Frequency of serological non-responders and false-negative RT-PCR results in SARS-CoV-2 testing: a population-based study

AbstractObjectivesThe sensitivity of molecular and serological methods for COVID-19 testing in an epidemiological setting is not well described. The aim of the study was to determine the frequency of negative RT-PCR results at first clinical presentation as well as negative serological results after a follow-up of at least 3 weeks.MethodsAmong all patients seen for suspected COVID-19 in Liechtenstein (n=1921), we included initially RT-PCR positive index patients (n=85) as well as initially RT-PCR negative (n=66) for follow-up with SARS-CoV-2 antibody testing. Antibodies were detected with seven different commercially available immunoassays. Frequencies of negative RT-PCR and serology results in individuals with COVID-19 were determined and compared to those observed in a validation cohort of Swiss patients (n=211).ResultsAmong COVID-19 patients in Liechtenstein, false-negative RT-PCR at initial presentation was seen in 18% (12/66), whereas negative serology in COVID-19 patients was 4% (3/85). The validation cohort showed similar frequencies: 2/66 (3%) for negative serology, and 16/155 (10%) for false negative RT-PCR. COVID-19 patients with negative follow-up serology tended to have a longer disease duration (p=0.05) and more clinical symptoms than other patients with COVID-19 (p<0.05). The antibody titer from quantitative immunoassays was positively associated with the number of disease symptoms and disease duration (p<0.001).ConclusionsRT-PCR at initial presentation in patients with suspected COVID-19 can miss infected patients. Antibody titers of SARS-CoV-2 assays are linked to the number of disease symptoms and the duration of disease. One in 25 patients with RT-PCR-positive COVID-19 does not develop antibodies detectable with frequently employed and commercially available immunoassays.

Download Full-text

Scoring System for the Diagnosis of COVID-19

The Open Public Health Journal ◽

10.2174/1874944502013010413 ◽

2020 ◽

Vol 13 (1) ◽

pp. 413-414 ◽

Cited By ~ 1

Author(s):

Mohamed Farouk Allam

Keyword(s):

Scoring System ◽

Clinical Symptoms ◽

False Negative ◽

Nasopharyngeal Swab ◽

Rt Pcr ◽

Pcr Assay ◽

Negative Results ◽

False Negative Results ◽

Symptoms And Signs

Due to the international spread of COVID-19, the difficulty of collecting nasopharyngeal swab specimen from all suspected patients, the costs of RT-PCR and CT, and the false negative results of RT-PCR assay in 41% of COVID-19 patients, a scoring system is needed to classify the suspected patients in order to determine the need for follow-up, home isolation, quarantine or the conduction of further investigations. A scoring system is proposed as a diagnostic tool for suspected patients. It includes Epidemiological Evidence of Exposure, Clinical Symptoms and Signs, and Investigations (if available). This scoring system is simple, could be calculated in a few minutes, and incorporates the main possible data/findings of any patient.

Download Full-text

Incorporating false negative tests in epidemiological models for SARS-CoV-2 transmission and reconciling with seroprevalence estimates

Scientific Reports ◽

10.1038/s41598-021-89127-1 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Rupam Bhattacharyya ◽

Ritoban Kundu ◽

Ritwik Bhaduri ◽

Debashree Ray ◽

Lauren J. Beesley ◽

...

Keyword(s):

