UNASSIGNED: Major depressive disorder (MDD) is a leading cause of disability worldwide. An accurate assessment of depressive symptomology is crucial for clinical management and research. This study assessed the convergent validity, reliability, and total scale score interconversion across the 9-item Patient Health Questionnaire (PHQ-9) self-report, the 16-item Quick Inventory of Depressive Symptomatology-clinician report (QIDS-C) (two widely used clinical ratings) and the 5-item Very Brief Quick Inventory of Depressive Symptoms-clinician report (VQIDS-C), which evaluate the core features of MDD.
UNASSIGNED: This study leveraged electronic health record (EHR)-derived, de-identified data from the NeuroBlu Database (Version 23R1), a longitudinal behavioural health real-world platform. Classical Test Theory (CTT) and Item Response Theory (IRT) analyses were used to evaluate the reliability, validity of, and conversions between the scales. The Test Information Function (TIF) was calculated for each scale, with greater test information reflecting higher precision and reliability in measuring depressive symptomology. IRT was also used to generate conversion tables so that total scores on each scale could be compared to the other.
UNASSIGNED: The study sample (n = 2,156) had an average age of 36.4 years (standard deviation [SD] = 13.0) and 59.7% were female. The mean depression scores for the PHQ-9, QIDS-C, and VQIDS-C were 12.9 (SD = 6.6), 12.0 (SD = 4.9), and 6.18 (SD = 3.2), respectively. The Cronbach\'s alpha coefficients for PHQ-9, QIDS-C, and VQIDS-C were 0.9, 0.8, and 0.7, respectively, suggesting acceptable internal consistency. PHQ-9 (TIF = 30.3) demonstrated the best assessment of depressive symptomology, followed by QIDS-C (TIF = 25.8) and VQIDS-C (TIF = 17.7).
UNASSIGNED: Overall, PHQ-9, QIDS-C, and VQIDS-C appear to be reliable and convertible measures of MDD symptomology within a US-based adult population in a real-world clinical setting.

BACKGROUND: Trauma registries and their quality improvement programs only collect data from the acute hospital admission, and no additional information is captured once the patient is discharged. This lack of long-term data limits these programs\' ability to affect change. The goal of this study was to create a longitudinal patient record by linking trauma registry data with third party payer claims data to allow the tracking of these patients after discharge.
METHODS: Trauma quality collaborative data (2018-2019) was utilized. Inclusion criteria were patients age ≥18, ISS ≥5 and a length of stay ≥1 d. In-hospital deaths were excluded. A deterministic match was performed with insurance claims records based on the hospital name, date of birth, sex, and dates of service (±1 d). The effect of payer type, ZIP code, International Classification of Diseases, Tenth Revision, Clinical Modification diagnosis specificity and exact dates of service on the match rate was analyzed.
RESULTS: The overall match rate between these two patient record sources was 27.5%. There was a significantly higher match rate (42.8% versus 6.1%, P < 0.001) for patients with a payer that was contained in the insurance collaborative. In a subanalysis, exact dates of service did not substantially affect this match rate; however, specific International Classification of Diseases, Tenth Revision, Clinical Modification codes (i.e., all 7 characters) reduced this rate by almost half.
CONCLUSIONS: We demonstrated the successful linkage of patient records in a trauma registry with their insurance claims. This will allow us to the collect longitudinal information so that we can follow these patients\' long-term outcomes and subsequently improve their care.

There is a clear need to harmonize outcome measurement. Some authors propose to express scores as T scores to facilitate interpretation of PROM results in clinical practice. While this is a step in the right direction, there are important limitations to the acceptance of the T score metric as a common metric when T scores are based on raw sum scores of ordinal items: Such T scores of different instruments are not exactly comparable because they are not interval scaled; T scores of different measures are only on the same scale if exactly the same reference group is used; and the T sore metric cannot be maintained because it is reference population-dependent and needs to be updated regularly. These limitations can be overcome by using an item response theory (IRT)-based metric. Items from different measures can be placed on the same IRT metric to make scores comparable on an interval scale. The PROMIS initiative used IRT to develop item banks for measuring various health outcomes. Other PROMs have been linked to the PROMIS metric. Although PROMIS uses a T-score metric for practical reasons, the underlying PROMIS metric is actually an IRT metric. An IRT approach also enables further development of an item bank while preserving the underlying metric. Therefore, IRT-based metrics should be considered as common metrics for the future.

