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PURPOSE: There is a lack of a clear, uniform definition for intraoperatively assessed component loosening of a knee arthroplasty component, complicating the interpretation and interchangeability of results of diagnostic studies using an intraoperative observation as the reference test. The purpose of this study was to establish a consensus among specialised knee revision surgeons regarding the definition of intraoperatively determined loosening of total or unicondylar knee arthroplasty components. METHODS: Utilising the Delphi consensus method, an international panel of highly specialised knee revision surgeons was invited to participate in a three-round process. The initiation of the first round involved the exploration of possible criteria for intraoperatively determined loosening with open questions. The second round focused on rating these criteria importance on a five-point Likert scale. For the third round, criteria that reached consensus were summarised in consecutive definitions for intraoperatively determined loosening and proposed to the panel. Consensus was established when over 70% of participants agreed with a definition for intraoperatively determined loosening. RESULTS: The 34 responding panel members described in total 60 different criteria in the first round of which 34 criteria received consensus in the second round. Summarising these criteria resulted in four different definitions as minimal requirements for intraoperatively determined loosening. Eighty-eight percent of the panel members agreed on defining a component as loose if there is visible fluid motion at the interface observed during specific movements or when gently applying direct force. CONCLUSION: This study successfully established a consensus using a Delphi method among knee revision surgeons on the definition of intraoperatively determined component loosening. By agreeing on the visibility of fluid motion as new definition, this study provides a standardised reference for future diagnostic research. This definition will enhance the interpretability and interchangeability of future diagnostic studies evaluating knee arthroplasty component loosening. LEVEL OF EVIDENCE: Level V.
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Diagnostic accuracy, a measure of diagnostic tests for correctly identifying patients with or without a target disease, plays an important role in evidence-based medicine. Diagnostic accuracy of a new test ideally should be evaluated by comparing to a gold standard; however, in many medical applications it may be invasive, costly, or even unethical to obtain a gold standard for particular diseases. When the accuracy of a new candidate test under evaluation is assessed by comparison to an imperfect reference test, bias is expected to occur and result in either overestimates or underestimates of its true accuracy. In addition, diagnostic test studies often involve repeated measurements of the same patient, such as the paired eyes or multiple teeth, and generally lead to correlated and clustered data. Using the conventional statistical methods to estimate diagnostic accuracy can be biased by ignoring the within-cluster correlations. Despite numerous statistical approaches have been proposed to tackle this problem, the methodology to deal with correlated and clustered data in the absence of a gold standard is limited. In this article, we propose a method based on the composite likelihood function to derive simple and intuitive closed-form solutions for estimates of diagnostic accuracy, in terms of sensitivity and specificity. Through simulation studies, we illustrate the relative advantages of the proposed method over the existing methods that simply treat an imperfect reference test as a gold standard in correlated and clustered data. Compared with the existing methods, the proposed method can reduce not only substantial bias, but also the computational burden. Moreover, to demonstrate the utility of this approach, we apply the proposed method to the study of National-Eye-Institute-funded Telemedicine Approaches to Evaluating of Acute-Phase Retinopathy of Prematurity (e-ROP), for estimating accuracies of both the ophthalmologist examination and the image evaluation.
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Oftalmopatías , Recien Nacido Prematuro , Sesgo , Humanos , Recién Nacido , Funciones de Verosimilitud , Sensibilidad y EspecificidadRESUMEN
Campylobacter spp. enteritis is the most frequent bacterial enteritis in both adults and children and is sometimes a source of severe complications. Its diagnosis by culture suffers from a lack of sensitivity and delays the result, preventing an early initiation of optimal antibiotic therapy in some cases. Our aim was to test a new rapid immuno-enzymatic method for Campylobacter spp. diagnosis in comparison to a composite reference standard (CRS). Stool samples from the French National Reference Center for Campylobacter and Helicobacter were tested with the CAMPYLOBACTER QUIK CHEK™ (Abbott). The CRS used to consider a case positive for Campylobacter spp. was a positive culture and, in case of a negative culture, a positive result obtained with both an ELISA and a molecular test. One hundred and eight stools were included: 53 were positive according to the CRS. If performed alone, culture would have missed 5 cases which the CAMPYLOBACTER QUIK CHEK™ detected. Finally, the CAMPYLOBACTER QUIK CHEK™ showed a sensitivity of 96.2% and a specificity of 94.5% and is relevant for clinical practice. Given the characteristics of the new method, it can be used as a screening method for Campylobacter spp. detection.
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Estimating biomarker-index accuracy when only imperfect reference-test information is available is usually performed under the assumption of conditional independence between the biomarker and imperfect reference-test values. We propose to define a latent normally-distributed tolerance-variable underlying the observed dichotomous imperfect reference-test results. Subsequently, we construct a Bayesian latent-class model based on the joint multivariate normal distribution of the latent tolerance and biomarker values, conditional on latent true disease status, which allows accounting for conditional dependence. The accuracy of the continuous biomarker-index is quantified by the AUC of the optimal linear biomarker-combination. Model performance is evaluated by using a simulation study and two sets of data of Alzheimer's disease patients (one from the memory-clinic-based Amsterdam Dementia Cohort and one from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database). Simulation results indicate adequate model performance and bias in estimates of the diagnostic-accuracy measures when the assumption of conditional independence is used when, in fact, it is incorrect. In the considered case studies, conditional dependence between some of the biomarkers and the imperfect reference-test is detected. However, making the conditional independence assumption does not lead to any marked differences in the estimates of diagnostic accuracy.