False Negative ◽

Population Based ◽

Training Data ◽

Epidemiological Models ◽

Rt Pcr ◽

Antibody Prevalence ◽

Igg Antibody ◽

False Negatives ◽

Seir Model ◽

Study Population

AbstractSusceptible-Exposed-Infected-Removed (SEIR)-type epidemiologic models, modeling unascertained infections latently, can predict unreported cases and deaths assuming perfect testing. We apply a method we developed to account for the high false negative rates of diagnostic RT-PCR tests for detecting an active SARS-CoV-2 infection in a classic SEIR model. The number of unascertained cases and false negatives being unobservable in a real study, population-based serosurveys can help validate model projections. Applying our method to training data from Delhi, India, during March 15–June 30, 2020, we estimate the underreporting factor for cases at 34–53 (deaths: 8–13) on July 10, 2020, largely consistent with the findings of the first round of serosurveys for Delhi (done during June 27–July 10, 2020) with an estimated 22.86% IgG antibody prevalence, yielding estimated underreporting factors of 30–42 for cases. Together, these imply approximately 96–98% cases in Delhi remained unreported (July 10, 2020). Updated calculations using training data during March 15-December 31, 2020 yield estimated underreporting factor for cases at 13–22 (deaths: 3–7) on January 23, 2021, which are again consistent with the latest (fifth) round of serosurveys for Delhi (done during January 15–23, 2021) with an estimated 56.13% IgG antibody prevalence, yielding an estimated range for the underreporting factor for cases at 17–21. Together, these updated estimates imply approximately 92–96% cases in Delhi remained unreported (January 23, 2021). Such model-based estimates, updated with latest data, provide a viable alternative to repeated resource-intensive serosurveys for tracking unreported cases and deaths and gauging the true extent of the pandemic.

Download Full-text

A population-based model for predicting sentinel lymph node (SLN) status for cutaneous melanoma patients and a clinical decision rule (CDR) for sparing a SLN biopsy (SLNB).

Journal of Clinical Oncology ◽

10.1200/jco.2019.37.15_suppl.9589 ◽

2019 ◽

Vol 37 (15_suppl) ◽

pp. 9589-9589

Author(s):

Phyllis A. Gimotty ◽

Giorgos Karakousis ◽

Meghan A. Buckley ◽

DuPont Guerry

Keyword(s):

Validation Cohort ◽

False Negative ◽

Clinical Decision ◽

Mitotic Rate ◽

Population Based ◽

Multivariable Logistic Regression Model ◽

Related Factors ◽

C Statistic ◽

Definitive Surgery ◽

The One

9589 Background: Generally, a SLNB is offered to the patient whose likelihood of positivity is ≥ 5%. Using population-based cohorts, we sought to [1] develop and validate a predictive model to estimate the individualized risk (IR) of SLNB positivity (SLNBp) and its confidence interval (CI), [2] evaluate an IR-based CDR to identify patients with sufficiently low IRs to avoid SLNB, and [3] compare the performance of the CDR with that of the 2019 NCCN guideline. Methods: The learning cohort (n = 18,214; SLNBp rate = 10.7%; 2010-2014) and validation cohort (n = 3,924; SLNBp rate = 11%; 2015) included SEER patients 18-99 years old who had a SLNB as part of definitive surgery. A multivariable logistic regression model for SLNBp, including 4 AJCC related-factors (thickness, ulceration, level and mitotic rate) and age, was used to estimate the IR of SLNBp and its one-sided 95% CI. The CDR was defined using the IR and CI and then used to classify patients into 3 categories: SLNB not indicated (IR and upper limit of the one-sided CI < 5%), SLNB indicated (IR and lower limit of the one-sided CI ≥ 5%), and borderline. Results: In the learning cohort all 5 factors were significant in the multivariate model, which had a c-statistic of 0.742 (95%CI, 0.731-0.753). In the validation cohort the model c-statistic was 0.728. Based on the CDR, 21.6%, 56.9%, and 21.5% of patients would not be offered SLNB, would be offered SLNB, or would need further shared decision making. Compared to the guideline, the CDR classified more patients as “SLNB not indicated” (21.6% vs. 7.1%) and fewer as “SLNB indicated” (56.9% vs. 68.5%). Of the 16,137 SLNB negative patients, 3815 (23.6%) would not be offered SLNB based on the CDR compared to 1258 (7.8%) who would not be offered SLNB based on the guideline. The false negative rates associated with “not indicated” by the CDR and guideline were 4.6% and 1.2%, respectively. Conclusions: Use of this CDR rather than the NCCN guideline will spare more low-risk patients the expense and harms of SLNB and increase only marginally their likelihood of a false negative test (still < 5%).

Download Full-text

Incidence and clinical profiles of COVID-19 in patients with gynecological surgery: A single center descriptive study from Spain.

10.21203/rs.3.rs-31368/v1 ◽

2020 ◽

Author(s):

Reyes Oliver ◽

Gregorio Lopez-Gonzalez ◽

Alberto Galindo ◽

Carmen Alvarez-Conejo ◽

Sofia Aragon-Sanchez ◽

...

