RESUMO
BACKGROUND: Inaccuracy in estimating reference intervals (RIs) is a problem with small sample sizes. OBJECTIVES: This study aimed to identify the most accurate statistical methods to estimate RIs based on sample size and population distribution shape. We also studied the accuracy of sample frequency distribution histograms to retrieve the original population distribution and compared strategies based on the histogram and goodness-of-fit test. METHODS: The statistical methods that best enhanced accuracy were determined for various sample sizes (n = 20-60) and population distributions (Gaussian, log-normal, and left-skewed) were determined by repeated-measures ANOVA and posthoc analyses. Frequency distribution histograms were built from 900 samples of five different sizes randomly extracted from six simulated populations. Three reviewers classified the population distributions from visual assessments of a sample histogram, and the classification error rate was calculated. RI accuracy was compared among the strategies based on the histograms and goodness-of-fit tests. RESULTS: The parametric, nonparametric, and robust methods enhanced lower reference limit estimation accuracy for Gaussian, log-normal, and left-skewed distributions, respectively. The parametric, nonparametric bootstrap, and nonparametric methods enhanced the upper limit estimation accuracy for Gaussian, log-normal, and left-skewed distributions, respectively. Regardless of sample size, sample histogram assessments properly classified the original population distribution 71% to 93.9% of the time, depending on the reviewers. In this study, the strategy based on histograms assessed by the statistician was significantly more precise and accurate than the strategy based on the goodness-of-fit test (P < 0.001). CONCLUSIONS: A strategy based on histograms might enhance the accuracy of RI estimations. However, relevant inter-reviewer variations in histogram interpretation were detected. Factors affecting inter-reviewer variations should be further explored.
Assuntos
Computadores , Animais , Simulação por Computador , Distribuição Normal , Valores de Referência , Tamanho da AmostraRESUMO
BACKGROUND: Different thromboplastins are available to measure prothrombin time (PT). Stago coagulation analyzers and reagents are currently used in veterinary laboratories and enable PT measurements to explore the coagulation cascade (extrinsic pathway). OBJECTIVES: The main objective was to compare PT measurements obtained with the STA-NeoPTimal reagent with the commonly used STA-Neoplastine CI Plus reagent. The secondary objective was to compare the PT ratio with the international normalized ratio (INR) calculated from our derived clotting times. METHODS: Analytical performance was evaluated with intra-assay and inter-assay precision. Seventy-two individual canine plasma samples were collected. Each sample was tested with both thromboplastins, using an STA Satellite Max analyzer. The PT, PT ratio, and INR values obtained with the two reagents were compared using Passing-Bablok regression for correlations and Bland-Altman plots for method agreements. RESULTS: The analytical performance of STA-NeoPTimal reagent was acceptable. Compared with the STA-Neoplastine CI Plus reagent, the STA-NeoPTimal reagent showed a positive proportional bias for PT values. Narrow range analyses showed good agreement for normal PT values (less than 9.5 seconds, internal reference cutoff with STA-Neoplastine CI Plus), and clinical concordance was achieved. When PT was prolonged (more than 9.5 seconds), PT increases were more marked with the STA-NeoPTimal reagent. Agreement was good for INR values across the whole range of PT results. CONCLUSION: STA-NeoPTimal can be reliably implemented in veterinary laboratories for canine PT measurements, as agreement between the PT results measured with the two reagents was clinically acceptable.