A biopsychosocial approach to persistent post-COVID-19 fatigue and cognitive complaints: ... 2024 Klinkhammer et al

[Andy]

Full title: A biopsychosocial approach to persistent post-COVID-19 fatigue and cognitive complaints: results of the prospective multicenter NeNeSCo study

Objective
To evaluate whether psychological and social factors complement biomedical factors in understanding post-COVID-19 fatigue and cognitive complaints. Additionally, to incorporate objective (neuro-cognitive) and subjective (patient-reported) variables in identifying factors related to post-COVID-19 fatigue and cognitive complaints.

Design
Prospective, multicentre cohort study.

Setting
Six Dutch hospitals.

Participants
205 initially hospitalized (March-June 2020), confirmed SARS-CoV-2 patients, aged ≥18 years, physically able to visit the hospital, without prior cognitive deficit, MRI contraindication, or severe neurological damage post-hospital discharge.

Interventions
Not applicable.

Main Outcome Measures
Nine months post-hospital discharge, a 3T MRI scan and cognitive testing were performed and patients completed questionnaires. Medical data were retrieved from medical dossiers. Hierarchical regression analyses were performed on fatigue severity (Fatigue Severity Scale; FSS) and cognitive complaints (Cognitive Consequences following Intensive Care Admission; CLC-IC; dichotomized into CLC-high/low). Variable blocks: 1. Demographic and premorbid factors (sex, age, education, comorbidities), 2. Illness severity (ICU/general ward, PROMIS physical functioning [PROMIS-PF]), 3. Neuro-cognitive factors (self-reported neurological symptoms, MRI abnormalities, cognitive performance), and 4. Psychological and social factors (Hospital Anxiety and Depression Scale [HADS], Utrecht Coping List, Social Support List), 5. Fatigue or cognitive complaints.

Results
The final models explained 60% (FSS) and 48% (CLC-IC) variance, with most blocks (except neuro-cognitive factors for FSS) significantly contributing. Psychological and social factors accounted for 5% (FSS) and 11% (CLC-IC) unique variance. Higher FSS scores were associated with younger age (p=.01), lower PROMIS-PF (p<.001), higher HADS-Depression (p=.03), and CLC-high (p=.04). Greater odds of CLC-high were observed in individuals perceiving more social support (OR=1.07, p<.05).

Conclusions
Results show that psychological and social factors add to biomedical factors in explaining persistent post-COVID-19 fatigue and cognitive complaints. Objective neuro-cognitive factors were not associated with symptoms. Findings highlight the importance of multidomain treatment, including psychosocial care, which may not target biologically-rooted symptoms directly but may reduce associated distress.

Paywall, https://www.archives-pmr.org/article/S0003-9993(24)00030-3/fulltext#

 

[EndME]

Is this a LC study or a PICS study? Does CBT have any merit in PICS?

 

[rvallee]

Well, rain definitely adds to the burden of hurricanes, but weather scientists don't go around claiming that the rain that fell during the hurricane is what caused it, even though you technically could make a case for it if you really wanted to and didn't care about being accurate, or respecting the linear passage of time. Because those sure are a bunch of mostly made-up numbers. And even taking them seriously, 5% and 11% are too small to matter.

They really seriously cannot tell the difference between causes and things that happen after, they just prefer to attribute them as causes and be done with it. And as usual that point to their inadequate technology as evidence, argument by ignorance. If they were studying famine, they would attribute the hunger as the cause for the famine. What absurd nonsense, no difference than old mythologies about curses and whatnot.

 

[dave30th]

Who are these people that keep producing such bullshit?

 

[Sean]

The game here is to flood the literature with apparently independent studies, all 'reproducing' the same basic result, using the same suite of flawed assumptions and methodology (mainly inadequate control of open label self-report measures, but also cherry picking evidence, selective interpretations, unfalsifiability, straw man, etc).

Then claim that the quantity and alleged independence constitutes robust assessment, while completely ignoring the core issue all along – the methodological quality, or lack of it.

 

[Midnattsol]

)Then claim that the quantity and alleged independence constitutes robust assessment, while completely ignoring the core issue all along – the methodological quality, or lack of it.

And unfortunately students are taught that the claim is true. Consistent results across multiple studies: robust findings. In nutrition there are rules of thumb such as How many RCTs / case/control and cohort studies have to point in the same direction for findings to be considered «robus enough».