Percentage Of Reclassification Research Articles

#2120 Impact on CKD classification and comorbidities using GFR estimated by European Kidney Function Consortium equation in kidney transplant recipients

Abstract Background and Aims In 2020, European Kidney Function Consortium (EKFC) proposed a new equation that estimates glomerular filtration rate (GFR) in European population. Few studies have compared EKFC with CKDEPI, particularly in kidney transplant (KT) recipients. Chronic Kidney Disease (CKD) classification by KDIGO is used not only by nephrologists who evaluate more parameters of kidney function, but also by every other specialist who are going to be guided mainly by this stage. Our objective is to compare EKFC equation and CKDEPI in classifying CKD in KT patients and its relationship with associated comorbidities. Method We conduct a retrospective observational study including all KT performed at our centre from 1993 to 2022 with survival greater than one year. We collect creatinine, haemoglobin (Hb), phosphorus (P−), potassium (K+), and bicarbonate (Bic) values at three months and one-year post-transplant. We define anaemia as Hb < 11 g/dl, hyperphosphataemia as serum P− > 4.5 mg/dl, hyperkalaemia as serum K+ > 5 mEq/ml, and acidosis as Bic < 22 mEq/L. We calculate estimated GFR (eGFR) using CKDEPI and EKFC equations, classify CKD stage according to KDIGO, and compare both results in terms of correlation and differences. We use Kappa Coefficient and Chi-Square by contingency tables, and ROC curves with homogeneity test for prediction of these comorbidities. We use SPSS and MedCalc as statistics programs. Results We include 968 KT, with median age at the time of transplant 52.75 year [41.25-61.27]. 294 KT (30.4%) are in women. Comorbidity frequencies are depicted in Table 1. ROC analysis shows no significant differences in predicting acidosis at one year, hyperphosphataemia at any time, hyperkalaemia at 3rd month, anaemia at any time, and composite event at any time. We find significant differences in favour to CKDEPI for acidosis at 3rd month (ΔAUC 0.00575 95% CI [0.00182-0.00969]; p = 0.0042) and for hyperkalaemia at one year (ΔAUC = 0.00853 [0.00161-0.0154]; p = 0.0157). Through contingency tables we compare classification into stages, finding very good agreement based on the Kappa coefficient (κ) but significant differences by Chi-Square. With κ = 0.905, EKFC reclassifies 70 patients, 7.23% overall, but not significantly down nor upstaging (31 vs 39). It reclassifies more men than women: 8.46% vs 4.42%. In 10-year age groups, the largest reclassification occurs in the 70-80 years group, a 17.07% with κ = 0.774, all cases upstaged. At one-year eGFR, contingency tables also show a very good agreement based on κ but significant differences by Chi-Square. EKFC reclassifies 83 KT (κ = 0.887), 8.57% overall. It reclassifies 7.48% women and 9.05% men. In 10-year age groups, the largest reclassification occurs in 20-30 years group with 17.24% (κ = 0.767) and 14.81% in 70-80 years (κ = 0.796). All patients in these groups were upstaged. We resume graphically the reclassification of the groups in Fig. 1, observing how EKFC upstages CKD (worsen CKD stage) in high eGFR stages, and downstages CKD in low eGFR stages. Conclusion Estimation of GFR in KT recipients using the new EKFC equation yields similar results to CKDEPI, showing very good agreement for CKD classification although there is a non-negligible percentage of reclassification, which may be clinically relevant in terms of treatment indications and diagnostic tests. It is to a worse CKD stage in high eGFR and to a better stage in low eGFR, and when EKFC reclassification percentage is greater—in the extreme ages of our cohort—it is always by upstaging. Except for minimal differences which we consider clinically inconsequential, we find no significant differences between both equations in discriminating presence of hyperphosphatemia, hyperkalaemia, anaemia or acidosis.