Research on health anxiety has bloomed in recent years, but summaries of the literature are complicated by the use of dissimilar self-report questionnaires. Furthermore, these instruments have rarely been administered in parallel, and especially not in clinical samples. In this study, we aimed to investigate the relationship between five widespread health anxiety measures, and to draft guidelines for the conversion of different sum scores.
Clinical trial participants with principal pathological health anxiety (n = 335) and a sample of healthy volunteers (n = 88) completed the 14-item Whiteley Index (WI-14), the Illness Attitude Scale (IAS), and the 14-, 18-, and 64-item Health Anxiety Inventory (the HAI-64, HAI-18, and HAI-14). Cross-sectional data from all participants were pooled (N = 423) and we conducted a joint factor analysis and approximate equipercentile linking of the WI-14, IAS, HAI-64, HAI-18, and HAI-14.
Inter-scale correlations were high (rs ≥ 0.90 and ≥ 0.88 in adjusted analyses), and the scree plot of the joint factor analysis spoke for a unifactorial solution where 89/105 items (85%) had loadings ≥ 0.40. Most items at the core of this broad trait health anxiety factor pertained to the worry about health, the fear of having or developing a serious disease, and to some extent bodily preoccupation. We present a cross-walk table of observed equipercentile linked sum scores.
This study speaks clearly in favor of the WI-14, IAS, HAI-64, HAI-18, and HAI-14 all tapping into the same trait health anxiety construct, the core of which appears to concern the worry about health, the fear of having or developing a serious disease, and to some extent bodily preoccupation. Based on recently reported cut-offs for the HAI-14, a reasonable cutoff for pathological health anxiety in a psychiatric setting probably lies around 7-8 on the WI-14, 52-53 on the IAS, 82-83 on the HAI-64, and 26-27 on the HAI-18.
ClinicalTrials.gov NCT01966705, NCT02314065.

This paper provides experimental evidence on the economic determinants of intermediation networks by considering two pricing rules-respectively, criticality and betweenness-and three group sizes of subjects-10, 50, and 100 subjects. We find that when brokerage benefits accrue only to traders who lie on all paths of intermediation, stable networks involve interconnected cycles, and trading path lengths grow while linking and payoff inequality remain modest as the number of traders grows. By contrast, when brokerage benefits are equally distributed among traders on the shortest paths, stable networks contain a few hubs that provide the vast majority of links, and trading path lengths remain unchanged while linking and payoff inequality explode as the number of traders grows.

Several validated scales have been developed to measure frailty, yet the direct relationship between these measures and their scores remains unknown. To bridge this gap, we created a crosswalk of the most commonly used frailty scales.
We used data from 7070 community-dwelling older adults who participated in National Health and Aging Trends Study (NHATS) Round 5 to construct a crosswalk among frailty scales. We operationalized the Study of Osteoporotic Fracture Index (SOF), FRAIL Scale, Frailty Phenotype, Clinical Frailty Scale (CFS), Vulnerable Elder Survey-13 (VES-13), Tilburg Frailty Indictor (TFI), Groningen Frailty Indicator (GFI), Edmonton Frailty Scale (EFS), and 40-item Frailty Index (FI). A crosswalk between FI and the frailty scales was created using the equipercentile linking method, a statistical procedure that produces equivalent scoring between scales according to percentile distributions. To demonstrate its validity, we determined the 4-year mortality risk across all scales for low-risk (equivalent to FI <0.20), moderate-risk (FI 0.20 to <0.40), and high-risk (FI ≥0.40) categories.
Using NHATS, the feasibility of calculating frailty scores was at least 90% for all nine scales, with the FI having the highest number of calculable scores. Participants considered frail on FI (cutpoint of 0.25) corresponded to the following scores on each frailty measure: SOF 1.3, FRAIL 1.7, Phenotype 1.7, CFS 5.3, VES-13 5.5, TFI 4.4, GFI 4.8, and EFS 5.8. Conversely, individuals considered frail according to the cutpoint of each frailty measure corresponded to the following FI scores: 0.37 for SOF, 0.40 for FRAIL, 0.42 for Phenotype, 0.21 for CFS, 0.16 for VES-13, 0.28 for TFI, 0.21 for GFI, and 0.37 for EFS. Across frailty scales, the 4-year mortality risks between the same categories were similar in magnitude.
Our results provide clinicians and researchers with a useful tool to directly compare and interpret frailty scores across scales.

