scholarly journals 370. Examining the Relationship Between SARS-CoV-2 PCR Cycle Threshold, Disease Severity and Epidemiologic Trends

2021 ◽  
Vol 8 (Supplement_1) ◽  
pp. S287-S287
Author(s):  
Jessica Penney ◽  
Amanda Jung ◽  
Benjamin Koethe ◽  
Shira Doron
Keyword(s):  
Logistic Regression ◽  
Disease Severity ◽  
Symptom Onset ◽  
Temporal Trends ◽  
Clinical Severity ◽  
Cycle Threshold ◽  
Inflammatory Phase ◽  
Significant Difference ◽  
Mean Cycle ◽  
The Relationship

Abstract Background Real-time reverse transcriptase PCR (rRT-PCR) has become the primary method for detection of SARS-CoV-2. Specific measurements of cycle threshold (Ct) values can give an estimate of viral load. Previous studies have shown temporal trends in Ct values, which could be used to predict the phase of the pandemic. This study’s goal was to examine the relationship between Ct and disease severity, as well as Ct trends. Methods Testing was performed using the Abbott M2000 SARS-CoV-2 assay. Data was collected for 262 SARS-CoV-2 positive patients from March-May 2020. Kruskal-Wallis testing was performed to determine differences in median Ct based on age, gender, race and ethnicity. To determine relationship between symptom onset and clinical severity with Ct, linear and logistic regression were performed. Results The majority of the patients had mild to moderate disease. Average time since symptom onset was 5.9 days, and 92% were symptomatic. Figure 1 demonstrates the distribution of Ct by disease severity at time of testing. There was no significant difference in cycle threshold by sex, age, race or ethnicity. Figure 2 shows weekly mean cycle threshold by total new cases in Massachusetts to reflect temporal trend of Ct and cases. In the multivariable linear regression model, Ct increased with days since symptom onset (P< 0.001). Cycle threshold was inversely associated with disease severity in multivariable logistic regression though (OR 1.06, 95%CI 1.01-1.11, p=0.03), even when controlling for time since symptom onset. Figure 1. Distribution of Ct by disease severity at time of SARS-CoV-2 testing Boxplot demonstrating distribution of Ct by disease severity at time of testing. There was no significant difference between groups. Figure 2. Weekly Mean Cycle Threshold by Total New MA Cases Line represents mean Ct over time period included in this study overlaid on total new cases in Massachusetts. Lower Ct were seen in the course as cases were increasing which peaked as cases stabilized. Conclusion Cycle threshold increased with time since symptom onset, consistent with prior data showing increasing Ct from time since infection due to decreasing viral replication. This study showed an inverse relationship between cycle threshold and disease severity, which differs from previous studies which demonstrated higher odds of progression to severe disease and mortality with lower Ct. This finding may reflect the disease severity associated with the secondary inflammatory phase of SARS-CoV-2 seen later in the disease course, although there was only moderate correlation between Ct and time since symptom onset. Further research is needed to better understand the role of Ct in predicting clinical severity of SARS-CoV-2 infections. Disclosures All Authors: No reported disclosures

scholarly journals Treated hydrocephalus in individuals with myelomeningocele in the National Spina Bifida Patient Registry

2018 ◽  
Vol 22 (6) ◽  
pp. 646-651 ◽  
Author(s):  
Irene Kim ◽  
Betsy Hopson ◽  
Inmaculada Aban ◽  
Elias B. Rizk ◽  
Mark S. Dias ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Spina Bifida ◽  
Temporal Trends ◽  
Patient Registry ◽  
Insufficient Data ◽  
Multivariate Logistic Regression ◽  
Significant Difference ◽  
Lesion Level ◽  
Hydrocephalus Treatment ◽  
The Relationship

