Patient-Reported Experiences of Persistent Post–COVID-19 Conditions After Hospital Discharge During the Second and Third Waves of the Pandemic in Switzerland: Cross-Sectional Questionnaire Study
Notice bibliographique
Résumé
Background Hospitalized patients infected with SARS-CoV-2 should recover within a few weeks. However, even those with mild versions can experience symptoms lasting 4 weeks or longer. These post–COVID-19 condition (PCC) comprise various new, returning, or ongoing symptoms that can last for months or years and cause disability. Few studies have investigated PCC using self-reports from discharged patients infected with SARS-CoV-2 to complement clinical and biomarker studies. Objective This study aimed to investigate self-reported, persistent PCC among patients infected with SARS-CoV-2 who were discharged during the second and third waves of the COVID-19 pandemic. Methods We designed, pretested, and posted an ad hoc paper questionnaire to all eligible inpatients discharged between October 2020 and April 2021. At 4 months post discharge, we collected data on PCC and scores for the Multidimensional Fatigue Inventory (MFI), the Patient Health Questionnaire-4 (PHQ-4), a Brief Memory Screening Scale (Q3PC), and a posttraumatic stress disorder scale (PCL-5). Descriptive, inferential, and multivariate linear regression statistics assessed PCC symptomatology, associations, and differences regarding sociodemographic characteristics and hospital length of stay (LOS). We examined whether our variables of interest significantly predicted MFI scores. Results Of the 1993 valid questionnaires returned, 245 were from discharged patients with SARS-CoV-2 (median age 71, IQR 62.7-77 years). Only 28.2% (69/245) of respondents were symptom-free after 4 months. Women had significantly more persistent PCC symptoms than men (P≤.001). Patients with a hospital LOS ≥11 days had more PCC symptoms as well (P<.001)—women had more symptoms and longer LOS. No significant differences were found between age groups (18-64, 65-74, and ≥75 years old; P=.50) or between intensive care units and other hospitalization units (P=.09). Patients self-reported significantly higher PHQ-4 scores during their hospitalization than at 4 months later (P<.001). Three-fourth (187/245, 76.4%) of the respondents reported memory loss and concentration disorders (Q3PC). No significant differences in the median MFI score (56, IQR 1-3, range 50-60]) were associated with sociodemographic variables. Patients with a hospital LOS of ≥11 days had a significantly higher median PCL-5 score (P<.001). Multivariate linear regression allowed us to calculate that the combination of PHQ-4, Q3PC, and PCL-5 scores, adjusted for age, sex, and LOS (of either ≥11 days [median 2 symptoms, IQR 1-5] or <11 days), did not significantly predict MFI scores (R2=0.09; F4,7 =1.5; P=.22; adjusted R2=0.06). Conclusions The majority of inpatients infected with SARS-CoV-2 presented with PCC 4 months after discharge, with complex clinical pictures. Only one-third of them were symptom-free during that time. Based on our findings, MFI scores were not directly related to self-reported depression, anxiety, or posttraumatic scores adjusted for age, sex, or LOS. Further research is needed to explore PCC and fatigue based on self-reported health experiences of discharged inpatients infected with SARS-CoV-2.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».