\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of COSMIN-Based Validation of InsulinAPP\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOSMIN Key Domain\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObjective\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKey Findings\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCross-Cultural Adaptation and Content Validity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAssess usability, cultural alignment, and content clarity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUsability testing showed strong acceptance (Likert 4.8/5); CVI\u0026thinsp;=\u0026thinsp;0.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCriterion Validity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCompare InsulinAPP recommendations to expert prescriptions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLin\u0026rsquo;s coefficient: \u0026lt;0.90 for insulin dosing; \u0026gt;0.90 for monitoring and structure\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReliability\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAssess intra- and inter-user consistency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eICC\u0026thinsp;=\u0026thinsp;0.98 (95% CI: 0.96\u0026ndash;0.99), showing high reproducibility\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eConstruct Validity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEvaluate clinical effectiveness in real-world practice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRCT showed comparable glycemic control and hypoglycemia rates (1.4%) vs. standard care\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eAbbreviatures: CI \u0026ndash; confidence interval; CVI - Content Validity Index; ICC - intraclass correlation coefficient; RCT \u0026ndash; randomized controlled trial\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eCross-Cultural Adaptation and Content Validity:\u003c/h3\u003e\n\u003cp\u003eUsability testing with different healthcare professionals\u0026mdash;including endocrinologists, hospitalists, and nurses\u0026mdash;demonstrated strong user acceptance. The average Likert score was 4.8/5, indicating excellent clarity, cultural appropriateness, and ease of use across different professional backgrounds. The CVI was 0.95, reflecting strong expert agreement with the tool's clinical recommendations.\u003c/p\u003e\n\u003ch3\u003eCriterion Validity:\u003c/h3\u003e\n\u003cp\u003eAll Lin's concordance correlation coefficients for insulin doses and regimens were below 0.90, whereas those related to monitoring frequency and overall treatment structure were above 0.90. These results suggest that although InsulinAPP and endocrinologist prescriptions may differ slightly in dosing, they are aligned in terms of clinical logic and recommended monitoring routines.\u003c/p\u003e\n\u003ch3\u003eReliability:\u003c/h3\u003e\n\u003cp\u003eThe intra-observer reliability was strong, as the insulin regimens and doses prescribed using InsulinAPP for the two identical cases were exactly the same across all evaluated time points. The ICC was 0.98 (95% CI: 0.96\u0026ndash;0.99), confirming the tool\u0026rsquo;s reproducibility and consistent performance across different users and time points.\u003c/p\u003e\n\u003ch3\u003eConstruct Validity:\u003c/h3\u003e\n\u003cp\u003eIn a randomized controlled trial, glycemic outcomes achieved by non-specialist physicians using InsulinAPP were comparable to those under endocrinologist-led protocols, supporting its use as a decision-support tool in settings where specialist input is limited. Hypoglycemia rates were similarly low (less than 2%). These findings confirm the clinical safety and effectiveness of InsulinAPP in real-world hospital settings. Full results are detailed in Lavinas-Jones et al. (2025) [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo our knowledge, InsulinAPP is the first electronic glycemic management tool developed for inpatient use to undergo formal validation using the COSMIN framework. Originally designed to support non-specialist physicians in applying evidence-based insulin protocols, InsulinAPP demonstrated strong performance across all five COSMIN domains\u0026mdash;cross-cultural adaptation, content validity, criterion validity, reliability, and construct validity\u0026mdash;reinforcing its scientific robustness and real-world usability.