OBJECTIVEAlthough the majority of patients with myelomeningocele have hydrocephalus, reported rates of hydrocephalus treatment vary widely. The purpose of this study was to determine the rate of surgical treatment for hydrocephalus in patients with myelomeningocele in the National Spina Bifida Patient Registry (NSBPR). In addition, the authors explored the variation in shunting rates across NSBPR institutions, examined the relationship between hydrocephalus, and the functional lesion level of the myelomeningocele, and evaluated for temporal trends in rates of treated hydrocephalus.METHODSThe authors queried the NSBPR to identify all patients with myelomeningoceles. Individuals were identified as having been treated for hydrocephalus if they had undergone at least 1 hydrocephalus-related operation. For each participating NSBPR institution, the authors calculated the proportion of patients with treated hydrocephalus who were enrolled at that site. Logistic regression was performed to analyze the relationship between hydrocephalus and the functional lesion level of the myelomeningocele and to compare the rate of treated hydrocephalus in children born before 2005 with those born in 2005 or later.RESULTSA total of 4448 patients with myelomeningocele were identified from 26 institutions, of whom 3558 patients (79.99%) had undergone at least 1 hydrocephalus-related operation. The rate of treated hydrocephalus ranged from 72% to 96% among institutions enrolling more than 10 patients. This difference in treatment rates between centers was statistically significant (p < 0.001). Insufficient data were available in the NSBPR to analyze reasons for the different rates of hydrocephalus treatment between sites. Multivariate logistic regression demonstrated that more rostral functional lesion levels were associated with higher rates of treated hydrocephalus (p < 0.001) but demonstrated no significant difference in hydrocephalus treatment rates between children born before versus after 2005.CONCLUSIONSThe rate of hydrocephalus treatment in patients with myelomeningocele in the NSBPR is 79.99%, which is consistent with the rates in previously published literature. The authors’ data demonstrate a clear association between functional lesion level of the myelomeningocele and the need for hydrocephalus treatment.

scholarly journals A model based on CT radiomic features for predicting RT-PCR becoming negative in coronavirus disease 2019 (COVID-19) patients

2020 ◽  
Author(s):  
Quan Cai ◽  
Siyao Du ◽  
Si Gao ◽  
Guoliang Huang ◽  
Zheng Zhang ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Symptom Onset ◽  
Clinical Characteristics ◽  
Recovery Period ◽  
Clinical Treatment ◽  
Time Interval ◽  
Negative Group ◽  
Rt Pcr ◽  
Model Based ◽  
Significant Difference

Abstract Background: Coronavirus disease 2019 (COVID-19) has emerged as a global pandemic. According to the diagnosis and treatment guidelines of China, negative reverse transcription-polymerase chain reaction (RT-PCR) is the key criterion for discharging COVID-19 patients. However, repeated RT-PCR tests lead to medical waste and prolonged hospital stays for COVID-19 patients during the recovery period. Our purpose is to assess a model based on chest computed tomography (CT) radiomic features and clinical characteristics to predict RT-PCR negativity during clinical treatment. Methods: From February 10 to March 10, 2020, 203 mild COVID-19 patients in Fangcang Shelter Hospital were retrospectively included (training: n=141; testing: n=62), and clinical characteristics were collected. Lung abnormalities on chest CT images were segmented with a deep learning algorithm. CT quantitative features and radiomic features were automatically extracted. Clinical characteristics and CT quantitative features were compared between RT-PCR-negative and RT-PCR-positive groups. Univariate logistic regression and Spearman correlation analyses identified the strongest features associated with RT-PCR negativity, and a multivariate logistic regression model was established. The diagnostic performance was evaluated for both cohorts. Results: The RT-PCR-negative group had a longer time interval from symptom onset to CT exams than the RT-PCR-positive group (median 23 vs. 16 days, p<0.001). There was no significant difference in the other clinical characteristics or CT quantitative features. In addition to the time interval from symptom onset to CT exams, nine CT radiomic features were selected for the model. ROC curve analysis revealed AUCs of 0.811 and 0.812 for differentiating the RT-PCR-negative group, with sensitivity/specificity of 0.765/0.625 and 0.784/0.600 in the training and testing datasets, respectively. Conclusion: The model combining CT radiomic features and clinical data helped predict RT-PCR negativity during clinical treatment, indicating the proper time for RT-PCR retesting.

scholarly journals A model based on CT radiomic features for predicting RT-PCR becoming negative in coronavirus disease 2019 (COVID-19) patients

2020 ◽  
Author(s):  
Quan Cai ◽  
Siyao Du ◽  
Si Gao ◽  
Guoliang Huang ◽  
Zheng Zhang ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Symptom Onset ◽  
Clinical Characteristics ◽  
Recovery Period ◽  
Clinical Treatment ◽  
Time Interval ◽  
Negative Group ◽  
Rt Pcr ◽  
Model Based ◽  
Significant Difference

