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Elsevier - PMC COVID-19 Collection logoLink to Elsevier - PMC COVID-19 Collection
. 2020 Jun 23;46:6–11. doi: 10.1016/j.semerg.2020.06.010

Predictive factors of COVID-19 in patients with negative RT-qPCR

Factores predictivos de la COVID-19 en pacientes con RT-qPCR negativa

J López de la Iglesia a, T Fernández-Villa b,, A Rivero c, A Carvajal d, E Bay Simon e, M Martínez Martínez f, H Argüello d, H Puente d, JP Fernández Vázquez g
PMCID: PMC7309836  PMID: 32651152

Abstract

Objective

To evaluate the factors associated with false negatives in RT-qPCR in patients with mild-moderate symptoms of COVID-19.

Materials and methods

This was a cross-sectional study that used a random sample of non-hospitalized patients from the primary care management division of the Healthcare Area of Leon (58 RT-qPCR-positive cases and 52 RT-qPCR-negative cases). Information regarding symptoms was collected and all patients were simultaneously tested using two rapid diagnostic tests – RDTs (Combined – cRDT and Differentiated – dRDT). The association between symptoms and SARS-CoV-2 infection was evaluated by non-conditional logistic regression, with estimation of Odds Ratio.

Results

A total of 110 subjects were studied, 52% of whom were women (mean age: 48.2 ± 11.0 years). There were 42.3% of negative RT-qPCRs that were positive in some RDTs. Fever over 38 °C (present in 35.5% of cases) and anosmia (present in 41.8%) were the symptoms most associated with SARS-CoV-2 infection, a relationship that remained statistically significant in patients with negative RT-qPCR and some positive RDT (aOR = 6.64; 95%CI = 1.33–33.13 and aOR = 19.38; 95% CI = 3.69–101.89, respectively).

Conclusions

RT-qPCR is the technique of choice in the diagnosis of SARS-CoV-2 infection, but it is not exempt from false negatives. Our results show that patients who present mild or moderate symptoms with negative RT-qPCR, but with fever and/or anosmia, should be considered as suspicious cases and should be evaluated with other diagnostic methods.

Keywords: SARS-CoV-2, RT-qPCR, Diagnosis, Fever, Anosmia

Introduction

One of the main strategies for the prevention and control of the COVID-19 pandemic is detecting and isolating of the infection sources.1 The reverse transcription quantitative polymerase chain reaction (RT-qPCR) is the technique of choice for detecting infection sources due to its high sensitivity and specificity.2 It is also a well-known and widespread technique in the clinical laboratories of our hospitals.3 This method, however, is not free of false negatives, the most frequent causes of which being theinadequate sample collection, delays in transport, labeling errors and the poor virus elimination in the patient.4, 5 For these reasons, in the face of clinical suspicion, a negative RT-qPCR result must be contrasted against other diagnostics tests.4

The aim of this article is to understand the factors associated with false negatives in RT-qPCR in patients with mild-moderate symptoms of COVID-19.

Material and methods

Study design

A cross-sectional study was carried out. A random selection was made of 58 non-hospitalized patients with positive RT-qPCR and 52 negative RT-qPCR. Patients were selected from the register of confirmed or suspected COVID-19 cases from the primary care management of the Healthcare Area of Leon. More than 14 days had passed in all patients since the beginning of the symptoms.

Procedure

Participation in the study was voluntary. The invitation to participate in the study was extended via a telephone call, in which the participants were summoned for a biological sample and information collection. All protection regulations were followed during the collection process and the project was approved by the Ethics Committee of the Healthcare Area of León and the Bierzo (reference: 2073). After signing an informed consent, each participant completed a brief ad hoc questionnaire that collected information on socio-demographic data, symptoms, date of onset and end of symptoms and date of the RT-qPCR.

All patients were tested simultaneously with two RDTs6:

  • -

    Combined (c-RDT) (one band): Wondfo® SARS-COV-2 Antibody test (Lateral Flow Method) of GUANGZHOU WONDFO BIOTECH CO LTD,

  • -

    Differentiated (d-RDT) (two bands): Allowing differentiation between IgG and IgM. All Test® 2019-nCoV IgG/IgM Rapid Test Casette of HANGZHOU ALL TEST BIOTECH CO LTD.

