UNASSIGNED: We report a case series of 4 patients with type 1 diabetes who used hybrid closed-loop insulin pumps (Medtronic MiniMed 670 G) during hospitalization.
UNASSIGNED: Clinical data and point-of-care glucose values are presented for each patient. Glucose values are shown graphically while in manual mode as well as in auto mode.
UNASSIGNED: The first case was a 30-year-old man admitted for pancreatitis. Mean point-of-care blood glucose was 165.7 mg/dL while in auto mode, without hypoglycemia, compared with 221 mg/dL while in manual mode. The second case was a 28-year-old woman who was admitted for a laparoscopic cholecystectomy. Mean point-of-care blood glucose in auto mode was 131.3 mg/dL, without hypoglycemia, compared with 117.6 mg/dL while in manual mode. The third case was a 46-year-old man admitted to the intensive care unit for influenzal pneumonia. Mean point-of-care blood glucose in auto mode was 159.1 mg/dL without hypoglycemia, compared with 218.5 mg/dL while in manual mode. The fourth case was a 60-year-old man who remained in auto mode throughout his hospitalization except for a period when he removed his pump for an endoscopic retrograde cholangiopancreatography and endoscopic ultrasound. His mean point-of-care blood glucose while in auto mode was 156.8 mg/dL without hypoglycemia.
UNASSIGNED: These case reports support the use of hybrid closed-loop insulin-pump therapy in the inpatient setting to maintain inpatient glycemic targets and avoid hypoglycemia when part of an institution-sanctioned strategy for safe use of insulin pumps that includes point-of-care blood glucose monitoring.

UNASSIGNED: Sodium-glucose cotransporter-2 (SGLT2) inhibitors are a relatively novel class of oral medications for the treatment of type 2 diabetes mellitus (T2DM). Their use has increased recently due to their beneficial renal and cardiovascular outcomes, but they come with the rare risk of diabetic ketoacidosis (DKA) at normal or slightly elevated glucose values, termed euglycemic DKA (euDKA). Recently, carbohydrate-deprived, ketogenic diets have gained popularity due to benefits of weight loss and improved control of T2DM. We describe 2 patients with T2DM who developed euDKA caused by SGLT2 inhibitor use while on a ketogenic diet and provide a review of the literature.
UNASSIGNED: We describe the hospital course, laboratory data, and treatment of 2 patients and provide a literature review.
UNASSIGNED: Both of our patients were found to have normal or mildly elevated serum glucose levels, with an elevated anion gap and ketosis, representative of euDKA. The first patient developed euDKA after only 1 dose of empagliflozin, while the second patient developed euDKA after only 1 week of being on a ketogenic diet while on an SGLT2 inhibitor.
UNASSIGNED: While there have been a few reports of euDKA with SGLT2 inhibitors and ketogenic diets, many physicians prescribing these medications may not be aware of this association. Therefore, they must inform their patients to avoid a ketogenic diet if on an SGLT2 inhibitor. If a patient presents with symptoms of DKA and is eating a carbohydrate-free diet while taking an SGLT2 inhibitor, there should be a low threshold to screen for DKA.

UNASSIGNED: Diabetes mellitus has been recognized as one of the comorbidities that predict the severity of illness in patients infected with COVID-19. The characteristics of patients presenting with diabetic ketoacidosis (DKA) and COVID-19 infection have not been described.
UNASSIGNED: We describe 5 patients with DKA and concomitant COVID-19 admitted to the intensive care unit of an academic medical center. Three patients had type 1 diabetes mellitus, and 2 patients had type 2 diabetes mellitus.
UNASSIGNED: While DKA with an infectious etiology is a common presentation, we observed that the patients with DKA precipitated by COVID-19 presented with atypical symptoms. COVID-19 infection was revealed during search for an etiology of DKA.
UNASSIGNED: It is prudent to have a low threshold to screen for COVID-19 infection in patients with DKA.

UNASSIGNED: To develop and validate a phenotyping algorithm for the identification of patients with type 1 and type 2 diabetes mellitus (DM) preoperatively using routinely available clinical data from electronic health records.
UNASSIGNED: We used first-order logic rules (if-then-else rules) to imply the presence or absence of DM types 1 and 2. The \"if\" clause of each rule is a conjunction of logical and, or predicates that provides evidence toward or against the presence of DM. The rule includes International Classification of Diseases, Ninth Revision, Clinical Modification diagnostic codes, outpatient prescription information, laboratory values, and positive annotation of DM in patients\' clinical notes. This study was conducted from March 2, 2015, through February 10, 2016. The performance of our rule-based approach and similar approaches proposed by other institutions was evaluated with a reference standard created by an expert reviewer and implemented for routine clinical care at an academic medical center.
UNASSIGNED: A total of 4208 surgical patients (mean age, 52 years; males, 48%) were analyzed to develop the phenotyping algorithm. Expert review identified 685 patients (16.28% of the full cohort) as having DM. Our proposed method identified 684 patients (16.25%) as having DM. The algorithm performed well-99.70% sensitivity, 99.97% specificity-and compared favorably with previous approaches.
UNASSIGNED: Among patients undergoing surgery, determination of DM can be made with high accuracy using simple, computationally efficient rules. Knowledge of patients\' DM status before surgery may alter physicians\' care plan and reduce postsurgical complications. Nevertheless, future efforts are necessary to determine the effect of first-order logic rules on clinical processes and patient outcomes.

暂无摘要。