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Clinical laboratories invest substantial time and resources to mitigate measurement error but potential errors during the preanalytical phase of testing are not subjected to the same level of scrutiny. Herein, we assess the proportions of intravenous (IV) fluid contamination sufficient to exceed common performance metrics and compare it to contaminated results flagged by current protocols.

BackgroundThe coronavirus disease 2019 (COVID-19) pandemic caused a halt to in-person ambulatory care. We evaluated how the reduction in access to care affected HbA1c testing and patient HbA1c levels.MethodsHbA1c data from 11 institutions were extracted to compare testing volume and the percentage of abnormal results between a pre-pandemic period (January-June 2019, period 1) and a portion of the COVID-19 pandemic period (Jan-June 2020, period 2). HbA1c results greater than 6.4% were categorized as abnormal.ResultsHbA1C testing volumes decreased in March, April and May by 23, 61 and 40% relative to the corresponding months in 2019. The percentage of abnormal results increased in April, May and June (25, 23, 9%). On average, we found that the frequency of abnormal results increased by 0.31% for every 1% decrease in testing volume (p

BackgroundNumerous studies have documented reduced access to patient care due to the COVID-19 pandemic, including access to diagnostic or screening tests, prescription medications, and treatment for an ongoing condition. In the context of clinical management for venous thromboembolism, this could result in suboptimal therapy with warfarin. We aimed to determine the impact of the pandemic on utilization of International Normalized Ratio (INR) testing and the percentage of high and low results.MethodsINR data from 11 institutions were extracted to compare testing volume and the percentage of INR results ≥3.5 and ≤1.5 between a pre-pandemic period (January-June 2019, period 1) and a portion of the COVID-19 pandemic period (January-June 2020, period 2). The analysis was performed for inpatient and outpatient cohorts.ResultsTesting volumes showed relatively little change in January and February, followed by a significant decrease in March, April, and May, and then returned to baseline in June. Outpatient testing showed a larger percentage decrease in testing volume compared to inpatient testing. At 10 of the 11 study sites, we observed an increase in the percentage of abnormal high INR results as test volumes decreased, primarily among outpatients.ConclusionThe COVID-19 pandemic impacted INR testing among outpatients which may be attributable to several factors. Increased supratherapeutic INR results during the pandemic period when there was reduced laboratory utilization and access to care is concerning because of the risk of adverse bleeding events in this group of patients. This could be mitigated in the future by offering drive-through testing and/or widespread implementation of home INR monitoring.

Background A1C ≥6.0% is associated with increased risk of adverse outcomes in pregnant diabetic patients. A1C testing is recommended by the American Diabetes Association as a secondary measure of glycemic control in pregnant patients. Objective To determine the utility of A1C point-of-care testing (POCT) during pregnancy to facilitate rapid counseling and diabetes care, particularly in relatively low-income transient patient populations. Methods We performed a single-center, retrospective analysis of patients presenting to an outpatient obstetrics office with routine, in-laboratory A1C testing, before and after the implementation of POCT for A1C (n = 70 and n = 75, respectively). Demographics, results, physician referral to a nutritionist, counseling, and outcomes were retrieved from patient electronic medical records. Results In total, 9% and 23% of the in-laboratory and POCT groups, respectively, were referred for nutrition services (P =.02). Of these, 22% of the in-laboratory group and 42% of the POCT group received immediate counseling (P <.01). An inverse correlation was observed between A1C level at study entry and gestational weeks at delivery, with a Pearson r value of −0.39 (−0.58 to −0.16) for the in-laboratory group and −0.38 (−0.57 to −0.14) for the POCT group. No statistically significant difference in pregnancy outcomes was observed. Conclusion Implementation of A1C POCT was associated with immediate counseling and management of the health of pregnant patients, but was not associated with improved outcomes, in a low-resource patient population. [ABSTRACT FROM AUTHOR]

Free light chain (FLC) assays and the ratio of κ/λ are recommended for diagnosis, prognosis and monitoring of plasma cell dyscrasias (PCD). Limited data exists on FLC clinical specificity in patients diagnosed with other conditions. We assessed the κ, λ, and κ/λ FLC ratio using the FreeLite assay and the Sebia FLC ELISA assay in 176 patients with clinical presentations of fatigue, anemia, polyclonal hypergammaglobulinemia, joint disorders, kidney disease and non PCD-cancers with no monoclonal protein observed on serum protein electrophoresis or MASS-FIX immunoglobulin isotyping. Manufacturer defined reference intervals (RI) and glomerular filtration rate (GFR) specific RI (renal RI) were utilized. For the κ/λ ratio, 68.7 % (121/176) of specimens on the FreeLite and 87.5 % (154/176) of specimens on the Sebia assay were within RI. For κ, 68.2 % (120/176) and 72.2 % (127/176) of results were outside RI for FreeLite and Sebia respectively. For λ, 37.5 % (66/176) and 84.1 % (148/176) of FreeLite and Sebia results were outside RI. With FreeLite and Sebia, patients with kidney disease (n=25) had the highest κ/λ ratios. 44 patients (25.0 %) had GFR <60 mL/min/BSA. When renal RI were applied, 13.6 % had a FLCr outside the renal RI with FreeLite, and 4.5 % with Sebia. In a cohort of patients with signs and symptoms suggestive of PCDs, but ultimately diagnosed with other conditions, Sebia FLC had improved clinical specificity relative to FreeLite, if one was using an abnormal κ/λ ratio as a surrogate for monoclonality. [ABSTRACT FROM AUTHOR]

Background: Specimens contaminated with intravenous (IV) fluids are common in clinical laboratories. Current methods for detecting contamination rely on insensitive and workflow-disrupting delta checks or manual technologist review. Herein, we assessed the utility of large language models for detecting contamination by IV crystalloids and compared its performance to multiple, but variably trained healthcare personnel (HCP). Methods: Contamination of basic metabolic panels was simulated using 0.9% normal saline (NS), with (n = 30) and without (n = 30) 5% dextrose (D5NS), at mixture ratios of 0.10 and 0.25. A multimodal language model (GPT-4) and a diverse panel of 8 HCP were asked to adjudicate between real and contaminated results. Classification performance, mixture quantification, and confidence was compared by Wilcoxon rank sum. Results: The 95% CIs for accuracy were 0.57–0.71 vs 0.73–0.80 for GPT-4 and HCP, respectively, on the NS set and 0.57–0.57 vs 0.73–0.80 on the D5NS set. HCP overestimated severity of contamination in the 0.10 mixture group (95% CI of estimate error, 0.05–0.20) for both fluids, while GPT-4 markedly overestimated the D5NS mixture at both ratios (0.16–0.33 for NS, 0.11–0.35 for D5NS). There was no correlation between reported confidence and likelihood of a correct classification. Conclusions: GPT-4 is less accurate than trained HCP for detecting IV fluid contamination of basic metabolic panel results. However, trained individuals were imperfect at identifying contaminated specimens implying the need for novel, automated tools for its detection. [ABSTRACT FROM AUTHOR]