\u003c/p\u003e \u003cp\u003eThe COSMIN methodology, traditionally applied to health measurement instruments, proved both suitable and adaptable for evaluating a digital clinical decision-support tool [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. By offering consistent, guideline-based insulin recommendations, InsulinAPP has the potential to overcome key barriers to glycemic control in resource-limited hospital environments, particularly where endocrinologists support is limited or absent.\u003c/p\u003e \u003cp\u003eBrazil has approximately 5,210 endocrinologists [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], although data on how many are actively involved in inpatient care remain scarce. This shortage is particularly concerning given the high prevalence of inpatient hyperglycemia. While most cases do not require direct specialist management, many non-specialist physicians encounter barriers such as insufficient training and lack of confidence when initiating or adjusting insulin therapy. As a result, inpatient hyperglycemia is often underdiagnosed or inadequately managed.\u003c/p\u003e \u003cp\u003eIn this context, InsulinAPP emerges as a scalable, validated solution that empowers non-specialists to deliver safe, evidence-based glycemic care. Importantly, the tool is not intended to replace the role of endocrinologists, but rather to extend best practices to settings where specialist input is unavailable or insufficient.\u003c/p\u003e \u003cp\u003eAlthough criterion validity showed moderate agreement between InsulinAPP and endocrinologist prescribed insulin doses, complete concordance was observed for blood glucose monitoring frequency and treatment structure. These discrepancies may be attributed to differences between the InsulinAPP algorithm and the clinical guidelines available at the time of validation [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Since then, the 2022 Endocrine Society guideline [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] and the 2024 Brazilian Diabetes Society guideline [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] have introduced a stratified insulinization approach for patients with mild-to-moderate hyperglycemia or those on low-dose outpatient insulin therapy\u0026mdash;an approach InsulinAPP had already incorporated from its inception [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. This alignment underscores the tool\u0026rsquo;s foresight and ongoing relevance.\u003c/p\u003e \u003cp\u003eThe development of InsulinAPP followed a multi-phase process involving early publication [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], clinical validation, and progressive real-world implementation. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes the main milestones, including the COSMIN-based validation study in clinical inpatients, a retrospective analysis in surgical patients [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], and a randomized controlled trial in cardiac patients that demonstrated both clinical efficacy and cost reduction [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBeyond the validation study, InsulinAPP has demonstrated positive impacts in diverse inpatient populations. In S\u0026atilde;o Paulo, complementary studies in surgical and cardiac cohorts reported reductions in complications, hospital length of stay, and overall costs [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In a prospective randomized controlled study involving patients undergoing coronary artery bypass graft (CABG) surgery, the use of InsulinAPP was associated with a significant reduction in a composite outcome that included hospital-acquired infections, arrhythmias, and acute kidney injury (16% vs. 58%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Additionally, it led to a shorter median length of hospital stay (7.2 vs. 10.1 days, p\u0026thinsp;=\u0026thinsp;0.02) and a 18% reduction in hospitalization costs per patient, compared to conventional glycemic control [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough the COSMIN validation was conducted in a single-center setting with predominantly clinical patients, these additional findings support the tool\u0026rsquo;s broader applicability. In particular, a previous study demonstrated the safety and effectiveness of InsulinAPP in a real-world inpatient population composed predominantly of surgical patients, further reinforcing its potential for widespread implementation