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Biomarcadores/análisis , Teorema de Bayes , Demencia , HumanosRESUMEN
Several statistical methods for meta-analysis of diagnostic accuracy studies have been discussed in the presence of a gold standard. However, in practice, the selected reference test may be imperfect due to measurement error, non-existence, invasive nature, or expensive cost of a gold standard. It has been suggested that treating an imperfect reference test as a gold standard can lead to substantial bias in the estimation of diagnostic test accuracy. Recently, two models have been proposed to account for imperfect reference test, namely, a multivariate generalized linear mixed model (MGLMM) and a hierarchical summary receiver operating characteristic (HSROC) model. Both models are very flexible in accounting for heterogeneity in accuracies of tests across studies as well as the dependence between tests. In this article, we show that these two models, although with different formulations, are closely related and are equivalent in the absence of study-level covariates. Furthermore, we provide the exact relations between the parameters of these two models and assumptions under which two models can be reduced to equivalent submodels. On the other hand, we show that some submodels of the MGLMM do not have corresponding equivalent submodels of the HSROC model, and vice versa. With three real examples, we illustrate the cases when fitting the MGLMM and HSROC models leads to equivalent submodels and hence identical inference, and the cases when the inferences from two models are slightly different. Our results generalize the important relations between the bivariate generalized linear mixed model and HSROC model when the reference test is a gold standard.
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Pruebas Diagnósticas de Rutina/estadística & datos numéricos , Metaanálisis como Asunto , Modelos Estadísticos , Artritis Reumatoide/diagnóstico , Biometría , Angiografía Coronaria/normas , Angiografía Coronaria/estadística & datos numéricos , Enfermedad de la Arteria Coronaria/diagnóstico , Enfermedad de la Arteria Coronaria/diagnóstico por imagen , Pruebas Diagnósticas de Rutina/normas , Medicina Basada en la Evidencia/normas , Medicina Basada en la Evidencia/estadística & datos numéricos , Femenino , Humanos , Modelos Lineales , Análisis Multivariante , Prueba de Papanicolaou/normas , Prueba de Papanicolaou/estadística & datos numéricos , Curva ROC , Estándares de Referencia , Factor Reumatoide/análisis , Tomografía Computarizada por Rayos X/normas , Tomografía Computarizada por Rayos X/estadística & datos numéricos , Neoplasias del Cuello Uterino/diagnósticoRESUMEN
Antimicrobial resistance (R) surveillance across Asia and especially in China has documented unique patterns and mechanisms. This 2011 study reports results for 2278 isolates from 12 hospitals in China (94-216 strains/site); most from bacteremia (20.4%), pneumonias (29.1%), or skin and skin structure infections (20.9%). Samples were tested by reference broth microdilution methods, interpreted by published susceptibility (S) breakpoints. The most common species were Staphylococcus aureus (343, 45.8% MRSA), Escherichia coli (EC; 288), Pseudomonas aeruginosa (PSA; 221), Klebsiella spp. (KSP; 208), acinetobacters (ACB; 178), enterobacters (155), Streptococcus pneumoniae (SPN; 154, 46.8% penicillin-S), and enterococci (ENT; 137). Among 849 Gram-positive (GP) cocci, linezolid, tigecycline (TIG), daptomycin, and vancomycin provided best antimicrobial coverage (≥99.7% S). Resistance patterns of concern were 0.3% VISA, 15.4% teicoplanin non-S coagulase-negative staphylococci, 1.5% vancomycin-R ENT (all Enterococcus faecium), 1.9% levofloxacin-R ß-haemolytic streptococci, and 35.1 and 12.7% ceftriaxone-non-S rates for SPN and viridans group streptococci, respectively. For Gram-negative bacilli, R among Enterobacteriaceae was highest against ß-lactams (extended spectrum ß-lactamase-phenotype strains at 73.6 and 42.8% in EC and KSP, respectively; carbapenem-R was only 2.1-4.3% with KPC and IMP type enzymes detected in KSP). The widest spectrum agents were cefoperazone/sulbactam (79.5-86.1%), piperacillin/tazobactam (88.9-92.0%), TIG (98.6-100%), amikacin (AMK; 91.8-93.7%), and meropenem (95.7-97.1% S). PSA was most inhibited by AMK (90.5% S) and colistin (COL; 99.5%), with cefepime (67.9%) best among the tested ß-lactams. Only COL (100% S) and TIG (MIC90, 2 µg/mL) showed significant potencies against ACB. In conclusion, R among pathogens from 12 Chinese hospitals illustrates several agents active against GP pathogens, but more serious R problems were noted among Enterobacteriaceae, PSA, and ACB. Combination treatment for the latter multidrug-R strains appears necessary, guided by local antibiograms and national surveillance results applying reference methods.