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Immune checkpoint inhibitor (CPI)-induced diabetes mellitus (CPI-DM) is a rare immune-related adverse event (irAE). Patients and providers fear that continuing CPIs puts patients at risk for additional irAEs and thus may discontinue therapy. Currently, there are little data to inform this decision. Therefore, this study aims to elucidate whether discontinuing CPIs after diagnosis of CPI-DM impacts the development of future irAEs and cancer outcomes such as progression and death. Patients who developed CPI-DM during cancer treatment at UCSF from 1 July 2015 to 5 July 2023 were analyzed for cancer outcomes and irAE development. Fisher's exact tests, Student t-tests, Kaplan-Meier methods, and Cox regression were used as appropriate. Of the 43 patients with CPI-DM, 20 (47%) resumed CPIs within 90 days of the irAE, 4 (9%) patients restarted after 90 days, and 19 (44%) patients never restarted. Subsequent irAEs were diagnosed in 9 of 24 (38%) who resumed CPIs and 3 of 19 (16%) who discontinued CPIs (p = 0.17). There was no significant difference in death (p = 0.74) or cancer progression (p = 0.55) between these two groups. While our single-institution study did not show worse cancer outcomes after discontinuing CPIs, many variables can impact outcomes, which our study was not adequately powered to evaluate. A nuanced approach is needed to decide whether to continue CPI treatment after a severe irAE like CPI-DM.
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BACKGROUND: Hyperglycemia occurs in 22% to 46% of hospitalized patients, negatively affecting patient outcomes, including mortality, inpatient complications, length of stay, and hospital costs. Achieving inpatient glycemic control is challenging due to inconsistent caloric intake, changes from home medications, a catabolic state in the setting of acute illness, consequences of acute inflammation, intercurrent infection, and limitations in labor-intensive glucose monitoring and insulin administration. METHOD: We conducted a retrospective cross-sectional analysis at the University of California San Francisco hospitals between September 3, 2020 and September 2, 2021, comparing point-of-care glucose measurements in patients on nil per os (NPO), continuous total parenteral nutrition, or continuous tube feeding assigned to our novel automated self-adjusting subcutaneous insulin algorithm (SQIA) or conventional, physician-driven insulin dosing. We also evaluated physician efficiency by tracking the number of insulin orders placed or modified. RESULTS: The proportion of glucose in range (70-180 mg/dL) was higher in the SQIA group than in the conventional group (71.0% vs 69.0%, P = .153). The SQIA led to a lower proportion of severe hyperglycemia (>250 mg/dL; 5.8% vs 7.2%, P = .017), hypoglycemia (54-69 mg/dL; 0.8% vs 1.2%, P = .029), and severe hypoglycemia (<54 mg/dL; 0.3% vs 0.5%, P = .076) events. The number of orders a physician had to place while a patient was on the SQIA was reduced by a factor of more than 12, when compared with while a patient was on conventional insulin dosing. CONCLUSIONS: The SQIA reduced severe hyperglycemia, hypoglycemia, and severe hypoglycemia compared with conventional insulin dosing. It also improved physician efficiency by reducing the number of order modifications a physician had to place.
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Algoritmos , Glucemia , Control Glucémico , Hipoglucemiantes , Insulina , Humanos , Estudios Retrospectivos , Insulina/administración & dosificación , Insulina/efectos adversos , Femenino , Masculino , Persona de Mediana Edad , Glucemia/análisis , Glucemia/efectos de los fármacos , Estudios Transversales , Hipoglucemiantes/administración & dosificación , Hipoglucemiantes/efectos adversos , Control Glucémico/efectos adversos , Control Glucémico/métodos , Anciano , Hiperglucemia/sangre , Hiperglucemia/tratamiento farmacológico , Hospitalización , Inyecciones Subcutáneas , Hipoglucemia/inducido químicamente , Hipoglucemia/prevención & control , Hipoglucemia/sangre , Hipoglucemia/epidemiologíaRESUMEN
The annual Virtual Hospital Diabetes Meeting was hosted by Diabetes Technology Society on April 1 and April 2, 2022. This meeting brought together experts in diabetes technology to discuss various new developments in the field of managing diabetes in hospitalized patients. Meeting topics included (1) digital health and the hospital, (2) blood glucose targets, (3) software for inpatient diabetes, (4) surgery, (5) transitions, (6) coronavirus disease and diabetes in the hospital, (7) drugs for diabetes, (8) continuous glucose monitoring, (9) quality improvement, (10) diabetes care and educatinon, and (11) uniting people, process, and technology to achieve optimal glycemic management. This meeting covered new technology that will enable better care of people with diabetes if they are hospitalized.
