A Simple Approach for Sample Size Calculation for Comparing Two Concordance Correlation Coefficients Estimated on the Same Subjects

Computer assisted interpretation of Tc-99m mercaptoacetyltriglycine diuretic scintigraphy enhances resident performance

OBJECTIVE

iRENEX is a software module that incorporates scintigraphic and clinical data to interpret 99m Tc- mercaptoacetyltriglycine (MAG3) diuretic studies and provide reasons for their conclusions. Our objectives were to compare iRENEX interpretations with those of expert physicians, use iRENEX to evaluate resident performance and determine if iRENEX could improve the diagnostic accuracy of experienced residents.

METHODS

Baseline and furosemide 99m Tc-MAG3 acquisitions of 50 patients with suspected obstruction (mean age ± SD, 58.7 ± 15.8 years, 60% female) were randomly selected from an archived database and independently interpreted by iRENEX, three expert readers and four nuclear medicine residents with one full year of residency. All raters had access to scintigraphic data and a text file containing clinical information and scored each kidney on a scale from +1.0 to -1.0. Scores ≥0.20 represented obstruction with higher scores indicating greater confidence. Scores +0.19 to -0.19 were indeterminate; scores ≤-0.20 indicated no obstruction. Several months later, residents reinterpreted the studies with access to iRENEX. Receiver operating characteristic (ROC) analysis and concordance correlation coefficient (CCC) quantified agreement.

RESULTS

The CCC among experts was higher than that among residents, 0.84, versus 0.39, respectively, P  < 0.001. When residents reinterpreted the studies with iRENEX, their CCC improved from 0.39 to 0.73, P  < 0.001. ROC analysis showed significant improvement in the ability of residents to distinguish between obstructed and non-obstructed kidneys using iRENEX ( P  = 0.036).

CONCLUSION

iRENEX interpretations were comparable to those of experts. iRENEX reduced interobserver variability among experienced residents and led to better agreement between resident and expert interpretations.

Statistical considerations for repeatability and reproducibility of quantitative imaging biomarkers

Quantitative imaging biomarkers (QIBs) are increasingly used in clinical studies. Because many QIBs are derived through multiple steps in image data acquisition and data analysis, QIB measurements can produce large variabilities, posing a significant challenge in translating QIBs into clinical trials, and ultimately, clinical practice. Both repeatability and reproducibility constitute the reliability of a QIB measurement. In this article, we review the statistical aspects of repeatability and reproducibility of QIB measurements by introducing methods and metrics for assessments of QIB repeatability and reproducibility and illustrating the impact of QIB measurement error on sample size and statistical power calculations, as well as predictive performance with a QIB as a predictive biomarker.

Comparison of Creatinine and Cystatin C to Estimate Renal Function in Geriatric and Frail Patients

The aim of this study was to compare estimated glomerular filtration rate (eGFR) with creatinine (eGFRcrea) and cystatin C (eGFRcys) in geriatric and frail patients. A retrospective, cross-sectional study was performed at a geriatric clinic in Stockholm (n = 95). The revised Lund−Malmö equation was used to calculate eGFRcrea and the Caucasian-Asian-Pediatric-Adult (CAPA) equation was used for eGFRcys. The absolute mean percentage difference between eGFRcrea and eGFRcys was used as a surrogate measure for accuracy in eGFR. Other outcome measures were consistency expressed in Lin’s concordance correlation coefficient and the proportion of consistent staging of renal failure. Subgroup analyses were performed with regard to frailty (according to Clinical Frailty Scale) and age. eGFRcys estimated lower GFR than eGFRcrea across the entire study population as well as in all subgroups (p < 0.05). Difference between the estimates increased with increasing frailty (r2 = 0.15, p < 0.01), but was not significantly affected by age (r2 = 0.004, p = 0.55). In conclusion, eGFRcys was significantly lower compared to eGFRcrea in geriatric and frail patients. Moreover, frailty had greater impact than age on the accuracy of eGFR. However, this study cannot determine if any of the estimates are preferable over the other in this patient group.

Validation of "(fr)AGILE": a quick tool to identify multidimensional frailty in the elderly

Background

Several tools have been proposed and validated to operationally define frailty. Recently, the Italian Frailty index (IFi), an Italian modified version of Frailty index, has been validated but its use in clinical practice is limited by long time of administration. Therefore, the aim of this study was to create and validate a quick version of the IFi (AGILE).

Methods

Validation study was performed by administering IFi and AGILE, after a Comprehensive Geriatric Assessment (CGA) in 401 subjects aged 65 or over (77 ± 7 years). AGILE was a 10-items tool created starting from the more predictive items of the four domains of frailty investigated by IFi (mental, physical, socioeconomic and nutritional). AGILE scores were stratified in light, moderate and severe frailty. At 24 months of follow-up, death, disability (taking into account an increase in ADL lost ≥1 from the baseline) and hospitalization were considered. Area under curve (AUC) was evaluated for both IFi and AGILE.

Results

Administration time was 9.5 ± 3.8 min for IFi administered after a CGA, and 2.4 ± 1.2 min for AGILE, regardless of CGA (p < 0.001). With increasing degree of frailty, prevalence of mortality increased progressively from 6.5 to 41.8% and from 9.0 to 33.3%, disability from 16.1 to 64.2% and from 22.1 to 59.8% and hospitalization from 17.2 to 58.7% and from 27.0 to 52.2% with AGILE and IFi, respectively (p = NS). Relative Risk for each unit of increase in AGILE was 56, 44 and 24% for mortality, disability and hospitalization, respectively and was lower for IFi (8, 7 and 4% for mortality, disability and hospitalization, respectively). The AUC was higher in AGILE vs. IFi for mortality (0.729 vs. 0.698), disability (0.715 vs. 0.682) and hospitalization (0.645 vs. 0.630).

Conclusions

Our study shows that AGILE is a rapid and effective tool for screening multidimensional frailty, able to predict mortality, disability and hospitalization, especially useful in care settings that require reliable assessment instruments with short administration time.

Measuring shared mental models in healthcare

Objective

To review common qualitative and quantitative methods of measuring shared mental models appropriate for use in the healthcare setting.

Background

Shared mental models are the overlap of individuals’ set of knowledge and/or assumptions that act as the basis for understanding and decision making between individuals. Within healthcare, shared mental models facilitate effective teamwork and theorized to influence clinical decision making and performance. With the current rapid growth and expansion of healthcare teams, it is critical that we understand and correctly use shared mental model measurement methods assess optimal team performance. Unfortunately, agreement on the proper measurement of shared mental models within healthcare remains diffuse.

Method

This paper presents methods appropriate to measure shared mental models within healthcare.

Results

Multiple shared mental model measurement methods are discussed with regard to their utility within this setting, ease of use, and difficulties in deploying within the healthcare operational environment. For rigorous analysis of shared mental models, it is recommended that a combination of qualitative and quantitative analyses be employed.

Conclusion

There are multitude of shared mental model measurement methods that can be used in the healthcare domain; although there is no perfect solution for every situation. Researchers can utilize this article to determine the best approach for their needs.