Abstract Background: Coronavirus disease 2019 (COVID-19) has emerged as a global pandemic. According to the diagnosis and treatment guidelines of China, negative reverse transcription-polymerase chain reaction (RT-PCR) is the key criterion for discharging COVID-19 patients. However, repeated RT-PCR tests lead to medical waste and prolonged hospital stays for COVID-19 patients during the recovery period. Our purpose is to assess a model based on chest computed tomography (CT) radiomic features and clinical characteristics to predict RT-PCR negativity during clinical treatment.Methods: From February 10 to March 10, 2020, 203 mild COVID-19 patients in Fangcang Shelter Hospital were retrospectively included (training: n=141; testing: n=62), and clinical characteristics were collected. Lung abnormalities on chest CT images were segmented with a deep learning algorithm. CT quantitative features and radiomic features were automatically extracted. Clinical characteristics and CT quantitative features were compared between RT-PCR-negative and RT-PCR-positive groups. Univariate logistic regression and Spearman correlation analyses identified the strongest features associated with RT-PCR negativity, and a multivariate logistic regression model was established. The diagnostic performance was evaluated for both cohorts.Results: The RT-PCR-negative group had a longer time interval from symptom onset to CT exams than the RT-PCR-positive group (median 23 vs. 16 days, p<0.001). There was no significant difference in the other clinical characteristics or CT quantitative features. In addition to the time interval from symptom onset to CT exams, nine CT radiomic features were selected for the model. ROC curve analysis revealed AUCs of 0.811 and 0.812 for differentiating the RT-PCR-negative group, with sensitivity/specificity of 0.765/0.625 and 0.784/0.600 in the training and testing datasets, respectively.Conclusion: The model combining CT radiomic features and clinical data helped predict RT-PCR negativity during clinical treatment, indicating the proper time for RT-PCR retesting.

scholarly journals Coagulopathy-related soft tissue hematoma: a comparison between computed tomography findings and clinical severity

2020 ◽  
Vol 9 (5) ◽  
pp. 205846012092326
Author(s):  
Manabu Nakayama ◽  
Kenichi Kato ◽  
Kunihiro Yoshioka ◽  
Hirotaka Sato
Keyword(s):  
Computed Tomography ◽  
Soft Tissue ◽  
Anticoagulant Therapy ◽  
Vital Signs ◽  
Coagulation Factors ◽  
Clinical Severity ◽  
Fluid Level ◽  
Ct Findings ◽  
Significant Difference ◽  
The Relationship

Background Despite increases in the incidence of coagulopathy-related soft-tissue hematoma (CRSH), the relationship between computed tomography (CT) features and clinical severity remains unclear. Purpose To retrospectively evaluate the correlation between CT findings and clinical outcomes in CRSH. Material and Methods We retrospectively reviewed data of patients diagnosed with CRSH between March 2011 and March 2018. CRSH was morphologically classified according to the presence or absence of the fluid level pattern and was also divided into groups with or without extravasation as per CT findings. These CT findings were compared with the patients’ vital signs and laboratory investigation results. Results A total of 47 patients with CRSH were examined. Fluid level and non-fluid level patterns were observed in 28 (60%) and 19 (40%) patients, respectively. Anticoagulant therapy and extravasation were significantly correlated with the fluid level pattern. However, other clinicolaboratory outcomes, including shock index, hemoglobin, hematocrit, platelet count, and coagulation factors, showed no significant difference between the two patterns. In the comparison of hematomas with and without extravasation, none of the clinicolaboratory outcomes except for anticoagulant therapy showed significant differences. Conclusion CRSH with a fluid level pattern is significantly associated with extravasation. However, extravasation, which is generally suggestive of active bleeding, does not seem to be related to clinical severity in CRSH.

scholarly journals Attenuated serum vasoactive intestinal peptide concentrations are correlated with disease severity of non-traumatic osteonecrosis of femoral head

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Ming Liu ◽  
Gan Zhao ◽  
Biao-Fang Wei
Keyword(s):  
Femoral Head ◽  
Vasoactive Intestinal Peptide ◽  
Disease Severity ◽  
Roc Curve ◽  
Radiographic Progression ◽  
Clinical Severity ◽  
Harris Hip Score ◽  
Negatively Associated ◽  
Tnf Α ◽  
Significant Difference