Implications of methods for calculating the left ventricular outflow tract area in aortic stenosis severity grading

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): - Spanish Ministry of Economy and Competitiveness through the Carlos III Institute of Health-Fondo de Investigación Sanitaria. - Post-residency research contract. Medical Research Institute Hospital La Fe (IIS La Fe), Valencia, Spain. Introduction Aortic valve area (AVA) calculation by continuity equation is a fundamental aspect to estimate aortic stenosis (AS) severity. The estimation of the left ventricular outflow tract (LVOT) area is a source of technical variability in the calculation of AVA that can lead to errors in severity grading. Formulas for calculating LVOT diameter (LVOTd) based on body surface area (BSA) and patient height have been proposed, but their impact on reclassifying patients based on severity has not been described. Purpose To evaluate the differences in AS grading according to the LVOT area used in the calculation of the AVA. Methods We retrospectively analyzed (2019–2022) 1722 echocardiograms with a diagnosis of AS and with the following variables reported: AVA calculated using the continuity equation, height and weight of the patient. Predicted LVOTd by BSA was calculated by the formula: (5.7*BSA + 12). Predicted LVOTd by height was calculated as: (5.78 * height + 12.1). Results LVOT area and AVA from predicted LVOTd based on BSA and height showed slightly higher values. The AVA based on the LVOTd predicted by BSA was associated with a lower prevalence of severe AS, as well as a lower prevalence of discordant cases (mean gradient <40 mmHg and AVA <1 cm2) (Table). The AVA based on both methods of predicted LVOTd led to a reclassification from severe (by the standard method) to non-severe in a significant percentage of patients (13.6% for the BSA-predicted method, and 8.7% for the height-predicted method). For the AVA predicted by BSA, the "downgrade" of AS severity was more frequent (23.3%) in patients in the quartile with the highest BMI (>30 kg/m2), while the degree of obesity did not affect the method predicted by height. Conclusion Despite suppressing the potential errors derived from the LVOTd measurement, the AVA based on predicted LVOTd methods using BSA or height lead to a significant percentage of reclassification in terms of severity and prevalence of discordant severe AS due to low gradient. In obese patients, the method predicted by BSA is highly discordant and the method predicted by the patient's height is preferable.

Population structure and dynamics of the Atlantic mackerel (Scomber scombrus) in the North Atlantic inferred from otolith chemical and shape signatures

The Atlantic mackerel, Scomber scombrus, is an economically important and widely distributed fish species in the North Atlantic, currently considered to comprise two stocks: the North-West Atlantic (NWA) and the North-East Atlantic (NEA). Each stock is composed of different spawning components which involve temporal and spatial movements driven by the environment. Thus, resolving the species population structure and dynamics presents a challenge to scientists. In this study, the stock structure of S. scombrus was evaluated using otolith shape and chemical signatures. One hundred and eighty individuals of the same cohort (age 3), caught between January and February of 2018 from six key locations in the North Atlantic, were used. Individuals were collected from the two spawning components in the NWA stock, the Canadian Northern component (NWA-N) and the US Southern component (NWA-S); and from the three spawning components in the NEA stock, the North Sea (NEA-NS), the Western (NEA-W) and the Southern components (NEA-S), plus, an overlapping area of these last two components, the Bay of Biscay (NEA-BB). Combined otolith signatures fully discriminated the NEA and NWA stocks (100% of reclassification success, indicates distinct population-units) and discriminated the components within each stock with high reclassification percentages (100% and 68% for the overall reclassification of the NWA and NEA components, respectively). These data suggest that NWA stock should be regard as two distinct population-units for fisheries management purposes, confirms the complex metapopulational structure of the NEA stock, and calls for the need of continuous evaluation of these complex stocks in order to achieve a sustainable exploitation.

