The Plight of Patients with Lupus Nephritis during the Outbreak of COVID-19 in Wuhan, China
Bibliographic record
Abstract
To the Editor: The number of cases of SARS-CoV-2 infection is rising rapidly globally. Severe disease and high fatality are observed in older patients and those with comorbid conditions1. However, little is known about patients with rheumatic disease in the epidemic areas. Patients with rheumatic diseases are subject to societal lockdown and enforced quarantine, leading to inaccessibility to healthcare. Also, their immunosuppressed state heightens the fear of contracting coronavirus disease 2019 (COVID-19). Here we report the outcomes of a cohort of 101 patients with lupus nephritis (LN) including 2 confirmed COVID-19 cases during a surge of the outbreak of COVID-19 from January to February 2020, in Wuhan, China. We conducted a study by questionnaires and telephone interviews in March 2020. Questionnaires were sent to 160 patients with LN followed up in … Address correspondence to Dr. C. Xu, Tan Tock Seng Hospital, Department of Rheumatology, Allergy, and Immunology, Singapore. E-mail: xuchuanhui2008{at}gmail.com
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.001 |
| 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".