This study describes the prototype testing and clinical validation of the Fit-Frailty App, a fully guided, interactive mobile health (mHealth) app to assess frailty and sarcopenia. This multi-dimensional tool is freely available on the App Store and considers medical history, physical performance, cognition, nutrition, daily function and psychosocial domains. To guide management, a total frailty score and clinical summary of underlying "risk flags" are provided. Our objectives were to examine usability, feasibility, criterion and construct validity.

Cross-sectional

Outpatient geriatric medicine clinic

Community-dwelling older adults, age 65 years or older

The primary outcome of the clinical validation study was criterion validity. A research nurse administered the Fit-Frailty App during a routine clinic appointment. Clinicians simultaneously completed a paper-based frailty index (FI) tool with similar items from a comprehensive geriatric assessment (FI-CGA). Total scores for both assessments were computed using the cumulative deficits frailty index scoring method. Intraclass and Pearson correlation coefficients and 95% CIs were calculated to examine criterion validity. Secondary outcomes were construct validity, feasibility (eg, completion rates, safety occurrences, resources) and usability (eg, ratings on ease of use, time to complete the app).

In the clinical validation study (n=75, mean age 79.2, SD=7.0, 53% female), the mean total Fit-Frailty App score was 0.33 (SD=0.13) with 73% of our sample considered frail or severely frail. The app presented comparable results to FI-CGA (moderate to good validity; ICC=0.65, 95%CI=0.50–0.76) with a strong association between the measures (r=0.74, 95%CI=0.62–0.83). In our prototype and clinical cohorts, the app had a 100% completion rate with no safety occurrences and had high usability ratings.

The Fit-Frailty App is a feasible and valid tool that can be used in research and clinical settings to comprehensively assess frailty and sarcopenia by non-geriatricians and could assist with developing targeted interventions.

To assess the validity of the International Classification of Diseases, 10th Revision (ICD-10) healthcare database diagnosis codes for lithium toxicity at hospital admission in Ontario, Canada.

Population-based retrospective validation study.

A total of 152 hospitals linked to a provincial laboratory database in Ontario, Canada, from 2007 to 2023.

Patients 50 years of age or older taking lithium with hospital-based serum lithium laboratory measurements during admission to the hospital (n=2804).

Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) comparing an ICD-10 diagnostic coding algorithm for lithium toxicity to a serum lithium concentration of 1.5 mmol/L or more. The codes used in the algorithm were T568, T435, Y495, X41 and X49. Serum lithium values and changes in the concentration of serum lithium from baseline levels in patients with and without a diagnosis code for lithium toxicity (code-positive and code-negative, respectively).

The sensitivity of the ICD-10 coding algorithm for identifying a serum lithium level≥1.5 mmol/L was 84% (95% CI 81% to 87%). The specificity and the NPV were over 88%, and the PPV was 63% (95% CI 60% to 66%). The median (IQR) serum lithium measurement in code-positive patients was 1.7 (1.2 to 2.2) mmol/L, and it was 0.6 (0.4 to 0.9) mmol/L in code-negative patients. The median (IQR) increase in serum lithium concentration compared with the most recent prehospital baseline values was 0.7 (0.2 to 1.3) mmol/L in code-positive patients and 0.0 (–0.2 to 0.2) mmol/L in code-negative patients.

In Ontario, the sensitivity of the ICD-10 coding algorithms was moderate for identifying a serum lithium level≥1.5 mmol/L at hospital admission. The presence or absence of the ICD-10 codes for lithium toxicity at hospital admission successfully differentiated two groups of patients with distinct serum lithium measurements.