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Background: Diagnostic sensitivities of point-of-care SARS-CoV-2 assays depend on specimen type and population-specific viral loads. Evaluation of these assays require "direct" specimens from paired-swab studies rather than more accessible residual specimens in viral transport media (VTM)., Methods: Residual VTM and limit-of-detection studies were conducted on Abbott ID NOW™ COVID-19, Quidel Sofia 2™ SARS Antigen FIA, and DiaSorin Simplexa™ COVID-19 Direct assays, with cycle threshold (CT) adjustments to approximate direct-specimen testing based on gene-target doubling each PCR cycle. Logistic regression was used to model assay performance by specimen CT. These models were applied to CT distributions of symptomatic and asymptomatic populations presenting to emergency services to predict the percentage of specimens that would be detected by each assay. A 96-sample paired-swab study was conducted to confirm model results., Results: When using direct nasopharyngeal samples and fit with either VTM or limit-of-detection data, percent positivities for ID NOW (symptomatic 94.9%/97.4%; asymptomatic 88.4.0%/89.6%) and Simplexa (symptomatic 97.8%/97.2%; asymptomatic 91.1%/90.8%) were predicted to be similar. Likewise, percent positivities for ID NOW with direct nasal specimens (symptomatic 77.8%; asymptomatic 64.5%) and, fit with VTM data, Sofia 2 with direct nasopharyngeal specimens (symptomatic 76.6%, asymptomatic 60.3%) were similar. The paired-swab study comparing direct nasopharyngeal specimens on ID NOW and nasopharyngeal VTM specimens on Simplexa showed 99% concordance., Conclusions: Assay performance can be modeled as dependent on viral load, fit using laboratory bench study results, and adjusted to account for direct-specimen testing. When using nasopharyngeal specimens, direct testing on Abbott ID NOW and VTM testing on DiaSorin Simplexa have similar performance., (© American Association for Clinical Chemistry 2022. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Objectives: Serologic testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has experienced a changing landscape of available assays coupled with uncertainty surrounding performance characteristics. Studies are needed to directly compare multiple commercially available assays., Methods: Residual serum samples were identified based on SARS-CoV-2 reverse transcription polymerase chain reaction (RT-PCR) testing, clinical test results, and collection dates. Serum samples were analyzed using assays from four different manufacturers: DiaSorin anti-SARS-CoV-2 S1/S2 IgG, EUROIMMUN anti-SARS-CoV-2 IgG ELISA, Roche Elecsys anti-SARS-CoV-2, and Siemens SARS-CoV-2 Total antibody assays., Results: Samples from SARS-CoV-2 RT-PCR-positive patients became increasingly positive as time from symptom onset increased. For patients with latest sample 14 or more days after symptom onset, sensitivities reached 93.1% to 96.6%, 98.3%, and 96.6% for EUROIMMUN, Roche, and Siemens assays, respectively, which were superior to the DiaSorin assay at 87.7%. The specificity of Roche and Siemens assays was 100% and superior to DiaSorin and EUROIMMUN assays, which ranged from 96.1% to 97.0% and 86.3% to 96.4%, respectively., Conclusions: Laboratories should be aware of the advantages and limitations of serology testing options for SARS-CoV-2. The specificity and sensitivity achieved by the Roche and Siemens assays would be acceptable for testing in lower-prevalence regions and have the potential of orthogonal testing advantages if used in combination., (© American Society for Clinical Pathology, 2020.)

