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Data on interference indices in body fluid specimens submitted for clinical laboratory analysis.

ABSTRACT: Clinical chemistry analysis of body fluids from non-blood or urine sources presents a technical challenge for clinical laboratories. Examples of body fluids include biliary secretions, cerebrospinal fluid, cyst contents, dialysate, gastric aspirates, peritoneal fluid, pleural fluid, stool, surgical drain fluid, synovial fluid, and wound exudates. The heterogeneous nature of these body fluids presents technical difficulties for analysis. For example, body fluid specimens may have presence of hemolysis, icterus, or lipemia ('interference indices') that can interfere with clinical chemistry analysis. In the related research article, we analyzed the distribution of these interference indices and body fluid samples submitted for analysis at an academic medical center central clinical laboratory and compared this to data from serum/plasma specimens. The data in this article provide the body fluid type, clinical chemistry testing ordered, interference indices, and whether the indices exceeded the manufacturer's recommendations in the package insert for serum/blood specimens. The analyzed data are provided in the supplementary tables included in this article. The dataset reported is related to the research article entitled "Review of interference indices in body fluids specimens admitted for clinical chemistry analyses" [1].

SUBMITTER: Eigsti RL

PROVIDER: S-EPMC7114902 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Data on interference indices in body fluid specimens submitted for clinical laboratory analysis.

Eigsti Renee L RL Krasowski Matthew D MD Vidholia Aditi A Merrill Anna E AE

Data in brief 20200310

Clinical chemistry analysis of body fluids from non-blood or urine sources presents a technical challenge for clinical laboratories. Examples of body fluids include biliary secretions, cerebrospinal fluid, cyst contents, dialysate, gastric aspirates, peritoneal fluid, pleural fluid, stool, surgical drain fluid, synovial fluid, and wound exudates. The heterogeneous nature of these body fluids presents technical difficulties for analysis. For example, body fluid specimens may have presence of hemo ...[more]

PMID: 32258276

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Project description:The presence of elevated levels of bilirubin (icterus) in serum or plasma specimens has the potential to interfere with clinical chemistry and other laboratory assays. Along with hemolysis and lipemia, icterus represents one of the most common endogenous interferences with laboratory tests. There are two common mechanisms by which icterus can cause assay interference. The first common mechanism is spectral interference due to absorption at wavelengths used in assays by bilirubin and/or bilirubin breakdown products. The second common mechanism involves chemical reaction of bilirubin with the reagents used in some enzymatic assays. Most automated clinical chemistry platforms can perform rapid estimates of indices for hemolysis, icterus, and lipemia (HIL), typically by measuring absorbance at wavelengths impacted by these interferences. The data in this article provides results from a detailed 12-month retrospective review of icteric indices and the impact on 114 clinical chemistry assays at an academic medical center in the United States. The data include 414,502 specimens from 94,081 unique patients (51,851 females; 42,230 males), with a total of 2,791,591 discrete clinical chemistry assays performed on the specimens. Detailed chart review was performed for all patients who had one or more specimens with an icteric index of 40 or higher ('severe icterus'), including determination of the medical diagnoses likely causing icterus and the mortality of these patients within 1 and 3 years following laboratory testing. Data for all specimens include patient location at time of testing (emergency department, inpatient unit, or outpatient site), sex, age, HIL indices, specific clinical chemistry assays performed, and number of times specimens had icteric indices exceeding the icteric index threshold in the package inserts for the clinical chemistry assays performed. The dataset reported is related to the research entitled "Frequency of Icteric Interference in Clinical Chemistry Laboratory Tests and Causes of Severe Icterus" [S. Mainali, A.E. Merrill, M.D. Krasowski, Frequency of icteric interference in clinical chemistry laboratory tests and causes of severe icterus, Pract. Lab. Med. (2021) 27: e00259].