Keyword(s):

Postoperative Complications ◽

False Negative ◽

False Negative Rate ◽

Second Phase ◽

Gynecological Surgery ◽

Rt Pcr ◽

Third Phase ◽

Surgical Complexity ◽

Clinical Records

Abstract Background: The inflammatory reaction after a surgical intervention could exacerbate the course of the COVID-19. We aim to determine the rate of COVID-19 and its complications among gynecological surgeries in the context of different measures taken during the pandemic period in our department. Methods: A retrospective longitudinal observational study was conducted. Clinical records of patients who underwent gynecological surgery from March 1 st to April 10 th , 2020 were reviewed. During this period, three different approachs were made: first phase, without any screening or surgical restrictions; second phase, with presurgical epidemiological screening using a specific questionnaire; and third phase, also with presurgical SARS-COV-19 RT-PCR. During the second and third phases the surgical activity and complexity were restricted, and different workflows were established for patient with suspected/confirmed infection. After hospital discharge, telephone follow-up was performed and screening for COVID-19 was carried out. Complications from the disease were analyzed. Results : Of the 118 patients that underwent gynecological surgeries, 10 (8.5%) were perioperatively diagnosed with COVID-19. Of these patients, 8 (80%) were not pre-surgical screened for SARS-CoV-2 infection, neither clinical nor with RT-PCR. The other 2 (20%) were preoperative screened with RT-PCR, one of them with a positive test result. Screening false negative rate was 0.8%. No postoperative complications derived from COVID-19 were observed. Conclusions: The establishment of different surgical workflows, the reduction of surgical complexity, and the use of a pre-surgical screening to detect patient at SARS-CoV-2 infection risk, could reduce the postoperative complications derived from that infection and improve surgical outcomes.

Download Full-text

Seroepidemiological Study of Novel Corona Virus (CoVID-19) in Tehran, Iran

10.1101/2021.01.18.20248911 ◽

2021 ◽

Author(s):

Zeinab Tabanejad ◽

Sorena Darvish ◽

Zeinab Borjian Boroujeni ◽

Seyed Saeed Asadi ◽

Morteza Mesri ◽

...

Keyword(s):

False Negative ◽

Underlying Disease ◽

Population Based ◽

Immunological Methods ◽

Age Group ◽

Igg Antibodies ◽

Rt Pcr ◽

Igg Antibody ◽

Cross Sectional ◽

Exposed Population

AbstractA novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has now spread to all countries of the world, including Iran. Although new anti-coronavirus antibodies in patients may be identified by immunological methods with sufficient sensitivity and specificity, the conclusive diagnosis of the disease is by the molecular RT-PCR process. We used a population-based seroepidemiological survey to quantify the proportion of the exposed population with SARS-CoV-2 antibodies and evaluated whether the antibodies are a marker of total or partial immunity to the proportion of the population that remains susceptible to the virus. This cross-sectional study was conducted to investigate the seroprevalence of CoVID-19 in Tehran, the capital of Iran, between April and end of October 2020. Specimens of clotted and heparinized blood (2ml) were collected from the patients. The serum and plasma were separated and stored at − 80LJ°C until use. We examined serum anti-SARS-CoV-2 IgG and IgM antibodies from 1375 in-patients admitted to our hospitals using ELISA kits. In total, 1375 participants were enrolled in this study, and SARS-CoV-2 antibodies were detected using IgM-IgG antibody assay in 291 patients. Among the seropositive patients studied, 187 were men (64.3%), and 104 were women (35.7%) (P<0.05). The mean age of the patients was 49±8.4 years; the majority (27%) were in age group 31-40 years. Also, the lowest frequency of cases was reported in the age group of 1-10 years (P <0.05). We determined the seroprevalence of SARS-CoV-2 for IgM or IgG antibodies to be 21.2%. Diabetes mellitus was the most common underlying disease among SARS-CoV-2 patients [P=0.05; Odd Ratio=1.61(0.90-2.91)]. Conventional serological assays in SARS-CoV-2 cases, such as the enzyme-linked immunoassay (ELISA) for specific IgM and IgG antibodies, have a high-throughput advantage and minimize false-negative rates that occur with the RT-PCR method. This study determined the seroprevalence of SARS-CoV-2 antibodies to be 21%. Control of diabetes among other cases factors shall play important role in management and control of COVID-19.