Direct Planimetry of Left Ventricular Outflow Tract Area by Simultaneous Biplane Imaging: Challenging the Need for a Circular Assumption of the Left Ventricular Outflow Tract in the Assessment of Aortic Stenosis

Evaluation of aortic stenosis (AS) requires calculation of aortic valve area (AVA), which relies on the assumption of a circular-shaped left ventricular outflow tract (LVOT). However, the LVOT is often elliptical, and the circular assumption underestimates the true LVOT area (LVOTA). Biplane imaging using transthoracic echocardiography allows direct planimetry of LVOTA. The aim of this study was to assess the feasibility of obtaining LVOTA using this technique and its impact on the discordance between AVA and gradient criteria in AS grading. We prospectively studied 134 patients (median age, 80years; interquartile range, 73-87years; 39% women) with AS, including 82 (61%) with severe AS and 52 (39%) with mild or moderate AS. LVOTA was traced using direct planimetry (LVOTAbiplane) and compared with LVOTA calculated using the circular assumption (LVOTAcirc). In a subset of patients who underwent cardiac computed tomography, direct planimetry of LVOTA was used as a reference standard. LVOTAbiplane was significantly larger than LVOTAcirc (4.20cm2 [interquartile range, 3.66-4.90cm2] vs 3.73cm2 [interquartile range, 3.14-4.15cm2], P<.001). Among 30 patients who underwent cardiac computed tomography, LVOTAbiplane had better agreement with LVOTA by direct planimetry than LVOTAcirc (mean bias, -0.45±0.63 vs -1.02±0.63cm2; P<.0001). Of 82 patients with severe AS (AVA≤1cm2 using LVOTAcirc), 40 (49%) had discordant mean gradient (<40mm Hg). By using LVOTAbiplane, patients with discordant AVA and mean gradient decreased from 49% to 27% (P=.004), and 29% of patients with severe AS were reclassified with moderate AS, with the highest percentage of reclassification in the group with low-gradient AS with preserved left ventricular ejection fraction. Direct planimetry using biplane imaging avoids the inherent underestimation of LVOTA using the circular assumption. LVOTA obtained by biplane planimetry can lead to better concordance between AVA and mean gradient and classification of AS severity.

Age and Assay Related Changes of Laboratory Thyroid Function Tests in the Reference Female Population.

SummaryBackgroundLaboratory thyroid function tests play a central role in the diagnosis of thyroid disorders. The aim of our cross-sectional study was to determine reference values for thyroid tests in a rigorously selected group of Montenegrin females, investigate the impact of possible age-related changes and the influence of the interassay bias between three frequently used immunoassays.MethodsFemale subjects were randomly selected, aged between 20 and 69 and 946 of them met the selection criteria. TSH, fT3, fT4, thyroid peroxidase and thyroglobulin antibodies were measured. Eighty samples were further analyzed on two other immunochemistry platforms.ResultsMedian TSH progressively increased with age, there was no difference in fT3, while fT4 was significantly higher in the two oldest groups compared to the others. When using the age-related 97.5 percentile of TSH the percentage of reclassification was highest in the 20–29 years of age group (5.2%, p<0.05). In the oldest band, 7.7% had TSH values above cohort-specific and below the age-related upper reference limit. Bland-Altman bias plots revealed the highest interassay absolute mean difference between compared TSH assays of 24.5% and for fT4 assays of 13.8%.ConclusionsThe correlation coefficients between fT3 assays from different manufacturers were low. Serum TSH and fT4 concentrations increased with age and the implementation of age-specific TSH reference intervals would be of interest. The bias between the three commercial immunoassays indicated that the standardization of thyroid function tests is a task of great importance.

Integrated landmark and outline-based morphometric methods efficiently distinguish species of Euglossa (Hymenoptera, Apidae, Euglossini)

Morphometric methods permit identification of insect species and are an aid for taxonomy. Quantitative wing traits were used to identify male euglossine bees. Landmark- and outline-based methods have been primarily used independently. Here, we combine the two methods using five Euglossa. Landmark-based methods correctly classified 84% and outline-based 77%, but an integrated analysis correctly classified 91% of samples. Some species presented significantly high reclassification percentages when only wing cell contour was considered, and correct identification of specimens with damaged wings was also obtained using this methodology.