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Infecciones por Coronavirus , Diabetes Mellitus Tipo 1 , Diabetes Mellitus , Glucemia , Automonitorización de la Glucosa Sanguínea , Infecciones por Coronavirus/epidemiología , Diabetes Mellitus/terapia , Hospitales , HumanosRESUMEN
BACKGROUND: Adult patients with diabetes or newly recognized hyperglycemia account for over 30% of noncritically ill hospitalized patients. These patients are at increased risk for adverse clinical outcomes in the absence of defined approaches to glycemic management. OBJECTIVE: To review and update the 2012 Management of Hyperglycemia in Hospitalized Patients in Non-Critical Care Settings: An Endocrine Society Clinical Practice Guideline and to address emerging areas specific to the target population of noncritically ill hospitalized patients with diabetes or newly recognized or stress-induced hyperglycemia. METHODS: A multidisciplinary panel of clinician experts, together with a patient representative and experts in systematic reviews and guideline development, identified and prioritized 10 clinical questions related to inpatient management of patients with diabetes and/or hyperglycemia. The systematic reviews queried electronic databases for studies relevant to the selected questions. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology was used to assess the certainty of evidence and make recommendations. RESULTS: The panel agreed on 10 frequently encountered areas specific to glycemic management in the hospital for which 15 recommendations were made. The guideline includes conditional recommendations for hospital use of emerging diabetes technologies including continuous glucose monitoring and insulin pump therapy; insulin regimens for prandial insulin dosing, glucocorticoid, and enteral nutrition-associated hyperglycemia; and use of noninsulin therapies. Recommendations were also made for issues relating to preoperative glycemic measures, appropriate use of correctional insulin, and diabetes self-management education in the hospital. A conditional recommendation was made against preoperative use of caloric beverages in patients with diabetes. CONCLUSION: The recommendations are based on the consideration of important outcomes, practicality, feasibility, and patient values and preferences. These recommendations can be used to inform system improvement and clinical practice for this frequently encountered inpatient population.
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Diabetes Mellitus , Hiperglucemia , Glucemia , Automonitorización de la Glucosa Sanguínea , Diabetes Mellitus/tratamiento farmacológico , Humanos , Hiperglucemia/tratamiento farmacológico , Hipoglucemiantes , Insulina , Revisiones Sistemáticas como AsuntoRESUMEN
OBJECTIVE: To identify clinical characteristics and factors associated with the development of euglycemic diabetic ketoacidosis (eDKA), and develop suitable strategies to reduce such events. METHODS: Electronic health record (EHR) data were extracted to identify all patients between December 1, 2013, and March 30, 2021, who underwent surgical procedures and had been prescribed a sodium-glucose cotransporter 2 inhibitor (SGLT2i) before these procedures. The resulting list was streamlined to a subset of patients who either had diabetic ketoacidosis (DKA) listed as a hospital diagnosis, postoperative serum bicarbonate ≤ 16 mmol/L, or postoperative serum pH ≤ 7.20. Clinical documentation and laboratory data were reviewed to determine the patients with eDKA. RESULTS: A total of 2183 procedures conducted on 1307 patients, met the inclusion criteria with the majority (1726, 79.1%) being nonemergent patients. Among 1307 patients, 625 (47.8%) were prescribed empagliflozin, 447 (34.2%) canagliflozin, 214 (16.4%) dapagliflozin, and 21 (1.6%) ertugliflozin, respectively. A total of 8 incidences pertaining to eDKA were noted for 8 unique patients; 5 had undergone emergency surgery whereas 3 had undergone nonemergent procedures. In the 3 nonemergent cases, only 1 patient had received counseling to stop the SGLT2i 3 days before the procedure. In perioperative patients who were prescribed an SGLT2i over 6 years, the incidence of eDKA was 0.17% and 1.1% for nonemergent and emergent procedures, respectively. CONCLUSION: Euglycemic DKA was rare in patients undergoing nonemergent procedures, likely because of preoperative instructions to stop their SGLT2i 3 days before the procedure. Euglycemic DKA was more likely to occur in patients undergoing emergency surgery when the SGLT2i could not be prophylactically stopped.