in diverse hospital settings [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eInsulinAPP has not yet been implemented outside Brazil. Future multicenter trials and international collaborations will be essential to assess generalizability across healthcare systems. Notably, its current independence from electronic health record (EHR) systems\u0026ndash;which often requires complex infrastructures and full integration [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u0026ndash;makes InsulinAPP particularly well-suited for low-resource hospital settings. Future versions may include EHR integration, enhancing its applicability in hospitals with more advanced digital infrastructure.\u003c/p\u003e \u003cp\u003eFinally, no adverse events or unintended consequences were reported during clinical use. Hypoglycemia events were rare, and non-specialist physicians reported high confidence in using the tool after minimal training, further supporting its feasibility and safety in routine clinical practice.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eInsulinAPP has evolved over the past decade into a robust electronic glycemic management system, validated through the COSMIN framework across key domains of usability, validity, reliability, and clinical effectiveness. Its ability to support non-specialist physicians in delivering safe and guideline-based insulin therapy\u0026mdash;without the need for electronic health record integration\u0026mdash;makes it a particularly valuable tool in resource-limited hospital settings. By anticipating and aligning with recent international and national clinical guidelines, InsulinAPP demonstrates both clinical relevance and foresight. Advancing toward multicenter studies and broader implementation efforts will be essential to expand the reach of InsulinAPP and promote equitable access to high-quality inpatient diabetes care.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eADA - American Diabetes Association\u003c/p\u003e\n\u003cp\u003eCAAE - Certificate of Presentation of Ethical Appreciation\u003c/p\u003e\n\u003cp\u003eCI - confidence interval\u003c/p\u003e\n\u003cp\u003eCOSMIN - \u003cstrong\u003eCO\u003c/strong\u003ensensus-based \u003cstrong\u003eS\u003c/strong\u003etandards for the selection of health \u003cstrong\u003eM\u003c/strong\u003eeasurement \u003cstrong\u003eIN\u003c/strong\u003estruments\u003c/p\u003e\n\u003cp\u003eCVI - Content Validity Index\u003c/p\u003e\n\u003cp\u003eDM - diabetes mellitus\u003c/p\u003e\n\u003cp\u003eeGMS - electronic glycemic management system\u003c/p\u003e\n\u003cp\u003eEHR - electronic health record\u003c/p\u003e\n\u003cp\u003eHH - hospital hyperglycemia\u003c/p\u003e\n\u003cp\u003eICC - intraclass correlation coefficient\u003c/p\u003e\n\u003cp\u003eRCT - randomized controlled trial\u003c/p\u003e"},{"header":"Declarations","content":"\u003cul\u003e\n \u003cli\u003eEthics approval and consent to participate: This study was approved by the local Ethics Committee for National Research (CAAE: 59018616.0.0000.5520). All participants provided written informed consent prior to enrollment, in accordance with the Declaration of Helsinki and local ethical guidelines.\u003c/li\u003e\n \u003cli\u003eConsent for publication: Not applicable.\u003c/li\u003e\n \u003cli\u003eAvailability of data and materials: The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/li\u003e\n \u003cli\u003eCompeting interests: The authors declare that they have no competing interests.\u003c/li\u003e\n \u003cli\u003eFunding: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/li\u003e\n \u003cli\u003eAuthors\u0026apos; contributions: MTKT: data analysis, manuscript writing, and supervision; JMLJ: conceptualization, data collection, analysis, and manuscript drafting; ACRF: conceptualization, validation, data analysis, critical revision, and project administration; MN: supervision, critical review, and final manuscript approval. All authors have read and approved the final manuscript.\u003c/li\u003e\n \u003cli\u003eAcknowledgements: The authors thank the teams at Hospital Santa Izabel da Santa Casa da Bahia for their support in conducting the study. This manuscript is part of the Master\u0026rsquo;s dissertation of JMLJ, conducted at the Bahiana School of Medicine, Salvador, Brazil. We also extend our gratitude to all healthcare professionals who contributed to the validation and implementation of InsulinAPP and to \u003cem\u003eDiabetology and Metabolic Syndrome\u0026nbsp;\u003c/em\u003efor the origin publication of InsulinAPP, which laid the foundation for its transformative journey.