Burden of atherosclerosis improves the prediction of coronary heart disease but not cerebrovascular events: The Rotterdam Study

Since atherosclerosis is a systemic process, risk prediction would benefit from targeting multiple components of cardiovascular disease simultaneously. To this end, it is useful to examine the predictive value of non-invasive measures of atherosclerosis in various vascular beds for both coronary heart disease (CHD) and cerebrovascular disease. Between September 2003 and February 2006, 2153 asymptomatic participants (69.6±6.6 years) from the Rotterdam Study underwent a multi-detector computed tomography scan. During a median follow-up of 3.5 years, 58 CHD events (myocardial infarction and CHD death) and 52 cerebrovascular events (TIA and stroke) occurred. Participants were classified into low (<5%), intermediate (5-10%), and high (>10%) 5-year risk categories based on a refitted Framingham risk model. The model was extended by coronary, aortic arch, or carotid calcium and reclassification percentages were calculated. For the outcome CHD, the C-statistic improved from 0.693 for the Framingham refitted model to 0.743, 0.740, and 0.749 by addition of coronary, aortic arch, and carotid calcium, respectively. Reclassification was most substantial in the intermediate risk group where addition of coronary calcium reclassified 56% of persons [net reclassification improvement (NRI): 15%; P<0.01)]. Adding aortic arch calcium led to a reclassification of 32% of persons (NRI: 8%; P=0.01) and adding carotid calcium reclassified 51% (NRI: 9%; P=0.02). In contrast, calcification in any of the three vascular beds did not improve cerebrovascular risk prediction. Coronary, aortic arch, and carotid artery calcification significantly improved risk prediction of CHD but not of cerebrovascular events.

Problems With Risk Reclassification Methods for Evaluating Prediction Models

For comparing the performance of a baseline risk prediction model with one that includes an additional predictor, a risk reclassification analysis strategy has been proposed. The first step is to cross-classify risks calculated according to the 2 models for all study subjects. Summary measures including the percentage of reclassification and the percentage of correct reclassification are calculated, along with 2 reclassification calibration statistics. The author shows that interpretations of the proposed summary measures and P values are problematic. The author's recommendation is to display the reclassification table, because it shows interesting information, but to use alternative methods for summarizing and comparing model performance. The Net Reclassification Index has been suggested as one alternative method. The author argues for reporting components of the Net Reclassification Index because they are more clinically relevant than is the single numerical summary measure.

Coronary Calcium Score Improves Classification of Coronary Heart Disease Risk in the Elderly: The Rotterdam Study

The purpose of this study was to examine the effect of coronary artery calcium (CAC) on the classification of 10-year hard coronary heart disease (CHD) risk and to empirically derive cut-off values of the calcium score for a general population of elderly patients.Although CAC scoring has been found to improve CHD risk prediction, there are limited data on its impact in clinical practice.The study comprised 2,028 asymptomatic participants (age 69.6 ± 6.2 years) from the Rotterdam Study. During a median follow-up of 9.2 years, 135 hard coronary events occurred. Persons were classified into low (<10%), intermediate (10% to 20%), and high (>20%) 10-year coronary risk categories based on a Framingham refitted risk model. In a second step, the model was extended by CAC, and reclassification percentages were calculated. Cutoff values of CAC for persons in the intermediate-risk category were empirically derived based on 10-year hard CHD risk.Reclassification by means of CAC scoring was most substantial in persons initially classified as intermediate risk. In this group, 52% of men and women were reclassified, all into more accurate risk categories. CAC values above 615 or below 50 Agatston units were found appropriate to reclassify persons into high or low risk, respectively.In a general population of elderly patients at intermediate CHD risk, CAC scoring is a powerful method to reclassify persons into more appropriate risk categories. Empirically derived CAC cutoff values at which persons at intermediate risk reclassified to either high or low risk were 615 and 50 Agatston units, respectively.