Both tests were performed by two nurses using a finger-stick whole blood sample. The first test jointly determines the presence of IgM and IgG, while the second test makes a differentiated measurement of both antibody subtypes. The results of the tests were read 10–15 min after they were carried out.

We considered as a case of COVID19 those patients with a positive result to at least one of the RDTs or RT-qPCR.

Statistical analysis

Central and dispersion measures were calculated in quantitative variables (mean and standard deviation (SD)) and frequencies with their 95% confidence intervals in qualitative variables. Using non-conditional logistic regression models, adjusted by age and sex at minimum, we obtained the Odds Ratio (aOR) to be considered COVID-19 case, performing stratified analysis according to the results of the RDTs and the RT-qPCR. The characteristics of those patients with negative RT-qPCR and positive PDR were examined. All analyses were performed with the STATA 15 statistical package.7

Results

A total of 110 subjects were studied, of whom 51.8% were women. The age range was between 22 and 78 years, with a mean of 48.2 ± 11.0 years. The number of days from the onset of symptoms to the performance of the RDTs ranged from 14 to 40 days, with a median of 26 days.

Of the 110 patients, 80 (72.7%) had either RT-qPCR or a positive RDT for SARS-CoV-2 (20 were IgM positive, 64 were IgG positive, 64 were IgM or IgG positive, 46 were combined, 65 were RDT positive, and 58 were RT-qPCR positive). Of the 52 with negative RT-qPCR, 22 (42.3%) were positive for some RDT; there were 14 positives for the two RDTs and 8 only for RDTd. (Fig. 1 )

Figure 1.

Figure 1

Results obtained in the different diagnostic tests evaluated.

Table 1 shows the distribution of symptoms and their association with being a COVID-19 case. A statistically significant association with fever, anosmia, ageusia, myalgia and anorexia were observed in the model adjusted for age and sex. Adjusting for age, sex and the signs and symptoms statistically associated with COVID-19, the significant association with anosmia (aOR = 20.39; 95%CI = 4.74–87.73) and fever (aOR = 4.33; 95%CI = 1.24–15.11) was maintained.

Table 1.

Risk of having at least one positive test according to different signs and symptoms.

Signs or symptoms N n % aORa 95% CI
Cough
 No 34 27 79.4 1
 Yes 76 53 69.7 0.82 0.29 2.30



Expectoration
 No 74 54 73.0 1
 Yes 35 25 71.4 0.95 0.37 2.42



Fever (<38 °C)
 No 39 27 69.2 1
 Yes 71 53 74.7 1.47 0.59 3.66



Fever (≥ 38 °C)
 No 71 46 64.8 1
 Yes 39 34 87.2 4.14 1.35 12.72



Shaking chills
 No 49 35 71.4 1
 Yes 61 45 73.8 1.24 0.51 3.02



Dyspnea
 No 64 46 71.9 1
 Yes 45 33 73.3 1.94 0.73 5.15



Chest pain
 No 71 54 76.1 1
 Yes 39 26 66.7 0.83 0.33 2.07



Headache
 No 45 32 71.1 1
 Yes 65 48 73.9 1.75 0.68 4.51



Nausea
 No 90 65 72.2 1
 Yes 20 15 75.0 1.66 0.51 5.41
Diarrhea
 No 62 42 67.7 1
 Yes 47 37 78.7 2.34 0.90 6.04



Anosmia
No 64 37 57.8 1
Yes 46 43 93.5 19.75 4.76 82.00



Ageusia
 No 59 34 57.6 1
 Yes 51 46 90.2 9.92 3.09 31.87



Sore throat
 No 73 54 74.0 1
 Yes 37 26 70.3 1.00 0.40 2.52



Asthenia
 No 28 18 64.3 1
 Yes 82 62 75.6 2.00 0.74 5.42



Myalgia
 No 53 35 66.0 1
 Yes 56 44 78.6 2.63 1.02 6.72



Anorexia
 No 69 46 66.7 1
 Yes 41 34 82.9 3.28 1.17 9.16
a

aOR: adjusted odds ratio by sex and age.

Fig. 2 shows that all the patients with fever and anosmia were positive in some test and in the case of patients with negative RT-qPCR but positive in some RDT, more than 80% (18/22) had either fever or anosmia or both.