Abstract Background and objective The neuropeptide vasoactive intestinal peptide is a 28-amino acid neuropeptide that has been shown to stimulate bone repair and angiogenesis. The purpose of this study was to explore the potential role of serum VIP concentration in osteonecrosis of femoral trauma (ONFH). Methods One hundred five patients diagnosed with non-traumatic ONFH and 103 healthy individuals were enrolled in our study. Serum VIP, tumor necrosis factor-α (TNF-α), interluekin-1 beta (IL-1β), and macrophage colony-stimulating factor (M-CSF) levels also were detected using the commercial ELISA kit. Radiographic progression was evaluated using FICAT classification. The clinical severity of ONFH was assessed by visual analog score (VAS) and Harris Hip Score (HHS). Receiver-operating characteristic (ROC) curve was performed to test the potential diagnostic value of VIP in radiographic progression. Results The serum VIP level of patients with non-traumatic ONFH was significantly lower than that of healthy controls. There was no significant difference between the alcohol group, the steroid-induction group, and the idiopathic group. Serum VIP levels were significantly higher in ONFH patients with femoral head pre-collapse stage than collapse stage. Serum VIP levels were significantly lower. FICAT 4 non-traumatic ONFH patients had significantly lower serum concentrations of VIP when compared with FICAT 3 and FICAT 2. Moreover, serum VIP levels were significantly lower in ONFH patients with FICAT 3 than FICAT 2. Serum VIP levels were negatively related to FICAT stage. In addition, serum VIP levels were negatively associated with VAS score and positively associated with HHS score. Last, we found serum VIP levels were negatively associated with serum TNF-α and IL-1β levels. ROC curve analysis indicated that decreased serum VIP could serve as a decent biomarker with regard to the diagnosis of radiographic progression. Conclusion Attenuated serum VIP concentrations are correlated with disease severity of non-traumatic ONFH. Decreased serum VIP may serve as a potential indicator of non-traumatic ONFH.

scholarly journals A model based on CT radiomic features for predicting RT-PCR becoming negative in coronavirus disease 2019 (COVID-19) patients

2020 ◽  
Author(s):  
Quan Cai ◽  
Siyao Du ◽  
Si Gao ◽  
Guoliang Huang ◽  
Zheng Zhang ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Symptom Onset ◽  
Clinical Characteristics ◽  
Recovery Period ◽  
Clinical Treatment ◽  
Time Interval ◽  
Negative Group ◽  
Rt Pcr ◽  
Model Based ◽  
Significant Difference

Abstract Background Coronavirus disease 2019 (COVID-19) has emerged as a global pandemic. According to the diagnosis and treatment guidelines of China, negative reverse transcription-polymerase chain reaction (RT-PCR) is the key criterion for discharging COVID-19 patients. However, repeated RT-PCR assays lead to medical waste and prolonged hospital stays for COVID-19 patients during the recovery period. Our purpose is to assess a model based on CT radiomic features and clinical characteristics to predict RT-PCR negativity during clinical treatment. Methods From February 10 to March 10, 2020, 203 mild COVID-19 patients in Fangcang Shelter Hospital were retrospectively included (training: n = 141; testing: n = 62), and clinical characteristics were collected. Lung lobes and lesions on lung CT images were segmented with a deep learning algorithm. CT quantitative features and radiomic features were automatically extracted. Clinical characteristics and CT quantitative features were compared between RT-PCR-negative and RT-PCR-positive groups. Univariate logistic regression and Spearman correlation analyses identified the strongest features associated with RT-PCR negativity, and a multivariate logistic regression model was established. The diagnostic performance was evaluated for both cohorts. Results The RT-PCR-negative group had a longer time interval from symptom onset to CT exams than the RT-PCR-positive group (median 23 vs. 16 days, p < 0.001). There was no significant difference in the other clinical characteristics or CT quantitative features. In addition to the time interval from symptom onset to CT exams, nine CT radiomic features were selected for the model. ROC curve analysis revealed AUCs of 0.811 and 0.812 for differentiating the RT-PCR-negative group, with sensitivity/specificity of 0.765/0.625 and 0.784/0.600 in the training and testing datasets, respectively. Conclusions The model combining CT radiomic features and clinical data helped predict RT-PCR negativity during clinical treatment, indicating the proper time for RT-PCR retesting.

scholarly journals Evaluating the Relationship between Cycle Threshold Values and Reported COVID-19 Symptoms among Healthcare Workers

2021 ◽  
Vol 1 (S1) ◽  
pp. s19-s20
Author(s):  
Mindy Sampson ◽  
Catherine Passaretti ◽  
Jennifer Priem ◽  
Shelley Kester ◽  
Kristin Fischer ◽  
...  
Keyword(s):  
Symptom Onset ◽  
Healthcare Workers ◽  
Current Understanding ◽  
Linear Regression Models ◽  
Rt Pcr ◽  
Cycle Threshold ◽  
E Gene ◽  
Asymptomatic Individuals ◽  
Number Of Cycles ◽  
The Relationship