Assessment of Improved Prediction Beyond Traditional Risk Factors

The moderate predictive performance of cardiovascular disease risk models necessitates more studies that investigate the incremental value of novel biomarkers. In recent years, many new biomarkers have been evaluated for their ability to improve prediction of cardiovascular disease beyond traditional risk factors, including C-reactive protein, coronary artery calcium, and single-nucleotide polymorphisms in the 9p21 region.1 The interest in novel biomarkers is propelled, in part, by emerging discoveries from genomewide association studies of genetic variants associated with risk for many common diseases.2 Nonetheless, family history, an “old” tool in clinical practice—crucial for the diagnosis and management of genetic disorders—has not been adequately explored for its value in risk assessment and prevention of common diseases.3 Positive family history is a strong risk factor for cardiovascular diseases,4,5 reflecting the consequences of genetic and nongenetic risk factors that are shared among relatives. From a practical perspective, family history is a strong determinant of disease that is relatively easy to assess. For this reason, family history is advocated as a useful tool for identifying individuals at increased risk of disease and for tailoring preventive interventions.4,6,7 However, the challenge is to show that this knowledge has clinical utility for improving health.8 Article see p 97 In this issue of Circulation: Cardiovascular Genetics , Scheuner et al9 report the incremental value of adding family history information to the General Cardiovascular Risk Profile to improve identification of individuals with advanced coronary artery calcification. The incremental value of family history in disease prediction is assessed in several questions10: 1. Does family history improve prediction beyond traditional risk factors? 2. Does improved prediction change treatment decisions or health recommendations? 3. Do these changes improve health outcomes or have other benefits? 4. Do the incremental benefits outweigh the extra costs? This evaluation is a stepwise …

Determining the effect of negative allometry (length/height relationship) on variation in otolith shape in lake trout (Salvelinus namaycush), using Fourier-series analysis

Geometric mean regression analysis between log(length) and log(height) of otoliths from lake trout (Salvelinus namaycush) from six lakes revealed that the growth of this structure was negatively allometric, indicating that otolith shape varies throughout the life of the fish. Otolith shape was quantified using harmonic amplitudes 2-10 (A2-A10) extracted from Fourier-series analyses. We found harmonic amplitudes 2 (A2) and 5 (A5) to be associated with the length/height relationship. Some recent studies have suggested that growth of fish otoliths affects their shape. Our results indicate that part of this otolith-growth effect could be due to an intrinsic change in shape associated with allometric nature of the length/height relationship. There were no differences in otolith shape between males and females. Otolith shape was also compared among the six populations. Major differences were observed between Lake Normand (Saint Maurice River watershed) and the five lakes in the Ottawa River watershed, suggesting that genotype could be an important factor affecting otolith shape. The percentage of reclassification using a discriminant function analysis was high (86%) for the Lake Normand population. Among populations from the Ottawa River watershed, differences in otolith shape were more subtle, with reclassification percentages ranging from 50 to 75%. However, one population in the Ottawa River watershed (Lake Duval), which was introduced as hatchery-raised individuals, differed slightly from the other populations from the same watershed, including Lake Trente et un Milles, from which it originated.

Reproducibility of electrocardiographic criteria for left ventricular hypertrophy in hypertensive patients in general practice.

Before changes in ECG voltage criteria can be accepted as evidence for changes in LVH, the variability of ECG measurements must be known. Here we report on the results of a study, on the variability of electrocardiographic single lead voltage parameters and (voltage) criteria for left ventricular hypertrophy in hypertensive patients in general practice. Two electrocardiograms were recorded, from 64 patients at an interval of 2 min, to measure the minute-to-minute variability. From 77 patients, two electrocardiograms were recorded at an interval of one week to measure the day-to-day variability. The coefficient of variation of voltage parameters for single leads ranged in the day-to-day group from 9.2% in R/I to 42% in T/V1, and the coefficient of variation for voltage combinations in this group ranged from 10.0% for the Sokolow-Lyon criteria to 13.7% for Gubner-Ungerleider criteria. The reclassification percentages in the day-to-day group ranged from 0% for Gubner-Ungerleider to 17% for Minnesota code criteria. A factor analysis showed that studies which use the Romhilt-Estes score, the Sokolow-Lyon or the Minnesota criteria to detect ECG-LVH are not comparable with studies which use the Cornell or Gubner-Ungerleider criteria.