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Diabetes Mellitus Tipo 2 , Cetoacidosis Diabética , Inhibidores del Cotransportador de Sodio-Glucosa 2 , Diabetes Mellitus Tipo 2/complicaciones , Diabetes Mellitus Tipo 2/tratamiento farmacológico , Cetoacidosis Diabética/diagnóstico , Cetoacidosis Diabética/epidemiología , Cetoacidosis Diabética/prevención & control , Glucosa , Humanos , Incidencia , Pacientes Internos , Sodio , Inhibidores del Cotransportador de Sodio-Glucosa 2/efectos adversosRESUMEN
Background: Oral hypoglycemic agents are a frequent cause of hypoglycemia in nondiabetic people. Here, we report a case of recurrent hypoglycemia caused by glipizide, in which diagnosis was delayed because of a combination of delayed hypoglycemic agent screening and low sensitivity of the hypoglycemic agent screening panel used. Case Report: A 66-year-old woman repeatedly presented with symptomatic hypoglycemia. At the first presentation, the serum glucose level was 40 mg/dL (2.2 mmol/L), C-peptide level was 13.1 ng/mL (0.8-3.1 ng/mL), proinsulin level was 96.9 pmol/L (<18.8 pmol/L), and insulin level was 164 mU/L (<17 mU/L). An initial hypoglycemic agent screening, performed 24 hours after admission, yielded a negative result, leading to prolonged and recurrent hospitalizations for workup and localization of insulinoma. A hypoglycemic agent screening at a subsequent presentation, concordant with hypoglycemia, yielded a positive result for glipizide, which was at a level of 320 ng/mL (reporting limit, 40 ng/mL). An examination of the patient's home medications revealed a container, labeled as benztropine, containing glipizide tablets. After the diagnosis of glipizide-induced hypoglycemia, the patient had no further episodes of hypoglycemia. Discussion: The failure to detect glipizide using the initial hypoglycemia agent assay was likely because of a combination of a delay in the initial screening and low sensitivity of the assay for glipizide compared with that of other available assays. Here, we discuss important considerations for the interpretation of hypoglycemic agent screening in the diagnosis of hypoglycemia, including the timing of collection and reporting, pharmacokinetics of culprit agents, and sensitivity of the hypoglycemic agent panel used. Conclusion: Screening tests for hypoglycemic agents are necessary for the evaluation of hypoglycemia because their biochemical evaluation may be indistinguishable from that of insulinoma.
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PURPOSE OF REVIEW: There is a bidirectional relationship between cancer and diabetes, with one condition influencing the prognosis of the other. Multiple cancer therapies cause diabetes including well-established medications such as glucocorticoids and novel cancer therapies such as immune checkpoint inhibitors (CPIs) and phosphoinositide 3-kinase (PI3K) inhibitors. RECENT FINDINGS: The nature and severity of diabetes caused by each therapy differ, with some predominantly mediated by insulin resistance, such as PI3K inhibitors and glucocorticoids, while others by insulin deficiency, such as CPIs. Studies have demonstrated diabetes from CPIs to be more rapidly progressing than conventional type 1 diabetes. There remains a scarcity of published guidance for the screening, diagnosis, and management of hyperglycemia and diabetes from these therapies. The need for such guidance is critical because diabetes management in the cancer patient is complex, individualized, and requires inter-disciplinary care. In the present narrative review, we synthesize and summarize the most relevant literature pertaining to diabetes and hyperglycemia in the setting of these cancer therapies and provide an updated patient-centered framework for their evaluation and management.
