Suitability and Sufficiency of Telehealth Clinician-Observed, Participant-Collected Samples for SARS-CoV-2 Testing: The iCollect Cohort Pilot Study
Bibliographic record
Abstract
BACKGROUND: The severe acute respiratory coronavirus 2 (SARS-CoV-2) pandemic calls for expanded opportunities for testing, including novel testing strategies such as home-collected specimens. OBJECTIVE: We aimed to understand whether oropharyngeal swab (OPS), saliva, and dried blood spot (DBS) specimens collected by participants at home and mailed to a laboratory were sufficient for use in diagnostic and serology tests of SARS-CoV-2. METHODS: Eligible participants consented online and were mailed a participant-collection kit to support collection of three specimens for SARS-CoV-2 testing: saliva, OPS, and DBS. Participants performed the specimen collection procedures during a telehealth video appointment while clinical observers watched and documented the suitability of the collection. The biological sufficiency of the specimens for detection of SARS-CoV-2 by reverse transcriptase-polymerase chain reaction and serology testing was assessed by laboratorians using visual inspection and quantification of the nucleic acid contents of the samples by ribonuclease P (RNase P) measurements. RESULTS: Of the enrolled participants,153/159 (96.2%) returned their kits, which were included in this analysis. All these participants attended their video appointments. Clinical observers assessed that of the samples collected, 147/153 (96.1%) of the saliva samples, 146/151 (96.7%) of the oropharyngeal samples, and 135/145 (93.1%) of the DBS samples were of sufficient quality for submission for laboratory testing; 100% of the OPS samples and 98% of the saliva samples had cycle threshold values for RNase P <30, indicating that the samples contained sufficient nucleic acid for RNA-PCR testing for SARS-CoV-2. CONCLUSIONS: These pilot data indicate that most participant-collected OPS, saliva, and DBS specimens are suitable and sufficient for testing for SARS-CoV-2 RNA and serology. Clinical observers rated the collection of specimens as suitable for testing, and visual and quantitative laboratory assessment indicated that the specimens were biologically sufficient. These data support the utility of participant-collected and mailed-in specimens for SARS-CoV-2 testing. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/19054.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".