@article {87277, title = {Recent smell loss is the best predictor of COVID-19 among individuals with recent respiratory symptoms}, journal = {Chem Senses}, volume = {46}, year = {2021}, month = {12/2020}, abstract = {

In a preregistered, cross-sectional study we investigated whether olfactory loss is a reliable predictor of COVID-19 using a crowdsourced questionnaire in 23 languages to assess symptoms in individuals self-reporting recent respiratory illness. We quantified changes in chemosensory abilities during the course of the respiratory illness using 0-100 visual analog scales (VAS) for participants reporting a positive (C19+; n=4148) or negative (C19-; n=546) COVID-19 laboratory test outcome. Logistic regression models identified univariate and multivariate predictors of COVID-19 status and post-COVID-19 olfactory recovery. Both C19+ and C19- groups exhibited smell loss, but it was significantly larger in C19+ participants (mean{\textpm}SD, C19+: -82.5{\textpm}27.2 points; C19-: -59.8{\textpm}37.7). Smell loss during illness was the best predictor of COVID-19 in both univariate and multivariate models (ROC AUC=0.72). Additional variables provide negligible model improvement. VAS ratings of smell loss were more predictive than binary chemosensory yes/no-questions or other cardinal symptoms (e.g., fever). Olfactory recovery within 40 days of respiratory symptom onset was reported for ~50\% of participants and was best predicted by time since respiratory symptom onset. We find that quantified smell loss is the best predictor of COVID-19 amongst those with symptoms of respiratory illness. To aid clinicians and contact tracers in identifying individuals with a high likelihood of having COVID-19, we propose a novel 0-10 scale to screen for recent olfactory loss, the ODoR-19. We find that numeric ratings <=2 indicate high odds of symptomatic COVID-19 (4\<OR\<10). Once independently validated, this tool could be deployed when viral lab tests are impractical or unavailable.

}, doi = {10.1093/chemse/bjaa081}, author = {Gerkin, RC and Ohla, K and Veldhuizen, MG and Joseph, PV and Kelly, CE and Bakke, AJ and Steele, KE and Farruggia, MC and Pellegrino, R and Pepino, MY and Bouysset, C and Soler, GM and Pereda-Loth, V and Dibattista, M and Cooper, KW and Croijmans, I and Di Pizio, A and Ozdener, MH and Fjaeldstad, AW and Lin, C and Sandell, MA and Singh, PB and Brindha, VE and Olsson, SB and Saraiva, LR and Ahuja, G and Alwashahi, MK and Bhutani, S and D{\textquoteright}Errico, A and Fornazieri, MA and Golebiowski, J and Hwang, LD and {\"O}zt{\"u}rk, L and Roura, E and Spinelli, S and Whitcroft, KL and Faraji, F and Fischmeister, FP and Heinbockel, T and Hsieh, JW and Huart, C and Konstantinidis, I and Menini, A and Morini, G and Olofsson, JK and Philpott, CM and Pierron, D and Shields, VDC and Voznessenskaya, VV and Albayay, J and Altundag, A and Bensafi, M and Bock, MA and Calcinoni, O and Fredborg, W and Laudamiel, C and Lim, J and Lundstr{\"o}m, JN and Macchi, A and Meyer, P and Moein, ST and Santamar{\'\i}a, E and Sengupta, D and Dominguez, PR and Yanik, H and Hummel, T and Hayes, JE and Reed, DR and Niv, MY and Munger, SD and Parma, V and GCCR Group} } @article {79777, title = {An optimized protocol for large-scale in situ sampling and analysis of volatile organic compounds }, journal = {Ecology and Evolution}, volume = {8}, year = {2018}, month = {06/2018}, pages = {5924-5936}, abstract = {

Chemical ecology is an ever-expanding field with a growing interest in population- and community-level studies. Many such studies are hindered due to lack of an efficient and accelerated protocol for large-scale sampling and analysis of chemical compounds. Here, we present an optimized protocol for such large-scale study of volatiles. A large-scale in situ study to understand role of semiochemicals in variation in mating success of lekking blackbuck was conducted. Suitable methods for sampling and statistical analysis were identified by testing and comparing the efficiencies of available techniques to reduce analysis time while retaining sensitivity and comprehensiveness. Solid-phase extraction using polydimethylsiloxane, analysis using a semiautomated detection of retention time and base peak, and statistical analysis using random forest algorithm were identified as the most efficient methods for large-scale in situ sampling and analysis of volatiles. The protocol for large-scale volatile analysis can facilitate evolutionary and metaecological studies of volatiles in situ from all types of biological samples. The protocol has potential for wider application with the analysis and interpretation methods being suitable for all kinds of semiochemicals, including nonvolatile chemicals.

}, doi = {10.1002/ece3.4138}, author = {Nair, Jyothi and Pragadheesh, V S and Karpe, Snehal D and Ramakrishnan, Uma and Olsson, SB} }