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Diabetes Mellitus Tipo 1 , Hiperglucemia , Neoplasias , Diabetes Mellitus Tipo 1/inducido químicamente , Glucocorticoides/efectos adversos , Glucocorticoides/uso terapéutico , Humanos , Inhibidores de Puntos de Control Inmunológico/efectos adversos , Inhibidores de Puntos de Control Inmunológico/uso terapéutico , Neoplasias/complicaciones , Neoplasias/epidemiología , Neoplasias/terapia , Atención Dirigida al Paciente , Inhibidores de las Quinasa Fosfoinosítidos-3/efectos adversos , Inhibidores de las Quinasa Fosfoinosítidos-3/uso terapéuticoRESUMEN
This retrospective study examined changes in medication orders as a risk factor for future acute hypoglycemic events. The investigators identified factors associated with acute hypoglycemic events resulting in emergency department visits or inpatient admissions. Non-Hispanic Black race, chronic kidney disease, insulin at baseline, and nonprivate insurance were associated with higher risk of an acute hypoglycemic event, whereas age, sex, and A1C were not. After adjustment for other risk factors, changes in insulin orders after A1C measurement were associated with a 1.5 times higher risk of an acute hypoglycemia (adjusted hazard ratio 1.48, 95% CI 1.08-2.03). These results further understanding of risk factors and clinical processes relevant to predicting and preventing acute hypoglycemia.
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INTRODUCTION: To evaluate whether outpatient insulin treatment, hemoglobin A1c (HbA1c), glucose on admission, or glycemic control during hospitalization is associated with SARS-CoV-2 (COVID-19) illness severity or mortality in hospitalized patients with diabetes mellitus (DM) in a geographical region with low COVID-19 prevalence. RESEARCH DESIGN AND METHODS: A single-center retrospective study of patients hospitalized with COVID-19 from January 1 through August 31, 2020 to evaluate whether outpatient insulin use, HbA1c, glucose on admission, or average glucose during admission was associated with intensive care unit (ICU) admission, mechanical ventilation (ventilator) requirement, or mortality. RESULTS: Among 111 patients with DM, 48 (43.2%) were on outpatient insulin and the average HbA1c was 8.1% (65 mmol/mol). The average glucose on admission was 187.0±102.94 mg/dL and the average glucose during hospitalization was 173.4±39.8 mg/dL. Use of outpatient insulin, level of HbA1c, glucose on admission, or average glucose during hospitalization was not associated with ICU admission, ventilator requirement, or mortality among patients with COVID-19 and DM. CONCLUSIONS: Our findings in a region with relatively low COVID-19 prevalence suggest that neither outpatient glycemic control, glucose on admission, or inpatient glycemic control is predictive of illness severity or mortality in patients with DM hospitalized with COVID-19.
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COVID-19 , Diabetes Mellitus , Glucemia , Diabetes Mellitus/tratamiento farmacológico , Control Glucémico , Humanos , Pacientes Internos , Pacientes Ambulatorios , Estudios Retrospectivos , SARS-CoV-2RESUMEN
BACKGROUND: Perioperative diabetes patients are often treated with sliding-scale insulin, despite a lack of evidence to support therapeutic effectiveness. We introduced an automated subcutaneous insulin algorithm (SQIA) to improve glycemic control in these patients while maintaining the simplicity of a q4 hour adjustable sliding-scale insulin order set. METHODS: In this pilot study, we implemented a fully programmed, self-adjusting SQIA as part of a structured order set in the electronic medical record for adult patients who are nil per os, or on continuous enteral tube feedings or total parenteral nutrition. The nurse only enters the current glucose in the Medication Administration Record, and then the calculated dose is shown. The new dose is based on previous dose, and current and previous glucoses. The SQIA titrates the glucose to 120-180 mg/dL. For this pilot, this order set was utilized for complex perioperative oncologic patients. RESULTS: The median duration on the SQIA was 58 hours. Glucoses at titration initiation were highest at 206 ± 63 mg/dL, and came down to 156 ± 29 mg/dL by 72 hours. The majority of measured glucoses (66.8%, n = 647) were maintained between 80 and 180 mg/dL. There were no glucoses lower than 60 mg/dL, and only 0.3% (n = 3) were below 70 mg/dL. There was a low rate of errors (1%). CONCLUSIONS: A simple automated SQIA can be used to titrate insulin to meet the changing metabolic requirements of individuals perioperatively and maintain glucose within the target range for these hospitalized patients.