Background: We determined the availability and pricing of laboratory testing in the Northern Region of Ghana to identify current gaps with respect to the WHO's Essential Diagnostics List (EDL)., Methods: A representative sample of facilities offering diagnostic testing within the Northern Region was geographically mapped and evaluated, with random sampling stratified by population density. Data were collected on testing menus, volumes, turn-around times, and out-of-pocket test prices. A total of 27 health centers and 39 clinical laboratories were surveyed between June and August 2019., Results: Health centers offered a median of 2 of 20 tests recommended by the WHO for facilities without laboratories. The most common tests offered included point-of-care tests for malaria, HIV, and pregnancy. Clinical laboratories offered a median of 11 of 72 tests on the EDL. These facilities most commonly provided testing for malaria, HIV, pregnancy, HBsAg, urinalysis, HCV Ab, syphilis, glucose, and CBC. Urban laboratories had a total of 36 EDL tests available while rural laboratories had 12. Test prices were higher in private compared to public laboratories. National Health Insurance reimbursements were lower than out-of-pocket prices (38%), and when controlling for test price, test availability was negatively associated with this gap in reimbursement., Conclusions: Availability of diagnostic testing in Ghana's Northern Region is severely limited compared to the WHO's EDL. The disparity is pronounced in rural facilities. Reimbursement rates should be reset to more closely match out-of-pocket test prices in order to achieve the Universal Health Coverage target of the Sustainable Development Goals., (© American Association for Clinical Chemistry 2020. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: There are numerous barriers to achieving high-quality laboratory diagnostic testing in resource-limited countries. These include inconsistent supply chains, variable quality of diagnostic devices, lack of human and financial resources, the ever-growing list of available tests, and a historical reliance on syndromic treatment algorithms. A list of essential diagnostics based on an accepted standard like the WHO Essential Medicines List (EML) could coordinate stakeholders in the strengthening of laboratory capacity globally., Methods: To aid in the creation of an essential diagnostics list (EDL), we identified laboratory test indications from expert databases for the safe and effective use of WHO EML medicines. In all, 446 EML medicines were included in the study. We identified 279 conditions targeted by these medicines, spanning communicable and noncommunicable diseases (e.g., HIV, diabetes mellitus)., Results: We found 325 unique diagnostic tests, across 2717 indications, associated with the identified conditions or their associated medicines. The indications were divided into 10 categories: toxicity (865), diagnosis (591), monitoring (379), dosing/safety (325), complications (217), pathophysiology (154), differential diagnosis (97), comorbidities (53), drug-susceptibility testing (22), and companion diagnostic testing (14). We also created a sublist of 74 higher-priority tests to help define the core of the EDL., Conclusions: An EDL such as we describe here could align the global health community to solve the problems impeding equitable access to high-quality diagnostic testing in support of the global health agenda., (© 2018 American Association for Clinical Chemistry.)

Objectives: We evaluated the effect of diabetes on sickle hemoglobin (HbS) measurement on two common clinical hemoglobin separation platforms., Methods: We performed a method comparison between the Bio-Rad Variant II high-performance liquid chromatography (HPLC) and Sebia Capillarys 2 Flex Piercing capillary electrophoresis (CE) using clinical specimens from 38 patients without hemoglobin variants and 57 patients with sickle cell trait (AS) (HbA1c%, 4.1%-15.4%). We investigated the effect of intermethod Hb% differences on result interpretation by a panel of expert clinical observers., Results: In diabetic specimens, HPLC undermeasured HbS% up to 7.4% vs CE, due to S1c eluting closely with A0 in HPLC. This increased concern for underlying α-thalassemia in diabetic patients with AS based on HPLC results. HPLC P2% was linearly related to HbA1c% and can be a screen for diabetic AS samples., Conclusions: Glycosylation can interfere with HbS% measurement by HPLC. Susceptible specimens should be identified and preferentially analyzed via CE.

Introduction: M-protein quantification is routinely performed by demarcating serum protein electrophoresis (SPE) regions. However, quantification of β-migrating M-protein is hindered by overlapping nonimmunoglobulin protein. Immunosubtraction (ISUB) on capillary electrophoresis is a method currently used qualitatively to subtract out (and therefore highlight) immunoglobulin isotypes in serum, thus reducing the masking effect of normal serum proteins. This study expands on traditional ISUB by developing a quantitative immunosubtraction (qIS) methodology., Methods: qIS is achieved by estimating the monoclonal class-specific immunoglobulin contribution to the SPE region containing the M-protein. We conducted a recovery study by use of serial dilutions from 3 patients with β-region M-proteins (n = 22), performing SPE and ISUB on each dilution. We visualized the difference between the ISUB electrophoresis trace and the involved ISUB isotype-subtracted trace to distinguish M-protein and background polyclonal immunoglobulins, which was demarcated independently by 3 pathologists. The M-protein contribution to the β-region was calculated and applied to the β-region protein concentration producing the quantitative M-protein concentration, while minimizing contamination by nonimmunoglobulin or polyclonal immunoglobulin proteins., Results: Using a quality target of 25% error, we determined that our analytical measurable range spanned the maximum concentration tested (0.81 g/dL) to 0.05 g/dL. Passing-Bablok regression between qIS and the expected M-protein produced a slope of 1.04 (95% CI, 0.94-1.09), r = 0.99. Total CV was 4.8% and intraclass correlation between pathologists was 0.998., Discussion: qIS promises quantification of β-migrating M-proteins at concentrations an order of magnitude lower than traditional SPE methodology, allowing earlier detection of increasing or decreasing M-protein., (© 2017 American Association for Clinical Chemistry.)