Download Full-text

A case of SARS-CoV-2 carrier for 32 days with several times false negative nucleic acid tests

10.1101/2020.03.31.20045401 ◽

2020 ◽

Cited By ~ 6

Author(s):

Lingjie Song ◽

Guibao Xiao ◽

Xianqin Zhang ◽

Zhan Gao ◽

Shixia Sun ◽

...

Keyword(s):

Nucleic Acid ◽

Clinical Symptoms ◽

Early Stage ◽

Antiviral Treatment ◽

Immune Therapy ◽

False Negative ◽

Clinical Manifestations ◽

Nucleic Acid Detection ◽

Rt Pcr ◽

Nucleic Acid Tests

AbstractIn 2019, a novel coronavirus (SARS-CoV-2) was first discovered in Wuhan, Hubei, China, causing severe respiratory disease in humans, and has been identified as a public health emergency of international concern. With the spread of the virus, there are more and more false negative cases of RT-PCR nucleic acid detection in the early stage of potential infection. In this paper, we collected the epidemiological history, clinical manifestations, outcomes, laboratory results and images of a SARS-CoV-2 carrier with no significant past medical history. The patient was quarantined because of her colleague had been diagnosed. After the onset of clinical symptoms, chest CT results showed patchy ground-glass opacity (GGO) in her lungs, but it took a total of nine nucleic acid tests to confirm the diagnosis, among which the first eight RT-PCR results were negative or single-target positive. In addition to coughing up phlegm during her stay in the hospital, she did not develop chills, fever, abdominal pain, diarrhea and other clinical symptoms. Since initial antiviral treatment, the lung lesions were absorbed. But the sputum nucleic acid test was still positive. In combination with antiviral and immune therapy, the patient tested negative for the virus. Notably, SARS-CoV-2 was detected only in the lower respiratory tract samples (sputum) throughout the diagnosis and treatment period. This is a confirmed case of SARS-CoV-2 infection with common symptoms, and her diagnosis has undergone multiple false negatives, suggesting that it is difficult to identify certain carriers of the virus and that such patients may also increase the spread of the SARS-CoV-2.

Download Full-text

Real-life clinical sensitivity of SARS-CoV-2 RT-PCR test in symptomatic patients

PLoS ONE ◽

10.1371/journal.pone.0251661 ◽

2021 ◽

Vol 16 (5) ◽

pp. e0251661

Author(s):

Elisa Kortela ◽

Vesa Kirjavainen ◽

Maarit J. Ahava ◽

Suvi T. Jokiranta ◽

Anna But ◽

...

Keyword(s):

Clinical Decision Making ◽

False Negative ◽

Real Life ◽

Clinical Decision ◽

Population Based ◽

Clinical Suspicion ◽

Rt Pcr ◽

Clinical Sensitivity ◽

High Clinical Suspicion ◽

Pcr Test

Background Understanding the false negative rates of SARS-CoV-2 RT-PCR testing is pivotal for the management of the COVID-19 pandemic and it has implications for patient management. Our aim was to determine the real-life clinical sensitivity of SARS-CoV-2 RT-PCR. Methods This population-based retrospective study was conducted in March–April 2020 in the Helsinki Capital Region, Finland. Adults who were clinically suspected of SARS-CoV-2 infection and underwent SARS-CoV-2 RT-PCR testing, with sufficient data in their medical records for grading of clinical suspicion were eligible. In addition to examining the first RT-PCR test of repeat-tested individuals, we also used high clinical suspicion for COVID-19 as the reference standard for calculating the sensitivity of SARS-CoV-2 RT-PCR. Results All 1,194 inpatients (mean [SD] age, 63.2 [18.3] years; 45.2% women) admitted to COVID-19 cohort wards during the study period were included. The outpatient cohort of 1,814 individuals (mean [SD] age, 45.4 [17.2] years; 69.1% women) was sampled from epidemiological line lists by systematic quasi-random sampling. The sensitivity (95% CI) for laboratory confirmed cases (repeat-tested patients) was 85.7% (81.5–89.1%) inpatients; 95.5% (92.2–97.5%) outpatients, 89.9% (88.2–92.1%) all. When also patients that were graded as high suspicion but never tested positive were included in the denominator, the sensitivity (95% CI) was: 67.5% (62.9–71.9%) inpatients; 34.9% (31.4–38.5%) outpatients; 47.3% (44.4–50.3%) all. Conclusions The clinical sensitivity of SARS-CoV-2 RT-PCR testing was only moderate at best. The relatively high false negative rates of SARS-CoV-2 RT-PCR testing need to be accounted for in clinical decision making, epidemiological interpretations, and when using RT-PCR as a reference for other tests.

