Infectious Diseases Society of America.

Background The diagnostic challenges associated with the COVID‐19 pandemic resulted in rapid development of diagnostic test methods for detecting SARS‐CoV‐2 infection. Serology tests to detect the presence of antibodies to SARS‐CoV‐2 enable detection of past infection and may detect cases of SARS‐CoV‐2 infection that were missed by earlier diagnostic tests. Understanding the diagnostic accuracy of serology tests for SARS‐CoV‐2 infection may enable development of effective diagnostic and management pathways, inform public health management decisions and understanding of SARS‐CoV‐2 epidemiology. Objectives To assess the accuracy of antibody tests, firstly, to determine if a person presenting in the community, or in primary or secondary care has current SARS‐CoV‐2 infection according to time after onset of infection and, secondly, to determine if a person has previously been infected with SARS‐CoV‐2. Sources of heterogeneity investigated included: timing of test, test method, SARS‐CoV‐2 antigen used, test brand, and reference standard for non‐SARS‐CoV‐2 cases. Search methods The COVID‐19 Open Access Project living evidence database from the University of Bern (which includes daily updates from PubMed and Embase and preprints from medRxiv and bioRxiv) was searched on 30 September 2020. We included additional publications from the Evidence for Policy and Practice Information and Co‐ordinating Centre (EPPI‐Centre) ‘COVID‐19: Living map of the evidence’ and the Norwegian Institute of Public Health ’NIPH systematic and living map on COVID‐19 evidence’. We did not apply language restrictions. Selection criteria We included test accuracy studies of any design that evaluated commercially produced serology tests, targeting IgG, IgM, IgA alone, or in combination. Studies must have provided data for sensitivity, that could be allocated to a predefined time period after onset of symptoms, or after a positive RT‐PCR test. Small studies with fewer than 25 SARS‐CoV‐2 infection cases were excluded. We included any reference standard to define the presence or absence of SARS‐CoV‐2 (including reverse transcription polymerase chain reaction tests (RT‐PCR), clinical diagnostic criteria, and pre‐pandemic samples). Data collection and analysis We use standard screening procedures with three reviewers. Quality assessment (using the QUADAS‐2 tool) and numeric study results were extracted independently by two people. Other study characteristics were extracted by one reviewer and checked by a second. We present sensitivity and specificity with 95% confidence intervals (CIs) for each test and, for meta‐analysis, we fitted univariate random‐effects logistic regression models for sensitivity by eligible time period and for specificity by reference standard group. Heterogeneity was investigated by including indicator variables in the random‐effects logistic regression models. We tabulated results by test manufacturer and summarised results for tests that were evaluated in 200 or more samples and that met a modification of UK Medicines and Healthcare products Regulatory Agency (MHRA) target performance criteria. Main results We included 178 separate studies (described in 177 study reports, with 45 as pre‐prints) providing 527 test evaluations. The studies included 64,688 samples including 25,724 from people with confirmed SARS‐CoV‐2; most compared the accuracy of two or more assays (102/178, 57%). Participants with confirmed SARS‐CoV‐2 infection were most commonly hospital inpatients (78/178, 44%), and pre‐pandemic samples were used by 45% (81/178) to estimate specificity. Over two‐thirds of studies recruited participants based on known SARS‐CoV‐2 infection status (123/178, 69%). All studies were conducted prior to the introduction of SARS‐CoV‐2 vaccines and present data for naturally acquired antibody responses. Seventy‐nine percent (141/178) of studies reported sensitivity by week after symptom onset and 66% (117/178) for convalescent phase infection. Studies evaluated enzyme‐linked immunosorbent assays (ELISA) (165/527; 31%), chemiluminescent assays (CLIA) (167/527; 32%) or lateral flow assays (LFA) (188/527; 