Background: SARS-CoV-2 detected by reverse transcription polymerase chain reaction (RT-PCR) can persist for weeks to months in some individuals. Cycle threshold (Ct) values represent the number of cycles needed to amplify viral ribonucleic acid (RNA) to reach a detectable level. As such, Ct values are inversely related to the amount of virus in a sample. As knowledge of SARS-CoV-2 viral dynamics continues to evolve, understanding the relationship between Ct values, type of symptoms, and timing of symptom onset can help determine when infected individuals are most likely to be infectious. Methods: We conducted a retrospective cohort study of 1,027 healthcare workers (HCWs) who tested positive for SARS-CoV-2 by RT-PCR from nasopharyngeal specimens between June 27, 2020, and September 21, 2020. All HCWs were interviewed within 72 hours of their diagnosis for symptom history. Due to multiple PCR platforms being in use in our facility, only 360 HCWs (35%) had Ct values available for analysis. Multivariate linear regression models examined the effect of COVID-19–related symptoms and timing of symptom onset to test on Ct values. Results: The most frequently reported symptoms were congestion (55.6%), cough (50.3%), and headache (46.7%). Other symptoms less commonly reported were fatigue (36.7%), loss of taste or smell (36.4%), fever (35.4%), muscle aches (33.3%), sore throat (27.4%), and diarrhea (26.7%). Symptomatic HCWs (88.3% of sample) had lower Ct values (ORF-1 M = 22.66, SD = 5.17; E-Gene M = 24.34, SD = 6.60) than asymptomatic individuals (ORF-1 M = 25.46, SD = 6.06; E-Gene M = 29.34, SD = 7.96). Of all symptoms measured, only presence of fever, congestion, and muscle aches predicted significantly lower Ct values. Mean Ct values decreased 2 days prior to symptom onset, were lowest the day of symptom onset, then increased in a curvilinear fashion. There were no significant 2-way interactions between symptoms and time of symptom onset to testing. Conclusions: The curvilinear pattern of Ct values over time from symptom onset are consistent with disease progression patterns and support current understanding of infectivity being highest 2 days prior to symptom onset through day 8. Presence of fever, congestion, and muscle aches are significantly correlated with lower Ct values, suggesting that these symptoms are associated with higher viral load. Although Ct values are not without limitations, our findings support the current understanding that presymptomatic and symptomatic individuals, particularly those with fever, congestion, and muscle aches, may pose higher risk of transmission to others.Funding: NoDisclosures: None

scholarly journals Association Between SARS-CoV-2 Cycle Threshold Values and Clinical Outcomes in Patients With COVID-19: A Systematic Review and Meta-analysis

2021 ◽  
Vol 8 (9) ◽  
Author(s):  
Vishal P Shah ◽  
Wigdan H Farah ◽  
James C Hill ◽  
Leslie C Hassett ◽  
Matthew J Binnicker ◽  
...  
Keyword(s):  
Systematic Review ◽  
Clinical Outcomes ◽  
Disease Severity ◽  
Meta Analysis ◽  
Severe Disease ◽  
Sample Type ◽  
Sample Collection ◽  
Cycle Threshold ◽  
Significant Difference ◽  
Polymerase Chain

Abstract Cycle threshold (CT) values are correlated with the amount of viral nucleic acid in a sample and may be obtained from some qualitative real-time polymerase chain reaction tests used for diagnosis of most patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, CT values cannot be directly compared across assays, and they must be interpreted with caution as they are influenced by sample type, timing of sample collection, and assay design. Presently, the correlation between CT values and clinical outcomes is not well understood. We conducted a systematic review and meta-analysis of published studies through April 19, 2021, that reported an association between CT values and hospitalization, disease severity, and mortality in patients ≥18 years old with SARS-CoV-2. A meta-analysis of 7 studies showed no significant difference in mean CT values between hospitalized and nonhospitalized patients. Among hospitalized patients, those with CT values &lt;25 had a high risk of more severe disease and mortality than patients with CT values &gt;30 (odds ratio [OR], 2.31; 95% CI, 1.70 to 3.13; and OR, 2.95; 95% CI, 2.19 to 3.96; respectively). The odds of increased disease severity and mortality were less pronounced in patients with CT values of 25–30 compared with &gt;30.