Download Full-text

Real-life clinical sensitivity of SARS-CoV-2 RT-PCR test in symptomatic patients

10.1101/2020.11.01.20223107 ◽

2020 ◽

Author(s):

Elisa Kortela ◽

Vesa Kirjavainen ◽

Maarit J. Ahava ◽

Suvi T. Jokiranta ◽

Anna But ◽

...

Keyword(s):

Clinical Decision Making ◽

False Negative ◽

Real Life ◽

Clinical Decision ◽

Population Based ◽

Clinical Suspicion ◽

Rt Pcr ◽

Clinical Sensitivity ◽

High Clinical Suspicion ◽

Pcr Test

AbstractImportanceUnderstanding the false negative rates of SARS-CoV-2 RT-PCR testing is pivotal for the management of the COVID-19 pandemic and it has practical implications for patient management in healthcare facilities.ObjectiveTo determine the real-life clinical sensitivity of SARS-CoV-2 RT-PCR testing.DesignA retrospective study on case series from 4 March – 15 April 2020.SettingA population-based study conducted in primary and tertiary care in the Helsinki Capital Region, Finland.ParticipantsAdults who were clinically suspected of SARS-CoV-2 infection and underwent SARS-CoV-2 RT-PCR testing, and who had sufficient data for grading of clinical suspicion of COVID-19 in their medical records were eligible. All 1,194 inpatients admitted to COVID-19 cohort wards during the study period were included. The outpatient cohort of 1,814 individuals was sampled from epidemiological line lists by systematic quasi-random sampling. Altogether 83 eligible outpatients (4.6%) and 3 inpatients (0.3%) were excluded due to insufficient data for grading of clinical suspicion.ExposuresHigh clinical suspicion for COVID-19 was used as the reference standard for the RT-PCR test. Patients were considered to have high clinical suspicion of COVID-19 if the physician in charge recorded the suspicion on clinical grounds, or the patient fulfilled specifically defined clinical and exposure criteria.Main measuresSensitivity of SARS-CoV-2 RT-PCR by using manually curated clinical characteristics as the gold standard.ResultsThe study population included 1,814 outpatients (mean [SD] age, 45.4 [17.2] years; 69.1% women) and 1,194 inpatients (mean [SD] age, 63.2 [18.3] years; 45.2% women). The sensitivity (95% CI) for laboratory confirmed cases, i.e. repeatedly tested patients were as follows: 85.7% (81.5–89.1%) inpatients; 95.5% (92.2–97.5%) outpatients, 89.9% (88.2–92.1%) all. When also patients that were graded as high suspicion but never tested positive were included in the denominator, the following sensitivity values (95% CI) were observed: 67.5% (62.9–71.9%) inpatients; 34.9% (31.4–38.5%) outpatients; 47.3% (44.4–50.3%) all.Conclusions and relevanceThe clinical sensitivity of SARS-CoV-2 RT-PCR testing was only moderate at best. The relatively high false negative rates of SARS-CoV-2 RT-PCR testing need to be accounted for in clinical decision making, epidemiological interpretations and when using RT-PCR as a reference for other tests.Key PointsQuestionWhat is the clinical sensitivity of SARS-CoV-2 RT-PCR test?FindingsIn this population-based retrospective study on medical records of 1,814 outpatients and 1,194 inpatients, the clinical sensitivity of SARS-CoV-2 RT-PCR was 47.3–89.9%.MeaningThe false negative rates of SARS-CoV-2 RT-PCR testing need to be accounted for in clinical decision making, epidemiological interpretations and when using RT-PCR as a reference for other tests.