36%). Risk of bias was high because of participant selection (172, 97%); application and interpretation of the index test (35, 20%); weaknesses in the reference standard (38, 21%); and issues related to participant flow and timing (148, 82%). We judged that there were high concerns about the applicability of the evidence related to participants in 170 (96%) studies, and about the applicability of the reference standard in 162 (91%) studies. Average sensitivities for current SARS‐CoV‐2 infection increased by week after onset for all target antibodies. Average sensitivity for the combination of either IgG or IgM was 41.1% in week one (95% CI 38.1 to 44.2; 103 evaluations; 3881 samples, 1593 cases), 74.9% in week two (95% CI 72.4 to 77.3; 96 evaluations, 3948 samples, 2904 cases) and 88.0% by week three after onset of symptoms (95% CI 86.3 to 89.5; 103 evaluations, 2929 samples, 2571 cases). Average sensitivity during the convalescent phase of infection (up to a maximum of 100 days since onset of symptoms, where reported) was 89.8% for IgG (95% CI 88.5 to 90.9; 253 evaluations, 16,846 samples, 14,183 cases), 92.9% for IgG or IgM combined (95% CI 91.0 to 94.4; 108 evaluations, 3571 samples, 3206 cases) and 94.3% for total antibodies (95% CI 92.8 to 95.5; 58 evaluations, 7063 samples, 6652 cases). Average sensitivities for IgM alone followed a similar pattern but were of a lower test accuracy in every time slot. Average specificities were consistently high and precise, particularly for pre‐pandemic samples which provide the least biased estimates of specificity (ranging from 98.6% for IgM to 99.8% for total antibodies). Subgroup analyses suggested small differences in sensitivity and specificity by test technology however heterogeneity in study results, timing of sample collection, and smaller sample numbers in some groups made comparisons difficult. For IgG, CLIAs were the most sensitive (convalescent‐phase infection) and specific (pre‐pandemic samples) compared to both ELISAs and LFAs (P < 0.001 for differences across test methods). The antigen(s) used (whether from the Spike‐protein or nucleocapsid) appeared to have some effect on average sensitivity in the first weeks after onset but there was no clear evidence of an effect during convalescent‐phase infection. Investigations of test performance by brand showed considerable variation in sensitivity between tests, and in results between studies evaluating the same test. For tests that were evaluated in 200 or more samples, the lower bound of the 95% CI for sensitivity was 90% or more for only a small number of tests (IgG, n = 5; IgG or IgM, n = 1; total antibodies, n = 4). More test brands met the MHRA minimum criteria for specificity of 98% or above (IgG, n = 16; IgG or IgM, n = 5; total antibodies, n = 7). Seven assays met the specified criteria for both sensitivity and specificity. In a low‐prevalence (2%) setting, where antibody testing is used to diagnose COVID‐19 in people with symptoms but who have had a negative PCR test, we would anticipate that 1 (1 to 2) case would be missed and 8 (5 to 15) would be falsely positive in 1000 people undergoing IgG or IgM testing in week three after onset of SARS‐CoV‐2 infection. In a seroprevalence survey, where prevalence of prior infection is 50%, we would anticipate that 51 (46 to 58) cases would be missed and 6 (5 to 7) would be falsely positive in 1000 people having IgG tests during the convalescent phase (21 to 100 days post‐symptom onset or post‐positive PCR) of SARS‐CoV‐2 infection. Authors' conclusions Some antibody tests could be a useful diagnostic tool for those in whom molecular‐ or antigen‐based tests have failed to detect the SARS‐CoV‐2 virus, including in those with ongoing symptoms of acute infection (from week three onwards) or those presenting with post‐acute sequelae of COVID‐19. However, antibody tests have an increasing likelihood of detecting an immune response to infection as time since onset of infection progresses and have demonstrated adequate performance for detection of prior infection for sero‐epidemiological purposes. The applicability of results for detection of vaccination‐induced antibodies is uncertain. 

