PASC in Solid Organ Transplant Recipients With Self-reported SARS-CoV-2 Infection
Bibliographic record
Abstract
BACKGROUND: Postacute sequelae of SARS-CoV-2 infection (PASC) is an increasingly recognized phenomenon and manifested by long-lasting cognitive, mental, and physical symptoms beyond the acute infection period. We aimed to estimate the frequency of PASC symptoms in solid organ transplant (SOT) recipients and compared their frequency between those with SARS-CoV-2 infection requiring hospitalization and those who did not require hospitalization. METHODS: A survey consisting of 7 standardized questionnaires was administered to 111 SOT recipients with history of SARS-CoV-2 infection diagnosed >4 wk before survey administration. RESULTS: Median (interquartile range) time from SARS-CoV-2 diagnosis was 167 d (138-221). Hospitalization for SARS-CoV-2 infection was reported in 33 (30%) participants. Symptoms after the COVID episode were perceived as following: significant trauma (53%), cognitive decline (50%), fatigue (41%), depression (36%), breathing problems (35%), anxiety (23%), dysgeusia (22%), dysosmia (21%), and pain (19%). Hospitalized patients had poorer median scores in cognition (Quick Dementia Rating System survey score: 2.0 versus 0.5, P = 0.02), quality of life (Health-related Quality of Life survey: 2.0 versus 1.0, P = 0.015), physical health (Global physical health scale: 10.0 versus 11.0, P = 0.005), respiratory status (Breathlessness, Cough and Sputum Scale: 1.0 versus 0.0, P = 0.035), and pain (Pain score: 3 versus 0 out of 10, P = 0.003). Among patients with infection >6 mo prior, some symptoms were still present as following: abnormal breathing (42%), cough (40%), dysosmia (29%), and dysgeusia (34%). CONCLUSIONS: SOT recipients reported a high frequency of PASC symptoms. Multidisciplinary approach is needed to care for these patients beyond the acute phase.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".