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Hiperglucemia , Insulina , Adulto , Algoritmos , Glucemia , Nutrición Enteral , Humanos , Hipoglucemiantes , Proyectos PilotoRESUMEN
This article is the work product of the Continuous Glucose Monitor and Automated Insulin Dosing Systems in the Hospital Consensus Guideline Panel, which was organized by Diabetes Technology Society and met virtually on April 23, 2020. The guideline panel consisted of 24 international experts in the use of continuous glucose monitors (CGMs) and automated insulin dosing (AID) systems representing adult endocrinology, pediatric endocrinology, obstetrics and gynecology, advanced practice nursing, diabetes care and education, clinical chemistry, bioengineering, and product liability law. The panelists reviewed the medical literature pertaining to five topics: (1) continuation of home CGMs after hospitalization, (2) initiation of CGMs in the hospital, (3) continuation of AID systems in the hospital, (4) logistics and hands-on care of hospitalized patients using CGMs and AID systems, and (5) data management of CGMs and AID systems in the hospital. The panelists then developed three types of recommendations for each topic, including clinical practice (to use the technology optimally), research (to improve the safety and effectiveness of the technology), and hospital policies (to build an environment for facilitating use of these devices) for each of the five topics. The panelists voted on 78 proposed recommendations. Based on the panel vote, 77 recommendations were classified as either strong or mild. One recommendation failed to reach consensus. Additional research is needed on CGMs and AID systems in the hospital setting regarding device accuracy, practices for deployment, data management, and achievable outcomes. This guideline is intended to support these technologies for the management of hospitalized patients with diabetes.
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Glucemia/análisis , Equipos y Suministros , Hospitalización , Sistemas de Infusión de Insulina , Insulina/administración & dosificación , Monitoreo Fisiológico/instrumentación , Adulto , Glucemia/efectos de los fármacos , Glucemia/metabolismo , Automonitorización de la Glucosa Sanguínea/instrumentación , Automonitorización de la Glucosa Sanguínea/métodos , Automonitorización de la Glucosa Sanguínea/normas , COVID-19 , Niño , Consenso , Infecciones por Coronavirus/sangre , Infecciones por Coronavirus/complicaciones , Infecciones por Coronavirus/epidemiología , Infecciones por Coronavirus/terapia , Complicaciones de la Diabetes/sangre , Complicaciones de la Diabetes/epidemiología , Complicaciones de la Diabetes/terapia , Diabetes Mellitus/sangre , Diabetes Mellitus/epidemiología , Diabetes Mellitus/terapia , Cálculo de Dosificación de Drogas , Equipos y Suministros/normas , Femenino , Hospitales/normas , Humanos , Sistemas de Infusión de Insulina/normas , Monitoreo Fisiológico/métodos , Monitoreo Fisiológico/normas , Pandemias , Neumonía Viral/sangre , Neumonía Viral/complicaciones , Neumonía Viral/epidemiología , Neumonía Viral/terapia , EmbarazoAsunto(s)
Infecciones por Coronavirus/prevención & control , Diabetes Mellitus Tipo 1 , Educación , Pandemias/prevención & control , Relaciones Padres-Hijo , Responsabilidad Parental , Neumonía Viral/prevención & control , Acceso a la Información/psicología , Adulto , Anciano , Anciano de 80 o más Años , Actitud Frente a la Salud , COVID-19 , Infecciones por Coronavirus/epidemiología , Infecciones por Coronavirus/psicología , Diabetes Mellitus Tipo 1/epidemiología , Diabetes Mellitus Tipo 1/psicología , Consejo Dirigido/normas , Consejo Dirigido/estadística & datos numéricos , Educación/organización & administración , Femenino , Humanos , Masculino , Persona de Mediana Edad , Responsabilidad Parental/psicología , Padres/psicología , Neumonía Viral/epidemiología , Neumonía Viral/psicología , Pautas de la Práctica en Medicina/normas , Pautas de la Práctica en Medicina/estadística & datos numéricos , Instituciones Académicas , Encuestas y CuestionariosRESUMEN