Project description:BackgroundResistance to commonly used antimicrobials is a growing concern in both human and veterinary medicine. Understanding the temporal changes in the burden of the problem and identifying its determinants is important for guiding control efforts. Therefore, the objective of this study was to investigate temporal patterns and predictors of antimicrobial resistance among Staphylococcus spp. isolated from canine specimens submitted to the University of Kentucky Veterinary Diagnostic Laboratory (UKVDL) between 1993 and 2009.MethodsRetrospective data of 4,972 Staphylococcus isolates assessed for antimicrobial susceptibility using the disk diffusion method at the UKVDL between 1993 and 2009 were included in the study. Temporal trends were assessed for each antimicrobial using the Cochran-Armitage trend test. Logistic regression models were used to investigate predictors of antimicrobial resistance (AMR) and multidrug resistance (MDR).ResultsA total of 68.2% (3,388/4,972) Staphylococcus isolates were S. intermedius group (SIG), 18.2% (907/4,972) were coagulase-negative staphylococci (CoNS), 7.6% (375/4,972) were S. aureus, 5.8% (290/4,972) were S. hyicus, and S. schleiferi subsp. coagulans comprised 0.2% (12/4,972) of the isolates. The overall percentage of AMR and MDR were 77.2% and 25.6%, respectively. The highest levels of AMR were seen in CoNS (81.3%; 737/907), S. aureus (80.5%; 302/375), and SIG (77.6%; 2,629/3388). The lowest levels of AMR were observed in S. hyicus (57.9%; 168/290) and S. schleiferi subsp. coagulans (33.3%; 4/12). Overall, AMR and MDR showed significant (p<0.001) decreasing temporal trends. Significant temporal trends (both increasing and decreasing) were observed among 12 of the 16 antimicrobials covering 6 of the 9 drug classes assessed. Thus, significant increasing temporal trends in resistance were observed to ?-lactams (p<0.001) (oxacillin, amoxicillin-clavulanate, cephalothin, and penicillin (p = 0.024)), aminoglycosides (p<0.001) (gentamicin, and neomycin), bacitracin (p<0.001), and enrofloxacin (p<0.001). In contrast, sulfonamide (p<0.001) (sulfadiazin) and tetracycline (p = 0.010) resistant isolates showed significant decreasing temporal trends in AMR. Staphylococcus spp., geographic region, and specimen source were significant predictors of both AMR and MDR.ConclusionsAlthough not unexpected nor alarming, the high levels of AMR to a number of antimicrobial agents and the increasing temporal trends are concerning. Therefore, continued monitoring of AMR among Staphylococcus spp. is warranted. Future studies will need to identify local factors responsible for the observed geographic differences in risk of both AMR and MDR.

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Project description:BackgroundDuring the 2009 pandemic of an emerging influenza A virus (IAV; H1N1pdm09), data from several European countries indicated that the spread of the virus might have been interrupted by the annual autumn rhinovirus epidemic. We aimed to investigate viral interference between rhinovirus and IAV with use of clinical data and an experimental model.MethodsWe did a clinical data analysis and experimental infection study to investigate the co-occurrence of rhinovirus and IAV in respiratory specimens from adults (≥21 years) tested with a multiplex PCR panel at Yale-New Haven Hospital (CT, USA) over three consecutive winter seasons (Nov 1 to March 1, 2016-17, 2017-18, and 2018-19). We compared observed versus expected co-detections using data extracted from the Epic Systems electronic medical record system. To assess how rhinovirus infection affects subsequent IAV infection, we inoculated differentiated primary human airway epithelial cultures with rhinovirus (HRV-01A; multiplicity of infection [MOI] 0·1) or did mock infection. On day 3 post-infection, we inoculated the same cultures with IAV (H1N1 green fluorescent protein [GFP] reporter virus or H1N1pdm09; MOI 0·1). We used reverse transcription quantitative PCR or microscopy to quantify host cell mRNAs for interferon-stimulated genes (ISGs) on day 3 after rhinovirus or mock infection and IAV RNA on days 4, 5, or 6 after rhinovirus or mock infection. We also did sequential infection studies in the presence of BX795 (6 μM), to inhibit the interferon response. We compared ISG expression and IAV RNA and expression of GFP by IAV reporter virus.FindingsBetween July 1, 2016, and June 30, 2019, examination of 8284 respiratory samples positive for either rhinovirus (n=3821) or IAV (n=4463) by any test method was used to establish Nov 1 to March 1 as the period of peak virus co-circulation. After filtering for samples within this time frame meeting the inclusion criteria (n=13 707), there were 989 (7·2%) rhinovirus and 922 (6·7%) IAV detections, with a significantly lower than expected odds of co-detection (odds ratio 0·16, 95% CI 0·09-0·28). Rhinovirus infection of cell cultures induced ISG expression and protected against IAV infection 3 days later, resulting in an approximate 50 000-fold decrease in IAV H1N1pdm09 viral RNA on day 5 post-rhinovirus inoculation. Blocking the interferon response restored IAV replication following rhinovirus infection.InterpretationThese findings show that one respiratory virus can block infection with another through stimulation of antiviral defences in the airway mucosa, supporting the idea that interference from rhinovirus disrupted the 2009 IAV pandemic in Europe. These results indicate that viral interference can potentially affect the course of an epidemic, and this possibility should be considered when designing interventions for seasonal influenza epidemics and the ongoing COVID-19 pandemic.FundingNational Institutes of Health, National Institute of General Medical Sciences, and the Yale Department of Laboratory Medicine.

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Data on interference indices in body fluid specimens submitted for clinical laboratory analysis.

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Data on interference indices in body fluid specimens submitted for clinical laboratory analysis.

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