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eToyoshima MTK, De Souza ABC, Admoni SN, Cukier P, Lottenberg SA, Latronico AC, et al. New digital tool to facilitate subcutaneous insulin therapy orders: An inpatient insulin dose calculator. Diabetol Metab Syndr. 2015;7:114. \u003c/li\u003e\n\u003cli\u003eMokkink LB, Terwee CB, Patrick DL, Alonso J, Stratford PW, Knol DL, et al. The COSMIN checklist for assessing the methodological quality of studies on measurement properties of health status measurement instruments: An international Delphi study. Qual Life Res. 2010;19:539\u0026ndash;49. \u003c/li\u003e\n\u003cli\u003eAssad Lemos C, Zago Oliveira T, Alves Cunha JP, Vieira Medeiros Costa D, Barboza Zanetti MO, Aparecida Spadoti Dantas R, et al. Instruments to assess diabetes knowledge, skills and attitudes of people living with diabetes mellitus: A COSMIN-based systematic review. Diabetes Metab Syndr. 2024;18:102974. \u003c/li\u003e\n\u003cli\u003eBottino LG, Madalosso MM, Garcia SP, Schaan BD, Tel\u0026oacute; GH. Diabetes-Specific Questionnaires Validated in Brazilian Portuguese: A Systematic Review. Arch Endocrinol Metab. 2020; \u003c/li\u003e\n\u003cli\u003eAmerican Diabetes Association. Diabetes care in the hospital: Standards of medical care in Diabetes - 2018. Diabetes Care. 2018;41:S144\u0026ndash;51. \u003c/li\u003e\n\u003cli\u003eUmpierrez GE, Hellman R, Korytkowski MT, Kosiborod M, Maynard GA, Montori VM, et al. Management of hyperglycemia in hospitalized patients in non-critical care setting: An endocrine society clinical practice guideline. J Clin Endocrinol Metab. 2012;97:16\u0026ndash;38. \u003c/li\u003e\n\u003cli\u003eLavinas-Jones JM, Toyoshima MTK, Mesquita LA, Nery M, Feitosa ACR. Efficacy and Safety of an Electronic Glycemic Management System for Optimizing Insulin Therapy in Noncritical Patients With Diabetes: A Randomized Trial. J Diabetes Sci Technol. 2025;19(2):587-589.\u003c/li\u003e\n\u003cli\u003eScheffer M, Cassenote A, Guerra A, et al. Demografia M\u0026eacute;dica no Brasil 2020 [Internet]. S\u0026atilde;o Paulo, Brazil: Faculdade de Medicina da USP, Conselho Federal de Medicina; 2020 [cited 2024 Oct 16]. p. 0\u0026ndash;312. Available from: https://www.gov.br/saude/pt-br/composicao/sgtes/acoes-em-educacao-em-saude/cfm-e-usp/07-relatorio-demografia-medica-no-brasil_2020-5.pdf\u003c/li\u003e\n\u003cli\u003eKorytkowski MT, Muniyappa R, Antinori-Lent K, et al. Management of Hyperglycemia in Hospitalized Adult Patients in Non-Critical Care Settings: An Endocrine Society Clinical Practice Guideline. J Clin Endocrinol Metab. 2022;107(8):2101-2128. \u003c/li\u003e\n\u003cli\u003eMarino EC, Momesso D, Toyoshima MTK, et al. Screening and management of hospital hyperglycemia in non-critical patients: a position statement from the Brazilian Diabetes Society (SBD). Diabetol Metab Syndr. 2025;17(1):54.\u003c/li\u003e\n\u003cli\u003eToyoshima MTK, Brandes PHR, Lauterbach G da P, Moraes JRA, Paiva EF De, Umpierrez GE, et al. InsulinAPP application protocol for the inpatient management of type 2 diabetes on a hospitalist-managed ward: a retrospective study. Arch Endocrinol Metab. 2022;66:498\u0026ndash;505.\u003c/li\u003e\n\u003cli\u003eC\u0026acirc;mara de Souza AB, Toyoshima MTK, Cukier P, Lottenberg SA, Bolta PMP, Lima EG, et al. Electronic Glycemic Management System Improved Glycemic Control and Reduced Complications in Patients With Diabetes Undergoing Coronary Artery Bypass Surgery: A Randomized Controlled Trial. J Diabetes Sci Technol. 2024;19322968241268350. \u003c/li\u003e\n\u003cli\u003eJones JML, Feitosa ACR, Hita MC, Fonseca EM, Pato RB, Toyoshima MTK. Medical software applications for in-hospital insulin therapy: A systematic review. Digit Health. 2020;6:2055207620983120. \u003c/li\u003e\n\u003cli\u003eEkanayake PS, Juang PS, Kulasa K. Review of Intravenous and Subcutaneous Electronic Glucose Management Systems for Inpatient Glycemic Control. Curr Diab Rep. 2020;20(12):68.