In a patient who previously developed left bundle branch block after transcatheter aortic valve replacement, intermittent narrow QRS complexes were recorded on ambulatory electrocardiography monitoring. The peculiar distribution of wide and narrow QRS complexes suggested the presence of a window of supernormality in the refractory period of a branch block that on other occasions exhibited the Wenckebach phenomenon. (Level of Difficulty: Intermediate.).

Test equating is a statistical procedure to make scores from different test forms comparable and interchangeable. Focusing on an IRT approach, this paper proposes a novel method that simultaneously links the item parameter estimates of a large number of test forms. Our proposal differentiates itself from the current state of the art by using likelihood-based methods and by taking into account the heteroskedasticity and the correlation of the item parameter estimates of each form. Simulation studies show that our proposal yields equating coefficient estimates which are more efficient than what is currently available in the literature.

To investigate whether a multi-item performance outcome measure, the physical performance test (PPT), can be calibrated to a common scale with patient-reported outcome measures, using the Patient-Reported Outcomes Measurement Information System (PROMIS) physical function (PF) metric.
We analyzed baseline data (N = 1,113) from the CONVINCE study, an international trial in end-stage kidney disease patients comparing high-dose hemodiafiltration with high-flux hemodialysis. Assumptions of item response theory (IRT) modelling were investigated for the combined set of the nine-item PPT and a four-item PROMIS PF short form (PROMIS-PF4a). We applied unidimensional IRT linking for calibrating the PPT to the PROMIS PF metric.
Although some evidence for multidimensionality was found, classical test statistics (Cronbach\'s Alpha = 0.93), Mokken (Loevinger\'s H = 0.50), and bifactor analysis (explained common variance = 0.65) indicated that PPT and PROMIS-PF4a items can be used to assess a common PF construct. On the group level, the agreement between PROMIS-PF4a and linked PPT scores was stable across several subsamples. On the individual level, scores differed considerably.
We found preliminary evidence that the PPT can be linked to the PROMIS PF metric in hemodialysis patients, enabling group comparisons across patient-reported outcome and performance outcome measures. Alternative linking methods should be applied in future studies using a more comprehensive PROMIS PF item set.

Patient-reported physical function (PF) is a key endpoint in cancer clinical trials. Using complex statistical methods, common metrics have been developed to compare scores from different patient-reported outcome (PRO) measures, but such methods do not account for possible differences in questionnaire content. Therefore, the aim of our study was a content comparison of frequently used PRO measures for PF in cancer patients.
Relying on the framework of the International Classification of Functioning, Disability and Health (ICF) we categorized the item content of the physical domains of the following measures: EORTC CAT Core, EORTC QLQ-C30, SF-36, PROMIS Cancer Item Bank for Physical Function, PROMIS Short Form for Physical Function 20a, and the FACT-G. Item content was linked to ICF categories by two independent reviewers.
The 118 items investigated were assigned to 3 components (\'d - Activities and Participation\', \'b - Body Functions\', and \'e - Environmental Factors\') and 11 first-level ICF categories. All PF items of the EORTC measures but one were assigned to the first-level ICF categories \'d4 - Mobility\' and \'d5 - Self-care\', all within the component \'d - Activities and Participation\'. The SF-36 additionally included item content related to \'d9 - Community, social and civic life\' and the PROMIS Short Form for Physical Function 20a also included content related to \'d6 - domestic life\'. The PROMIS Cancer Item Bank (v1.1) covered, in addition, two first-level categories within the component \'b - Body Functions\'. The FACT-G Physical Well-being scale was found to be the most diverse scale with item content partly not covered by the ICF framework.
Our results provide information about conceptual differences between common PRO measures for the assessment of PF in cancer patients. Our results complement quantitative information on psychometric characteristics of these measures and provide a better understanding of the possibilities of establishing common metrics.