/pdf/antibody-tests-for-identification-of-current-and-past-12g43ag9.pdf

Antibody tests for identification of current and past infection with SARS-CoV-2

Comparison of eight commercial, high-throughput, automated or ELISA assays detecting SARS-CoV-2 IgG or total antibody.

Evidence from studies in the general population suggests an association between vitamin D insufficiency/deficiency and COVID-19 susceptibility and disease severity. The present study was performed on 165 third-trimester pregnant women at the time of delivery. Seventy-nine women tested negative for SARS-CoV-2. From 86 women testing positive, 32 were asymptomatic, 44 presented a mild form of the disease, and 10 experienced severe symptoms. Serum 25-OH vitamin D levels were measured on blood samples collected on admission. Low vitamin D levels were detected in symptomatic but not asymptomatic COVID-19 patients compared to healthy women (p = 0.0227). In addition, 20 (45.4%) pregnant women in the mild COVID-19 group and 6 (60%) in the severe group were vitamin D deficient (p = 0.030). On the other hand, lasso regression analysis showed that 25-OH vitamin D deficiency is an independent predictor of severe COVID-19 with an odds ratio (OR) of 5.81 (95% CI: 1.108–30.541; p = 0.037). These results show the relationship between vitamin D deficiency in pregnant women and the severity of COVID-19 infection and support the recommendation to supplement with vitamin D to avoid worse COVID-19 outcomes during pregnancy.

/pdf/association-between-25-oh-vitamin-d-deficiency-and-covid-19-2k2nm0uk.pdf

Association between 25-OH Vitamin D Deficiency and COVID-19 Severity in Pregnant Women

This study aims to create a precise skin cancer classification system (SC-CS) able to distinguish various skin cancer types. Targeted categories include melanoma, vascular lesions, melanocytic nevus, cutaneous fibromas, benign keratosis, and different carcinomas and skin moles. The system employs image segmentation and convolutional neural network (CNN) algorithms within a double artificial multiple intelligence system (AMIS) ensemble model, optimizing results weighting for superior solution quality. Evaluation of the SC-CS involved assessing metrics like accuracy, precision, AUC, and F1-score, and gathering feedback from 31 volunteers, including dermatologists, medical professionals and other medical staff with expertise in skin cancer diagnosis. The system accurately classified varied skin cancer types using HAM10000 and malignant vs. benign datasets, chosen for their broad representation and research utility. With over 99.4% accuracy, it surpassed state-of-the-art models by 2.1% for larger and 15.7% for smaller sizes. The high system usability scale (SUS) score of 96.85% signals strong user satisfaction and recommendation potential. High data security ensured patient privacy, with no access to personal information. Uploaded data and images are promptly deleted after processing. The system aids dermatologists in accurate skin cancer diagnosis, integrating into workflows with resource requirements. Performance varies with image quality, dataset diversity, and population-specific variations. 

Double AMIS-ensemble deep learning for skin cancer classification

Objectives Studies investigating the association between vitamin D and severity of COVID-19 have mixed results perhaps due to immunoassay assessment of total 25-hydroxyvitamin D (tD) (the sum of 25-hydroxyvitamin-D2 [25-OH-D2] and 25-hydroxyvitamin-D3 [25-OH-D3]). Liquid chromatography tandem mass spectrometry (LC-MS/MS) has high analytical specificity and sensitivity for 25-OH-D2 and 25-OH-D3, and thus enables a more accurate assessment of impact on COVID-19 outcomes. Methods We established reference intervals for 25-OH-D3 and tD using LC-MS/MS. 25-OH-D2, 25-OH-D3 and tD were quantitated for 88 COVID-19 positive and 122 COVID-19 negative specimens. Chi-square or Fisher’s exact tests were used to test associations in binary variables. T-Tests or Wilcoxon rank sum tests were used for continuous variables. Cox proportional hazards were used to test associations between 25-OH-D3 or tD levels and length of stay (LOS). For mortality and ventilation, logistic regression models were used. Results COVID-19 patients with deficient (<20 ng/mL) levels of 25-OH-D3 had significantly longer LOS by 15.3 days. COVID-19 P patients with deficient (<20 ng/mL) and insufficient (<30 ng/mL) of tD had significantly longer LOS by 12.1 and 8.2 days, respectively. Patients with insufficient levels of tD had significantly longer LOS by 13.7 days. COVID-19 patients with deficient serum 25-OH-D3 levels had significantly increased risk-adjusted odds of in-hospital mortality (OR [95% CI]: 5.29 [1.53–18.24]); those with insufficient 25-OH-D3 had significantly increased risk for requiring ventilation during hospitalization was found at LCMS insufficient cutoff (OR [95% CI]: 2.75 [1.10–6.90]). Conclusions There is an inverse relationship of 25-hydroxyvitamin D levels and hospital LOS for COVID-19 patients. Vitamin D status is a predictor for severity of outcomes. LCMS results are useful for assessing the odds of mortality and the need for ventilation during hospitalization.