Download Full-text

Multicenter evaluation of the Panbio™ COVID-19 Rapid Antigen-Detection Test for the diagnosis of SARS-CoV-2 infection

10.1101/2020.11.18.20230375 ◽

2020 ◽

Author(s):

Paloma Merino-Amador ◽

Jesús Guinea ◽

Irene Muñoz-Gallego ◽

Patricia González-Donapetry ◽

Juan-Carlos Galán ◽

...

Keyword(s):

Viral Load ◽

Clinical Symptoms ◽

False Negative ◽

Rapid Test ◽

Antigen Detection ◽

Nasopharyngeal Swab ◽

Diagnostic Strategy ◽

Rt Pcr ◽

University Hospitals ◽

Kappa Score

AbstractThe standard RT-PCR assay for COVID-19 is laborious and time-consuming, limiting the availability of testing. Rapid antigen-detection tests are faster and less expensive; however, the reliability of these tests must be validated before they can be used widely. The objective of this study was to determine the reliability of the PanbioTM COVID-19 Ag Rapid Test Device (PanbioRT) (Abbott) for SARS-CoV-2 in nasopharyngeal swab specimens. This was a prospective multicenter study in ten Spanish university hospitals of patients from hospital units with clinical symptoms or epidemiological criteria for COVID-19. Patients whose onset of symptoms or exposure was more than 7 days earlier were excluded. Two nasopharyngeal exudate samples were taken to perform the PanbioRT and a diagnostic RT-PCR test. Among the 958 patients studied, 359 (37.5%) were positive by RT-PCR and 325 (33.9%) were also positive by the PanbioRT. Agreement was 95.7% (kappa score: 0.90). All 34 false-negative PanbioRT results were in symptomatic patients, with 23.5% of them at 6–7 days since the onset of symptoms and 58.8% presenting CT >30 values for RT-PCR, indicating a low viral load. Overall sensitivity and specificity for the PanbioRT were 90.5% and 98.8%, respectively. The PanbioRT provides good clinical performance as a point-of-care test, with even more reliable results for patients with a shorter clinical course of the disease or a higher viral load. While this study has had a direct impact on the national diagnostic strategy for COVID-19 in Spain, the results must be interpreted based on the local epidemiological context.

Download Full-text

Artificial intelligence-enabled rapid diagnosis of COVID-19 patients

10.1101/2020.04.12.20062661 ◽

2020 ◽

Cited By ~ 11

Author(s):

Xueyan Mei ◽

Hao-Chih Lee ◽

Kai-yue Diao ◽

Mingqian Huang ◽

Bin Lin ◽

...

Keyword(s):

Artificial Intelligence ◽

Clinical Symptoms ◽

False Negative ◽

Clinical History ◽

Alternative Methods ◽

Ct Scans ◽

Rt Pcr ◽

Negative Results ◽

Radiologic Findings ◽

Pcr Test

AbstractFor diagnosis of COVID-19, a SARS-CoV-2 virus-specific reverse transcriptase polymerase chain reaction (RT-PCR) test is routinely used. However, this test can take up to two days to complete, serial testing may be required to rule out the possibility of false negative results, and there is currently a shortage of RT-PCR test kits, underscoring the urgent need for alternative methods for rapid and accurate diagnosis of COVID-19 patients. Chest computed tomography (CT) is a valuable component in the evaluation of patients with suspected SARS-CoV-2 infection. Nevertheless, CT alone may have limited negative predictive value for ruling out SARS-CoV-2 infection, as some patients may have normal radiologic findings at early stages of the disease. In this study, we used artificial intelligence (AI) algorithms to integrate chest CT findings with clinical symptoms, exposure history, and laboratory testing to rapidly diagnose COVID-19 positive patients. Among a total of 905 patients tested by real-time RT-PCR assay and next-generation sequencing RT-PCR, 419 (46.3%) tested positive for SARSCoV-2. In a test set of 279 patients, the AI system achieved an AUC of 0.92 and had equal sensitivity as compared to a senior thoracic radiologist. The AI system also improved the detection of RT-PCR positive COVID-19 patients who presented with normal CT scans, correctly identifying 17 of 25 (68%) patients, whereas radiologists classified all of these patients as COVID-19 negative. When CT scans and associated clinical history are available, the proposed AI system can help to rapidly diagnose COVID-19 patients.

Download Full-text