ABSTRACT
Introduction: The COVID-19 pandemic has challenged researchers to use remote data collection. Our project includes determining DLMO phase, requiring a family-friendly without face-to-face interaction. We describe here our protocol, experiences, lessons learned, and findings from the first 15 participants. Methods: Fifteen urban-dwelling children with moderate to severe persistent asthma [7 girls, ages 7 (n=1) to 10 years;and 8 boys, 8 or 9 years] and caregiver (CG) participated. CG tracked bedtimes and risetimes in daily diaries for 10-14 days;average bedtimes from 5 nights preceding saliva collection were used to determine timing for 10 half-hourly samples. CG and child were oriented and then watched a demo video. A spit-kit was delivered to the home the afternoon of the study. Kits included a small cooler bag with bottle of water, 10 numbered and 5 spare Salivette tubes (Starstedt, Germany), plastic bag, dark wraparound glasses with securing strap, and log sheet. Data collection began with a zoom call with staff, CG, and child to reiterate the instructions, answer questions, and observe the first sample. Thereafter, a staff member telephoned the caregiver every 30 minutes to prompt the next sample and query whether glasses had been kept on. CG placed kit outside the home for morning pick up. Samples were centrifuged and frozen (-20°) until sending to the assay lab (SolidPhase, Portland, ME) for melatonin radioimmunoassay (Alpco, Windham, NH). Results: DLMO phase was determined with a 4pg/ml threshold for 11 children. DLMO phases (mtime=21:46±68 min) and average bedtimes (mtime=20:40±88min) were positively correlated (r=.87). Challenges identified for missed DLMOs included: one child supervised by a teenaged sibling (not CG);one child/CG identified as potentially uncooperative. The other two misses likely arose from low saliva quantity, inconsistencies with staff training, and inadequate description of requirements for wearing glasses. Procedure modifications included strategies tailored to families' needs, experiences, and home environment that can challenge adherence to protocol, greater emphasis on wearing glasses, and cartoon reminder card and scales added to kit. Subsequent samples were successful. Conclusion: Our approach was effective for determining DLMO phase in children using a remote approach with careful application of methods.
ABSTRACT
Background and Aim: Salivary SARS-CoV-2 Ab determination could be suitable for monitoring the viral spread and vaccination efficacy, especially in pediatric patients. We investigated N/S1-RBD IgG antibody levels in salivary samples of infectious-naïve vaccinated subjects and of COVID-19 patients, further comparing levels with serum anti-SARS-CoV-2 S-RBD IgG. Methods: A total of 72 subjects were enrolled at the Padova University Hospital: 36 COVID-19 patients and 36 health care workers (HCW), who underwent a complete vaccination campaign with BNT162b2 (BioNTech/Pfizer). All collected a salivary sample, using Salivette (Sarstedt, Nümbrecht Germany). For 9 HCW, salivary samples were collected at three different times within the same day (before breakfast, at 10 am, and after lunch). A serum sample was also collected for all individuals. Time post symptoms onset or time from the first vaccine were also recorded. Salivary COVID-19 N/S1 RBD (sal-IgG) ELISA (RayBiotech, GA, USA) and anti-SARS-CoV-2 S-RBD IgG Ab (ser-IgG) (Snibe Diagnostics, Shenzhen, China) were used for determining IgG Ab. Results: Subjects' mean age (±sd) was 35.8±18.2 yrs. Age significantly differed (p<0.001) from COVID-19 patients [29.7±17.3 yrs] and HCW [47.1±12.9 yrs]. Positive sal-IgG were found in 70/72 (97.2%) samples;in sera, 71/72 (98.6%) samples were positive to ser-IgG. The sal-IgG median levels differed from COVID-19 to vaccinated HCW, being in salivary samples 0.21 kAU/L and 0.8 kAU/L (p =0.030), respectively;median levels for ser-IgG in COVID-19 and vaccinated HCW were 135 kBAU/L and 940 kBAU/L, respectively (p<0.001). Salivary IgG levels were not influenced by time post-symptom onset or time post-vaccination, both on vaccinated HCW (rho= -0.147, p=0.402) and COVID-19 subjects (rho=0.0267, p=0.986). Ser-IgG levels was not influenced by the time post-symptom onset for COVID-19 subjects (rho=0.102, p=0.419), while a strong significant correlation was found with time post-vaccination in HCW (rho=-0.6292, p<0.001). Sal-IgG levels were notinfluenced by the daytime of collection (rho=0.148, p=0.373). Passing-Bablok regressions showed that sar- IgG and ser-IgG comparability was assessable only when ser-IgG values were divided by 1000, being slope and intercept 0.068 (95%CI: 0.069-0.341) and 0.221 (95%CI:- 0.097 to 0.786), respectively. Conclusions: Salivary IgG is efficiently detectable both in COVID-19 and in vaccinated individuals and analyses appeared to be not influenced by the daytime of collection. The analyses performed showed that, overall, sal-IgG were lower than ser-IgG, and thus comparability with serum levels needs to be better explored.