scholarly journals Epidemiological Correlates of Polymerase Chain Reaction Cycle Threshold Values in the Detection of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)

2020 ◽  
Author(s):  
Phillip P Salvatore ◽  
Patrick Dawson ◽  
Ashutosh Wadhwa ◽  
Elizabeth M Rabold ◽  
Sean Buono ◽  
...  
Keyword(s):  
Polymerase Chain Reaction ◽  
Severe Acute Respiratory Syndrome ◽  
Symptom Onset ◽  
Temporal Trends ◽  
Viral Rna ◽  
Chain Reaction ◽  
Cycle Threshold ◽  
Ct Value ◽  
Polymerase Chain ◽  
Epidemiological Characteristics

Abstract Background Detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has principally been performed through the use of real-time reverse-transcription polymerase chain reaction testing. Results of such tests can be reported as cycle threshold (Ct) values, which may provide semi-quantitative or indirect measurements of viral load. Previous reports have examined temporal trends in Ct values over the course of a SARS-CoV-2 infection. Methods Using testing data collected during a prospective household transmission investigation of outpatient and mild coronavirus disease 2019 cases, we examined the relationships between Ct values of the viral RNA N1 target and demographic, clinical, and epidemiological characteristics collected through participant interviews and daily symptom diaries. Results We found that Ct values are lowest (corresponding to a higher viral RNA concentration) soon after symptom onset and are significantly correlated with the time elapsed since onset (P &lt; .001); within 7 days after symptom onset, the median Ct value was 26.5, compared with a median Ct value of 35.0 occurring 21 days after onset. Ct values were significantly lower among participants under 18 years of age (P = .01) and those reporting upper respiratory symptoms at the time of sample collection (P = .001), and were higher among participants reporting no symptoms (P = .05). Conclusions These results emphasize the importance of early testing for SARS-CoV-2 among individuals with symptoms of respiratory illness, and allow cases to be identified and isolated when their viral shedding may be highest.

scholarly journals Relationship between polymorphism of receptor SCARB2 gene and clinical severity of enterovirus-71 associated hand-foot-mouth disease

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Xia Wang ◽  
Hong Liu ◽  
Ying Li ◽  
Rui Su ◽  
Yamin Liu ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Enterovirus 71 ◽  
Mouth Disease ◽  
Clinical Severity ◽  
Control Group ◽  
Case Group ◽  
Hand Foot Mouth Disease ◽  
The Relationship

Abstract Background To investigate the relationship between polymorphism of scavenger receptor class B member 2 (SCARB2) gene and clinical severity of enterovirus (EV)-71 associated hand-foot-mouth disease (HFMD). Methods Among the 100 recruited cases, 56 were in the severe HFMD group (case group) and 44 were in the general HFMD group (control group). By screening functional single nucleotide polymorphisms (SNPs) and hot SNPs, and performing SNP site optimization, some SNP sites of SCARB2 gene were selected for analysis. Genotyping was performed using a MassArray platform. PLINK software was used for statistical processing and analysis of the correlation differences between the mutant genotypes in the severe and general HFMD groups. The relationship between the SNPs and clinical severity of enterovirus (EV)-71 associated HFMD was assessed. Results 28 SNPs in SCARB2 were selected by site optimization. Then three loci were not in agreement with the minor allele frequency (MAF) in the 1000 Han Chinese in Beijing (CHB) dataset. Another three loci could not be detected. Nine loci were not suitable for further analysis (MAF < 0.01 and Hardy–Weinberg [HWE] P < 0.001). A total of 13 sites were subsequently analyzed. Through Fisher analysis, the frequency of the rs6812193 T allele was 0.134 and 0.034 in the severe and general HFMD groups, respectively (P 0.023 < 0.05, odds ratio [OR] 4.381 > 1). Logistic regression analysis of rs6812193 T alleles between the severe and general HFMD groups, respectively (P 0.023 < 0.05, OR 4.412 > 1, L95 1.210 > 1). Genotype logistic regression analysis of the rs6812193 alleles CT + TT versus CC gave an OR of 4.56 (95% confidence interval [95% CI] 1.22–17.04, P = 0.012). Conclusion The rs6812193 T allele was a susceptibility SNP for SHFMD, and the rs6812193 polymorphism might be significantly associated with the susceptibility to EV-71 infection.

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