Electronic health record (EHR) systems can be configured to deliver novel EHR interventions that influence clinical decision making and to support efficient randomized controlled trials (RCTs) designed to evaluate the effectiveness, safety, and costs of those interventions. In designing RCTs of EHR interventions, one should carefully consider the unit of randomization (for example, patient, encounter, clinician, or clinical unit), balancing concerns about contamination of an intervention across randomization units within clusters (for example, patients within clinical units) against the superior control of measured and unmeasured confounders that comes with randomizing a larger number of units. One should also consider whether the key computational assessment components of the EHR intervention, such as a predictive algorithm used to target a subgroup for decision support, should occur before randomization (so that only 1 subgroup is randomized) or after randomization (including all subgroups). When these components are applied after randomization, one must consider expected heterogeneity in the effect of the differential decision support across subgroups, which has implications for overall impact potential, analytic approach, and sample size planning. Trials of EHR interventions should be reviewed by an institutional review board, but may not require patient-level informed consent when the interventions being tested can be considered minimal risk or quality improvement, and when clinical decision making is supported, rather than controlled, by an EHR intervention. Data and safety monitoring for RCTs of EHR interventions should be conducted to guide institutional pragmatic decision making about implementation and ensure that continuing randomization remains justified. Reporting should follow the CONSORT (Consolidated Standards of Reporting Trials) Statement, with extensions for pragmatic trials and cluster RCTs when applicable, and should include detailed materials to enhance reproducibility.
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Registros Electrónicos de Salud/organización & administración , Ensayos Clínicos Controlados Aleatorios como Asunto/estadística & datos numéricos , Humanos , Reproducibilidad de los ResultadosRESUMEN
OBJECTIVE: To increase awareness of unusual inflammatory and other responses including severe insulin resistance (IR) associated with the use of targeted immunotherapies such as brentuximab. METHODS: We report the case of a man without any previous diagnosis of diabetes who developed diabetic ketoacidosis complicated by severe IR (unresponsive to >600 units of intravenous insulin per hour) after receiving brentuximab for Hodgkin lymphoma. RESULTS: Autoantibodies to the insulin receptor were not detected in the patient's serum, thus excluding a diagnosis of type B IR. CONCLUSION: We hypothesize that brentuximab administration led to a rare reaction leading to systemic cytokine release with extreme IR in our patient.
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BACKGROUND: Acute hyperkalemia (serum potassium ≥ 5.1 mEq/L) is often treated with a bolus of IV insulin. This treatment may result in iatrogenic hypoglycemia (glucose < 70 mg/dl). OBJECTIVES: The aims of this study were to accurately determine the frequency of iatrogenic hypoglycemia following insulin treatment for hyperkalemia, and to develop an electronic health record (EHR) orderset to decrease the risk for iatrogenic hypoglycemia. DESIGN: This study was an observational, prospective study. SETTING: The setting for this study was a university hospital. PATIENTS: All nonobstetric adult inpatients in all acute and intensive care units were eligible. INTERVENTION: Implementation of a hyperkalemia orderset (Orderset 1.1) with glucose checks before and then one, two, four, and six hours after regular intravenous insulin administration. Based on the results from Orderset 1.1, Orderset 1.2 was developed and introduced to include weight-based dosing of insulin options, alerts identifying patients at higher risk of hypoglycemia, and tools to guide decision-making based on the preinsulin blood glucose level. MEASUREMENTS: Patient demographics, weight, diabetes history, potassium level, renal function, and glucose levels were recorded before, and then glucose levels were measured again at one, two, four, and six hours after insulin was administered. RESULTS: The iatrogenic hypoglycemia rate identified with mandatory glucose checks in Orderset 1.1 was 21%; 92% of these occurred within three hours posttreatment. Risk factors for hypoglycemia included decreased renal function (serum creatinine >2.5 mg/dl), a high dose of insulin (>0.14 units/kg), and re-treatment with blood glucose < 140 mg/dl. After the introduction of Orderset 1.2, the rate of iatrogenic hypoglycemia decreased to 10%. CONCLUSIONS: The use of an EHR orderset for treating hyperkalemia may reduce the risk of iatrogenic hypoglycemia in patients receiving insulin while still adequately lowering their potassium.