Application of Bayes' Theorem in Valuating Depression Tests Performance

Delirium diagnosis without a gold standard: Evaluating diagnostic accuracy of combined delirium assessment tools

Background

Fluctuating course of delirium and complexities of ICU care mean delirium symptoms are hard to identify or commonly confused with other disorders. Delirium is difficult to diagnose, and clinicians and researchers may combine assessments from multiple tools. We evaluated diagnostic accuracy of different combinations of delirium assessments performed in each enrolled patient.

Methods

Data were obtained from a previously conducted cross-sectional study. Eligible adult patients who remained admitted to ICU for >24 hours with at least one family member present were consecutively enrolled as patient-family dyads. Clinical delirium assessments (Intensive Care Delirium Screening Checklist [ICSDC] and Confusion Assessment Method-ICU [CAM-ICU]) were completed twice daily by bedside nurse or trained research assistant, respectively. Family delirium assessments (Family Confusion Assessment Method and Sour Seven) were completed once daily by family members. We pooled all delirium assessment tools in a single two-class latent model and pairwise (i.e., combined, clinical or family assessments) Bayesian analyses.

Results

Seventy-three patient-family dyads were included. Among clinical delirium assessments, the ICDSC had lower sensitivity (0.72; 95% Bayesian Credible [BC] interval 0.54–0.92) and higher specificity (0.90; 95%BC, 0.82–0.97) using Bayesian analyses compared to pooled latent class analysis and CAM-ICU had higher sensitivity (0.90; 95%BC, 0.70–1.00) and higher specificity (0.94; 95%BC, 0.80–1.00). Among family delirium assessments, the Family Confusion Assessment Method had higher sensitivity (0.83; 95%BC, 0.71–0.92) and higher specificity (0.93; 95%BC, 0.84–0.98) using Bayesian analyses compared to pooled latent class analysis and the Sour Seven had higher specificity (0.85; 95%BC, 0.67–0.99) but lower sensitivity (0.64; 95%BC 0.47–0.82).

Conclusions

Results from delirium assessment tools are often combined owing to imperfect reference standards for delirium measurement. Pairwise Bayesian analyses that explicitly accounted for each tool’s (performed within same patient) prior sensitivity and specificity indicate that two combined clinical or two combined family delirium assessment tools have fair diagnostic accuracy.

Tailored Screening for Late-Life Depression: A Short Version of the Teate Depression Inventory (TDI-E)

A number of assessment instruments have been developed as efficacy measures of geriatric depression in clinical trials but most showed several weaknesses, such as time-consuming administration, development and validation in younger populations, and lack of discrimination between anxiety and depression. Among the extant self-report measures of depression, the 21-item Teate Depression Inventory (TDI; Balsamo and Saggino, 2013), developed via Rasch analysis, showed a satisfactory level of diagnostic accuracy, and allowed the reduction of false positives in test scoring in adult population. The present study explored the potential improvement in the psychometric performance of the TDI in the elderly by item refinement through Rasch analysis in a sample of 836 elderly people (49.5% males; mean age = 73.28; SD = 6.56). A resulting shorter version was composed of the best-fitting and discriminative nine items from the full form. The Teate Depression Inventory (TDI-E) (E for elderly) presented good internal construct validity, with unidimensional structure, local dependency, good reliability (person separation index and Cronbach’s alpha), and no signs of differential item functioning or measurement bias due to gender and age (65 vs. 75+ years). Cut-off points and normative data provided could enhance the clinical usefulness of the TDI-E, which seems to be a promising valid and reliable tool for the screening of geriatric depression, with less risk of finding false positives due to overlapping of depression in elderly with other comorbid conditions.