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"diabetology-and-metabolic-syndrome","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dims","sideBox":"Learn more about [Diabetology \u0026 Metabolic Syndrome](http://dmsjournal.biomedcentral.com/)","snPcode":"13098","submissionUrl":"https://submission.nature.com/new-submission/13098/3","title":"Diabetology \u0026 Metabolic Syndrome","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"InsulinAPP, Glycemic management system, COSMIN validation, Diabetes mellitus, Inpatient glycemic control, Construct validity, Digital health tools, Non-specialist physicians, Hypoglycemia prevention, Electronic glycemic management","lastPublishedDoi":"10.21203/rs.3.rs-5844918/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5844918/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"This correspondence marks the 10-year milestone of InsulinAPP, a Brazilian-developed electronic glycemic management system (eGMS) designed to support inpatient insulin therapy. Initially published in 2015, InsulinAPP was developed to assist non-specialist physicians in applying evidence-based insulin protocols in hospital settings. Over the past decade, it has evolved into a validated clinical decision-support tool with demonstrated impact across multiple care contexts. In this manuscript, we present a structured overview of its validation using the COSMIN (COnsensus-based Standards for the selection of health Measurement INstruments) framework, assessing five core domains: cross-cultural adaptation, content validity, criterion validity, reliability, and construct validity. Usability testing showed high acceptance (mean Likert score 4.8/5), and expert consensus on content validity was strong (Content Validity Index = 0.95). The tool also demonstrated high reproducibility (intraclass correlation coefficient = 0.98), and in a randomized trial, glycemic control with InsulinAPP was comparable to endocrinologist-led care, with low hypoglycemia rates. Compared to other eGMS solutions, InsulinAPP stands out for its simplicity, independence from electronic health record integration, and adaptability to low-resource environments. Its protocol anticipated updates later adopted by the Endocrine Society and the Brazilian Diabetes Society, particularly regarding stratified insulinization for patients with mild-to-moderate hyperglycemia. Together, these findings confirm InsulinAPP’s scientific soundness, safety, and real-world applicability. Broader implementation and multicenter studies are warranted to further explore its impact in diverse healthcare systems and improve access to safe inpatient glycemic management.","manuscriptTitle":"A Decade of InsulinAPP: Validation Using COSMIN and Clinical Advancements Since Its Initial Publication","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-10 06:50:13","doi":"10.21203/rs.3.rs-5844918/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-21T21:57:57+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-14T17:09:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"263096210856747998093738186052565466400","date":"2025-04-14T16:34:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"285929527166852169644734329036999875192","date":"2025-04-08T23:48:00+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-08T12:10:47+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-04T02:58:16+00:00","index":"","fulltext":""},{"type":"submitted","content":"Diabetology \u0026 Metabolic Syndrome","date":"2025-04-03T23:30:06+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"diabetology-and-metabolic-syndrome","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dims","sideBox":"Learn more about [Diabetology \u0026 Metabolic Syndrome](http://dmsjournal.biomedcentral.com/)","snPcode":"13098","submissionUrl":"https://submission.nature.com/new-submission/13098/3","title":"Diabetology \u0026 Metabolic Syndrome","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4b9b04aa-e6dc-468c-9d93-6b3cdc2b81f0","owner":[],"postedDate":"April 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-05-12T16:06:08+00:00","versionOfRecord":{"articleIdentity":"rs-5844918","link":"https://doi.org/10.1186/s13098-025-01717-5","journal":{"identity":"diabetology-and-metabolic-syndrome","isVorOnly":false,"title":"Diabetology \u0026 Metabolic Syndrome"},"publishedOn":"2025-05-10 15:57:34","publishedOnDateReadable":"May 10th, 2025"},"versionCreatedAt":"2025-04-10 06:50:13","video":"","vorDoi":"10.1186/s13098-025-01717-5","vorDoiUrl":"https://doi.org/10.1186/s13098-025-01717-5","workflowStages":[]},"version":"v1","identity":"rs-5844918","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5844918","identity":"rs-5844918","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}