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1.
Arch Pathol Lab Med ; 139(10): 1295-301, 2015 Oct.
Artículo en Inglés | MEDLINE | ID: mdl-26414473

RESUMEN

CONTEXT: The perception of the severity of disease from laboratory results assumes that the results are free of analytical error; however, analytical error creates a spread of results into a band and thus a range of perceived disease severity. OBJECTIVE: To assess the impact of analytical errors by calculating the change in perceived disease severity, represented by the hazard ratio, using non-high-density lipoprotein (nonHDL) cholesterol as an example. DESIGN: We transformed nonHDL values into ranges using the assumed total allowable errors for total cholesterol (9%) and high-density lipoprotein cholesterol (13%). Using a previously determined relationship between the hazard ratio and nonHDL, we calculated a range of hazard ratios for specified nonHDL concentrations affected by analytical error. RESULTS: Analytical error, within allowable limits, created a band of values of nonHDL, with a width spanning 30 to 70 mg/dL (0.78-1.81 mmol/L), depending on the cholesterol and high-density lipoprotein cholesterol concentrations. Hazard ratios ranged from 1.0 to 2.9, a 16% to 50% error. Increased bias widens this range and decreased bias narrows it. CONCLUSIONS: Error-transformed results produce a spread of values that straddle the various cutoffs for nonHDL. The range of the hazard ratio obscures the meaning of results, because the spread of ratios at different cutoffs overlap. The magnitude of the perceived hazard ratio error exceeds that for the allowable analytical error, and significantly impacts the perceived cardiovascular disease risk. Evaluating the error in the perceived severity (eg, hazard ratio) provides a new way to assess the impact of analytical error.


Asunto(s)
HDL-Colesterol/sangre , Pruebas Diagnósticas de Rutina/normas , Lipoproteínas HDL/sangre , Índice de Severidad de la Enfermedad , Pruebas Diagnósticas de Rutina/métodos , Humanos , Reproducibilidad de los Resultados
2.
PLoS One ; 10(3): e0118108, 2015.
Artículo en Inglés | MEDLINE | ID: mdl-25738588

RESUMEN

BACKGROUND: Interpretation of parathyroid hormone (iPTH) requires knowledge of vitamin D status that is influenced by season. OBJECTIVE: Characterize the temporal relationship between 25-hydroxyvitamin D3 levels [25(OH)D3] and intact iPTH for several seasons, by gender and latitude in the U.S. and relate 25-hydrovitamin D2 [25(OH)D2] levels with PTH levels and total 25(OH)D levels. METHOD: We retrospectively determined population weekly-mean concentrations of unpaired [25(OH)D2 and 25(OH)D3] and iPTH using 3.8 million laboratory results of adults. The 25(OH)D3 and iPTH distributions were normalized and the means fit with a sinusoidal function for both gender and latitudes: North >40, Central 32-40 and South <32 degrees. We analyzed PTH and total 25(OH)D separately in samples with detectable 25(OH)D2 (≥4 ng/mL). FINDINGS: Seasonal variation was observed for all genders and latitudes. 25(OH)D3 peaks occurred in September and troughs in March. iPTH levels showed an inverted pattern of peaks and troughs relative to 25(OH)D3, with a delay of 4 weeks. Vitamin D deficiency and insufficiency was common (33% <20 ng/mL; 60% <30 ng/mL) as was elevated iPTH levels (33%>65 pg/mL). The percentage of patients deficient in 25(OH)D3 seasonally varied from 21% to 48% and the percentage with elevated iPTH reciprocally varied from 28% to 38%. Patients with detectable 25(OH)D2 had higher PTH levels and 57% of the samples with a total 25(OH)D > 50 ng/mL had detectable 25(OH)D2. INTERPRETATION: 25(OH)D3 and iPTH levels vary in a sinusoidal pattern throughout the year, even in vitamin D2 treated patients; 25(OH)D3, being higher in the summer and lower in the winter months, with iPTH showing the reverse pattern. A large percentage of the tested population showed vitamin D deficiency and secondary hyperparathyroidism. These observations held across three latitudinal regions, both genders, multiple-years, and in the presence or absence of detectable 25(OH)D2, and thus are applicable for patient care.


Asunto(s)
Hormona Paratiroidea/sangre , Deficiencia de Vitamina D/epidemiología , Vitamina D/análogos & derivados , Adulto , Anciano , Femenino , Humanos , Masculino , Persona de Mediana Edad , Estados Unidos , Vitamina D/sangre , Deficiencia de Vitamina D/sangre
3.
Arch Pathol Lab Med ; 129(8): 997-1003, 2005 Aug.
Artículo en Inglés | MEDLINE | ID: mdl-16048412

RESUMEN

CONTEXT: Proficiency testing (PT) participants can interpret their results to detect errors even when their performance is acceptable according to the limits set by the PT provider. OBJECTIVE: To determine which rules for interpreting PT data provide optimal performance for PT with 5 samples per event. DESIGN: We used Monte Carlo computer simulation techniques to study the performance of several rules, relating their error detection capabilities to (1) the analytic quality of the method, (2) the probability of failing PT, and (3) the ratio of the peer group SD to the mean intralaboratory SD. Analytic quality is indicated by the ratio of the PT allowable error to the intralaboratory SD. Failure of PT was defined (Clinical Laboratory Improvement Amendments of 1988) as an event when 2 or more results out of 5 exceeded acceptable limits. We investigated rules with limits based on the SD index, the mean SD index, and percentages of allowable error. RESULTS: No single rule performs optimally across the range of method quality. CONCLUSIONS: We recommend further investigation when PT data cause rejection by any of the following 3 rules: any result exceeds 75% of allowable error, the difference between any 2 results exceeds 4 times the peer group SD, or the mean SD index of all 5 results exceeds 1.5. As method quality increases from marginal to high, false rejections range from 16% to nearly zero, and the probability of detecting a shift equal to 2 times the intralaboratory SD ranges from 94% to 69%.


Asunto(s)
Química Clínica/normas , Competencia Clínica , Interpretación Estadística de Datos , Laboratorios/normas , Garantía de la Calidad de Atención de Salud , Método de Montecarlo , Control de Calidad , Reproducibilidad de los Resultados
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