/pdf/25-hydroxyvitamin-d-is-a-predictor-of-covid-19-severity-of-23qinvo4.pdf

25-hydroxyvitamin D is a predictor of COVID-19 severity of hospitalized patients

Public health emergency of SARS-CoV-2 has facilitated diagnostic testing as a related medical countermeasure against COVID-19 outbreak. Numerous serologic antibody tests have become available through an expedited federal emergency use only process. This paper highlights the analytical characteristic of an ELISA based assay by AnshLabs and three random access immunoassay (RAIA) by DiaSorin, Roche, and Abbott that have been approved for emergency use authorization (EUA), at a tertiary academic center in a low disease-prevalence area. The AnshLabs gave higher estimates of sero-prevalence, over the three RAIA methods. For positive results, AnshLabs had 93.3% and 100% agreement with DiaSorin or Abbott and Roche respectively. For negative results, AnshLabs had 74.3% and 78.3% agreement with DiaSorin and Roche or Abbott respectively. All discrepant samples that were positive by AnshLabs and negative by RAIA tested positive by all-in-one step SARS-CoV-2 Total (COV2T) assay performed on the automated Siemens Advia Centaur XPT analyzer. None of these methods, however, are useful in early diagnosis of SARS-CoV-2.

/pdf/correlation-of-elisa-method-with-three-other-automated-29o2kacc35.pdf

Correlation of ELISA method with three other automated serological tests for the detection of anti-SARS-CoV-2 antibodies.

Spinal metastasis accounts for 70% of the bone metastases of tumors, so how to diagnose and predict spinal metastasis in time through effective methods is very important for the physiological evaluation of the therapy of patients.MRI scans of 941 patients with spinal metastases from the affiliated hospital of Guilin Medical University were collected, analyzed, and preprocessed, and the data were submitted to a deep learning model designed with our convolutional neural network. We also used the Softmax classifier to classify the results and compared them with the actual data to judge the accuracy of our model.Our research showed that the practical model method could effectively predict spinal metastases. The accuracy was up to 96.45%, which could be used to diagnose the physiological evaluation of spinal metastases.The model obtained in the final experiment can capture the focal signs of patients with spinal metastases more accurately and can predict the disease in time, which has a good application prospect. 

https://doi.org/10.1016/j.jbo.2023.100483

Deep learning-based magnetic resonance imaging of the spine in the diagnosis and physiological evaluation of spinal metastases

Public health emergency of SARS-CoV-2 has facilitated diagnostic testing as a related medical countermeasure against COVID-19 outbreak. Numerous serologic antibody tests have become available through an expedited federal emergency use only process. This paper highlights the analytical characteristic of an ELISA based assay by AnshLabs and three random access immunoassay (RAIA) by DiaSorin, Roche, and Abbott that have been approved for emergency use authorization (EUA), at a tertiary academic center in a low disease-prevalence area. The AnshLabs gave higher estimates of sero-prevalence, over the three RAIA methods. For positive results, AnshLabs had 93.3% and 100% concordance with DiaSorin or Abbott and Roche respectively. For negative results, AnshLabs had 69.7% and 73.0% concordance with DiaSorin and Roche or Abbott respectively. All discrepant samples that were positive by AnshLabs and negative by RAIA tested positive by all-in-one step SARS-CoV-2 Total (COV2T) assay performed on the automated Siemens Advia Centaur XPT analyzer. None of these methods, however, are useful in early diagnosis of SARS-CoV-2.

/pdf/correlation-of-elisa-based-with-random-access-serologic-423om61if9.pdf

Correlation of ELISA based with random access serologic immunoassays for identifying adaptive immune response to SARS-CoV-2

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25-hydroxyvitamin D is a predictor of COVID-19 severity of hospitalized patients

Correlation of ELISA method with three other automated serological tests for the detection of anti-SARS-CoV-2 antibodies.

Deep learning-based magnetic resonance imaging of the spine in the diagnosis and physiological evaluation of spinal metastases

Correlation of ELISA based with random access serologic immunoassays for identifying adaptive immune response to SARS-CoV-2