Figure 2.

Figure 2

Presence or absence of fever and/or anosmia according to diagnostic test results.

Table 2 shows how anosmia (aOR = 19.38) and the presence of fever (aOR = 6.64) are strongly and significantly associated with having COVID-19 in subjects who previously tested RT-qPCR-negative.

Table 2.

Distribution of factors associated with being a COVID-19 case in patients with negative RT-qPCR or RDTs.

RT-qPCR negative (N = 52)
N RDTs+ % aOR 95% CI p
Sex
 Women 18 9 50.0 1 0.455
 Men 34 13 38.2 0.56 0.12 2.56



Fever (≥ 38 °C)
 No 37 12 32.4 1 0.021
 Yes 15 10 66.7 6.64 1.33 33.13



Anosmia
 No 36 9 25.0 1 <0.001
 Si 16 13 81.3 19.38 3.69 101.89



Age (years) 46.1 ± 11.3 vs 47.6 ± 8.9 1.04 0.96 1.12 0.319

Discussion

The results of our study reflect that 42.3% of respondents with negative RT-qPCR were positive for some RDT. The symptoms most commonly associated with SARS-CoV-2 infection were fever over 38 °C (present in 35.5% of cases) and anosmia (present in 41.8%), a relationship that remained significant in individuals with negative RT-qPCR and some positive RDT (aOR = 6.64; 95%CI = 1.33–33.13 and aOR = 19.38; 95% CI = 3.69–101.89 respectively).

RT-qPCR is the most widely used technique in the diagnosis of SARS-CoV-2 infection, given its high reliability.3 However, it is not exempt from false negatives, which may be due to tests with fewer genes detected, mild symptoms or very early stages of the disease, upper respiratory tract samples, denaturation of the materials used and/or delay in transport or processing of the sample.4, 5

Our data show that 42.3% of the subjects analyzed were classified as healthy according to the technique of choice (RT-qPCR), presenting infection after the results obtained in the RDTs. The Spanish Society of Intensive and Critical Medicine and Coronary Units (SEMICYUC) warned that false negatives by RT-qPCR can reach 30% in hospitalized patients, referring to a study carried out by Yang et al. in China.8, 9 These results highlight the need for caution in diagnosis, especially in cases of negative RT-qPCR and high clinical suspicion.

With regard to symptoms associated with SARS-CoV-2 infection, fever and anosmia were significant in the false negatives. These symptoms associated with the infection were not surprising, given that from the beginning of the pandemic, fever, cough and difficulty breathing were the warning symptoms. According to data published in a recent review, fever is present in 83–98% of cases, but up to 17% of patients may have afebrile illness.5 The Centers for Disease Control and Prevention (CDC) has expanded the list of symptoms associated with the disease to include chills, muscle pain, sore throat, and recent loss of taste or smell.10, 11, 12 This last symptom, anosmia, is emerging strongly among the cases detected worldwide, having been described by several studies with a prevalence between 33 and 86%.13, 14 Despite not being present in all cases, these are very characteristic symptoms that can arise in the early stage of the disease and should be taken into account as a clinical suspicion.

The results obtained in this study must be interpreted with caution, given that the main limitations are the descriptive nature of the study and the small sample size. However, it is one of the first research studies in Spain to highlight the factors associated with false negatives in the test of choice in the diagnosis of COVID-19, to ensure the diagnosis of the diasease.

Conclusion

The rapid spread of the COVID-19 pandemic requires the swift generation of knowledge to combat this disease. Our results reflect how patients with fever and anosmia and negative RT-qPCR should be considered as suspected COVID-19 cases in clinical practice, given the percentage of false negatives that this test of choice is presenting. Furthermore, it highlights the need to perform a combination of tests, such as the use of RDTs, to ensure the diagnosis of the diasease.

Funding

This research has not received specific support from public sector agencies, the commercial sector or non-profit organizations.

Conflict of interest

The authors declare no conflict of interest.

Acknowledgements

The authors would like to thank all patients for their participation in this study who have voluntarily agreed to collaborate in the evaluation of diagnostic techniques against COVID-19. Thank you to the primary care management division of the Healthcare Area of Leon and the University of Leon also, because their collaboration has been crucial in developing this study.

References


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