Background: The electronic medical record (EMR) holds a promising source of data for active postmarket surveillance of diagnostic accuracy, particularly for point-of-care (POC) devices. Through a comparison with prospective bedside and laboratory accuracy studies, we demonstrate the validity of active surveillance via an EMR data mining method [Data Mining EMRs to Evaluate Coincident Testing (DETECT)], comparing POC glucose results to near-in-time central laboratory glucose results., Methods: The Roche ACCU-CHEK Inform II(®) POC glucose meter was evaluated in a laboratory validation study (n = 73), a prospective bedside intensive care unit (ICU) study (n = 124), and with DETECT (n = 852-27 503). For DETECT, the EMR was queried for POC and central laboratory glucose results with filtering based on of bedside collection timestamps, central laboratory time delays, patient location, time period, absence of repeat testing, and presence of peripheral lines., Results: DETECT and the bedside ICU study produced similar estimates of average bias (4.5 vs 5.0 mg/dL) and relative random error (6.3% vs 5.6%), with overlapping CIs. For glucose <100 mg/dL, the laboratory validation study estimated a lower relative random error of 3.6%. POC average bias correlated with central laboratory turnaround times, consistent with 4.8 mg · dL(-1) · h(-1) glycolysis. After glycolysis adjustment, average bias was estimated by the bedside ICU study at -0.4 mg/dL (CI, -1.6 to 0.9) and DETECT at -0.7 (CI, -1.3 to 0.2), and percentage POC results occurring outside Clinical Laboratory Standards Institute quality goals were 2.4% and 4.8%, respectively., Conclusions: This study validates DETECT for estimating POC glucose meter accuracy compared with a prospective bedside ICU study and establishes it as a reliable postmarket surveillance methodology., (© 2016 American Association for Clinical Chemistry.)

Objectives: To describe key characteristics (laboratory quality, test volumes, and complexity) of clinical laboratories in Kampala, Uganda (population ~1.7 million)., Methods: Cross-sectional survey using a standard questionnaire to document laboratory type and quality, as well as test menus and volumes. Quality was based on the World Health Organization-Africa Region checklist., Results: Of the 954 laboratories identified (a density of one laboratory per 1,781 persons), 779 (82%) performed only simple kit tests or light microscope examinations. The 95% (907/954) of laboratories for whom volumes were obtained performed an average aggregate of 13,189 tests daily, for a test utilization rate of around 2 tests per individual per year. Laboratories could be segregated into eight groups based on quality, test volume, and complexity. However, 90% of the testing was performed by just two groups: (1) low-volume (≤100 tests daily), low-quality laboratories performing simple tests or (2) high-volume (>100 tests daily), high-quality laboratories. Each of these two groups did 45% of the daily testing volume (90% combined)., Conclusions: Clinical laboratory density in Kampala (1/1,781 persons) is high, approaching that in the United States (1/1,347 persons). Low-volume/low-quality and high-volume/high-quality laboratories do 90% of the daily aggregate testing. Quality improvement (QI) schemes for Africa must be appropriate to low-volume laboratories as well as to the large laboratories that have been the focus of previous QI efforts., (Copyright© by the American Society for Clinical Pathology.)

Objectives: A recent survey of laboratories in Kampala, Uganda, demonstrated that only 0.3% of laboratories (3/954) met international quality standards. To benchmark laboratory quality throughout the rest of sub-Saharan Africa (SSA), we compiled a list of SSA laboratories meeting international quality standards., Methods: Accrediting bodies were queried via online registries or direct communication in May 2013., Results: There were 380 laboratories accredited to international standards in SSA. Ninety-one percent were in South Africa. Thirty-seven of 49 countries had no laboratories accredited to international quality standards. Accredited laboratory density (per million people) in South Africa, Namibia, and Botswana were similar to those in many European countries. Single variable linear regression showed a correlation between accredited laboratory density and health expenditures per person (adjusted R(2) = 0.81, P < .001)., Conclusions: Most SSA countries do not have an accredited clinical laboratory. For those that do, there is a strong correlation between country-specific accredited laboratory density and per-capita health expenditures., (Copyright© by the American Society for Clinical Pathology.)