Evaluating fatigue in patients recovering from COVID-19: validation of the fatigue severity scale and single item screening questions 2022 Nacul et al

Abstract
Background
Fatigue is a common symptom in hospitalized and non-hospitalized patients recovering from COVID-19, but no fatigue measurement scales or questions have been validated in these populations. The objective of this study was to perform validity assessments of the fatigue severity scale (FSS) and two single-item screening questions (SISQs) for fatigue in patients recovering from COVID-19.

Methods
We examined patients ≥ 28 days after their first SARS-CoV-2 infection who were hospitalized for their acute illness, as well as non-hospitalized patients referred for persistent symptoms. Patients completed questionnaires through 1 of 4 Post COVID-19 Recovery Clinics in British Columbia, Canada. Construct validity was assessed by comparing FSS scores to quality of life and depression measures. Two SISQs were evaluated based on the ability to classify fatigue (FSS score ≥ 4).

Results
Questionnaires were returned in 548 hospitalized and 546 non-hospitalized patients, with scores computable in 96.4% and 98.2% of patients respectively. Cronbach’s alpha was 0.96 in both groups. The mean ± SD FSS score was 4.4 ± 1.8 in the hospitalized and 5.2 ± 1.6 in the non-hospitalized group, with 62.5% hospitalized and 78.9% non-hospitalized patients classified as fatigued. Ceiling effects were 7.6% in the hospitalized and 16.1% in non-hospitalized patients. FSS scores negatively correlated with EQ-5D scores in both groups (Spearman’s rho − 0.6 in both hospitalized and non-hospitalized; p < 0.001) and were higher among patients with a positive PHQ-2 depression screen (5.4 vs. 4.0 in hospitalized and 5.9 vs. 4.9 in non-hospitalized; p < 0.001). An SISQ asking whether there was “fatigue present” had a sensitivity of 70.6% in hospitalized and 83.2% in non-hospitalized patients; the “always feeling tired” SISQ, had a sensitivity of 70.5% and 89.6% respectively.

Conclusions
Fatigue was common and severe in patients referred for post COVID-19 assessment. Overall, the FSS is suitable for measuring fatigue in these patients, as there was excellent data quality, strong internal consistency, and construct validity. However, ceiling effects may be a limitation in the non-hospitalized group. SISQs had good sensitivity for identifying clinically relevant fatigue in non-hospitalized patients but only moderate sensitivity in the hospitalized group, indicating that there were more false negatives.

https://hqlo.biomedcentral.com/articles/10.1186/s12955-022-02082-x

 

The more upstream an error is, the more impact the error will have. I don't understand how people convinced themselves that this is a process of validation, but it is clearly the upstream error that needs to be addressed: invalid thinking. Those are different concepts, there is no overlap in validity here. WTH?

Might as well calibrate the temperature-feel (cold, warm, hot, not degrees) of your boiler based on average water dowsing ratings in the area and how they correlates to how many TV channels can be received using a bunny-ears antenna.

Or screw it just call ghost hunters, clearly that's the future the medical profession wants more than anything. You can't do science with garbage instruments. Doesn't matter what the intent here, the process is broken.