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Record W3037320721 · doi:10.1002/alr.22650

Challenges in interpreting the diagnostic performance of symptoms to predict COVID‐19 status: The case of anosmia

2020· review· en· W3037320721 on OpenAlexaff
Paolo Boscolo‐Rizzo, Daniele Borsetto, Claire Hopkins, Jerry Polesel

Bibliographic record

VenueInternational Forum of Allergy & Rhinology · 2020
Typereview
Languageen
FieldNeuroscience
TopicOlfactory and Sensory Function Studies
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsAnosmiaMedicineCoronavirus disease 2019 (COVID-19)Context (archaeology)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)DiseaseTastePositive predicative valuePredictive valueSeverity of illnessPredictive value of testsInternal medicineInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

There is mounting evidence that a sudden onset of altered sense of smell and/or taste is closely related to coronavirus disease-2019 (COVID-19). The severe acute respiratory syndrome‒coronavirus-2 (SARS-CoV-2) was observed to impair the sense of smell and/or taste in about two thirds of mild to moderate cases of COVID-19.1, 2 Consequently, several studies have tried to estimate the sensitivity and specificity as well as the positive predictive value of self-reported new onset of smell and/or taste impairment for COVID-19 in populations of patients with flulike symptoms. When faced with this task in the context of COVID-19, 2 main problems are predictably encountered. The first is that the standard diagnostic tool for diagnosis of SARS-CoV-2 infection, namely SARS-CoV-2 real-time polymerase chain reaction (RT-PCR) on a nasopharyngeal sample, is insufficient to rule-out COVID-19 when negative. Although its specificity is excellent, nasopharyngeal swab shows suboptimal sensitivity for SARS-CoV-2 detection in the early phase of infection being inconsistent during serial testing.3 Moreover, patients developing COVID-19‒related symptoms may be referred to nasopharyngeal swab later during the course of the disease when viral load is no longer detectable.4, 5 Thus, the diagnostic performance of new onset of smell and/or taste impairment for COVID-19 may be even higher than estimated. The other problem concerns the pretest probability of disease. Predictive values refer to the ability of a test result or symptom presence to confirm the presence or absence of a disease, based on positive predictive value (PPV) or negative predictive value (NPV), respectively. Although sensitivity and specificity are properties of a test itself that will not be affected by the characteristics and prevalence of disease in the population, PPV and NPV are strongly influenced by the prevalence of the disease in the target population.6 Among patients with flulike symptoms, the prevalence of SARS-CoV-2 infection may vary substantially according to geographic context and disease phase. For example, the study by Tostmann et al, conducted in The Netherlands during the early phase of the COVID-19 pandemic, demonstrated a prevalence of 11% in SARS-CoV-2‒positive subjects among patients with a flulike illness,7 whereas Zayet et al reported a prevalence of 44% in their cohort of patients evaluated in a French hospital.4 We performed a review of the literature to identify studies that tested patients with flulike symptoms for SARS-CoV-2 infection by RT-PCR and that reported data on the prevalence of loss of smell and/or taste. We identified a total of 6 studies (Fig. 1A).2, 4, 7-10 Sensitivity and specificity were represented using forest plots, and pooled estimates were calculated using a random intercept logistic regression model. Publication bias was assessed by funnel plot. PPVs and NPVs were calculated as a function of prevalence of COVID-19, ranging from 0% to 100%, using pooled sensitivity and specificity. Forest plots of the sensitivity and specificity of new-onset chemosensory impairment for diagnosing COVID-19 are shown in Figure 1A. Although the pooled sensitivity was 61% (95% confidence interval [CI], 55-68%), pooled specificity reached 87% (95% CI, 80-92%), with publication bias being possible (Fig. 1B). Given this sensitivity and specificity, Figure 1C shows the variation of PPV and NPV, with a prevalence of SARS-CoV-2 infection in patients with flulike symptoms. For example, if the prevalence is 50%, PPV and NPV would be 82% and 69%, respectively; however, when prevalence is 10%, PPV would decline to 34% and NPV would increase to 95%. Thus, in a different phase of the COVID-19 pandemic and in a different geographic context with a different diffusion of SARS-CoV-2, the PPV of the new onset of smell and/or taste loss may vary dramatically. Moreover, the increased impact of other viruses causing flulike symptoms may superimpose to SARS-CoV-2 circulation in next fall/winter season, thus further decreasing the PPV of new onset of smell and/or taste loss for COVID-19. In conclusion, we believe that a new onset of smell and/or taste loss during the COVID-19 pandemic should be considered a manifestation of SARS-CoV-2 infection until proven otherwise, sufficient to justify testing, self-isolation, and the use of personal protective equipment by medical personnel interacting with these subjects. However, taking into account the aforementioned considerations, diagnostic indications of individual symptoms should be fully understood and considered with caution when predicting SARS-CoV-2 infection in patients with flulike symptoms.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score0.678

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.161
GPT teacher head0.345
Teacher spread0.184 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

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Citations9
Published2020
Admission routes1
Has abstractyes

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