CoaguChek and Coag-Sense PT2 Meter Point of Care INR Device Validation.

OBJECTIVE: To standardize international normalized ratio (INR) measurements and improve data integrity by enabling electronic result transmission for warfarin monitoring, two point-of-care (POC) devices were evaluated against an internal plasma INR reference method. METHODS: A multicenter study was pursued (January 24, 2022, through October 19, 2022) to compare concordance of two commercially available POC devices, Coag-Sense PT2 Meter (Coag-Sense) and CoaguChek XS Pro and Plus devices (CoaguChek), against an internal plasma INR method among patients treated with warfarin. Bias and linear regression analysis were assessed for these devices including dosing decision accuracy compared with plasma INR reference. RESULTS: Two hundred ninety-nine patients treated with warfarin across three Mayo Clinic sites agreed to participate. Atrial fibrillation (n=191, 63.9%), venous thromboembolism (n=65; 21.7%), and heart valve prosthesis (n=46; 15.4%) were common anticoagulant indications with a 2.5 INR target for 280 (93.6%) of patients. For the CoaguChek devices, 243 (81.3%) of values fell within 0.2 INR units with plasma INR referent and 285 (95.3%) within 0.4 units (R2=0.93). For the Coag-Sense device, 102 (34.1%) of values fell within 0.2 INR units and 180 (60.2%) within 0.4 INR units of plasma INR values, (R2=0.83; P<.0001). Using the plasma INR as the gold standard, appropriate dosing recommendations would have occurred for 292 (97.7%) of the CoaguChek and 244 (81.6%) of the Coag-Sense results. CONCLUSION: Compared with a plasma referent, INR values obtained from the CoaguChek devices exhibited less systematic bias compared with Coag-Sense measures. This translates to a greater percentage of concordant management decisions between POC and laboratory INR methods.

Temporal and geographic patterns of hypoglycemia among hospitalized patients with diabetes mellitus.

BACKGROUND: Hypoglycemia is often cited as a barrier to achieving inpatient glycemic targets. We sought to characterize hypoglycemic events in our institution by work-shift cycle and by specific treatment area. METHODS: Capillary (bedside) and blood (laboratory) glucose values of <70 mg/dl for patients with either a known diagnosis of diabetes or with evidence of hyperglycemia were abstracted from our laboratory database for hospitalizations between October 1, 2007, and February 3, 2008. Hypoglycemic events were analyzed by 12 h nursing work-shift cycles (day shift, 07:00 to 18:59; night shift, 19:00 to 06:59) and by the six medical, surgical, and intensive care areas in the hospital (designated areas 1 to 6). RESULTS: We identified 206 individual patients with either diabetes or hyperglycemia (mean age, 67 years; 56% men; 83% white) who had 423 hypoglycemic events. There were 78% more hypoglycemic events during the night shift (n = 271 events in 128 individual patients) than during the day shift (n = 152 events in 96 individual patients). Most of the night-shift hypoglycemic measurements were detected between 04:00 and 04:59 or 06:00 and 06:59. The mean hypoglycemic level was comparable between shifts (p = .79) and across the six inpatient areas. The number of hypoglycemic events per person increased with lengths of hospital stay >5 days. The prevalence of hypoglycemia varied across patient care areas within the hospital, with most (28%) detected in one area of the hospital. CONCLUSION: There are temporal and geographic patterns in the occurrence of hypoglycemia among patients with diabetes or hyperglycemia in our hospital. Further study should focus on the reasons underlying these variations so that specific interventions can address the risk of hypoglycemia during peak times and places.