Association between clinical symptoms and time to pharyngeal PCR negativity among mild omicron COVID-19 patients: a retrospective study

Abstract

Background

The time to pharyngeal polymerase chain reaction (PCR) negativity (TPCRN) in patients with coronavirus disease 2019 (COVID-19) is influenced by multiple factors. This study aimed to investigate the association between clinical symptoms of COVID-19 patients and TPCRN.

Methods

This retrospective study enrolled 486 participants with COVID-19, aged 18–89 years, who were admitted to Shanghai Lingang Makeshift Hospital between April 10, 2022, and May 20, 2022. Clinical data, including patient demographics, clinical symptoms, and TPCRN, were collected and analyzed.

Results

This study enrolled COVID-19 patients with a median age of 38 years, consisting of 66.05% males and 33.95% females. Stepwise (forward selection) analyses revealed a positive association between TPCRN and the clinical symptoms of throat pain (B = 1.277, 95% CI = 0.592–1.962, P < 0.001) and diarrhea (B = 1.445, 95% CI = 0.382–2.508, P = 0.008) in COVID-19 patients. Logistic regression analysis indicated that throat pain was associated with a lower 7-day negative nucleic acid conversion rate (OR = 0.584, 95% CI:0.362–0.943, P = 0.028), as was diarrhea (OR = 0.435, 95% CI:0.220–0.860, P = 0.017).

Conclusion

Our findings indicate that throat pain and diarrhea are associated with a longer time to pharyngeal polymerase chain reaction (PCR) negativity. These results may assist in identifying high-risk patients with delayed viral clearance and provide a reference for optimizing clinical management strategies for this patient population.

Clinical trial number

Not applicable.

Background

The coronavirus disease 2019 (COVID-19) pandemic has had a profound impact on global public health and economies. Its pathogen, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), primarily spreads via respiratory droplets and can cause lung infections. Despite ongoing advancements in vaccine development and treatment strategies, the diagnosis and management of COVID-19 remain challenging [1–6]. Infected individuals are categorized by illness severity: asymptomatic, mild, moderate, or severe [7]. Among these, patients with mild-to-moderate disease exhibit relatively mild clinical symptoms but still face the risk of progressing to severe disease without standardized management. Thus, controlling disease progression in this patient population is of significant clinical importance [8].

Nucleic acid testing, a key method for detecting viral genetic material, is currently the most widely recommended approach for identifying SARS-CoV-2 infection. In laboratories, RNA is extracted from patient samples, and polymerase chain reaction (PCR) technology is used to amplify and detect specific viral gene sequences. This method offers high sensitivity and specificity, enabling rapid and accurate diagnosis of COVID-19 [9–13]. During the study period (2022), in accordance with guidelines from the National Health Commission of the People’s Republic of China, discharge criteria for COVID-19 patients included two consecutive negative results of SARS-CoV-2 RNA testing (throat swab) plus improvement in clinical symptoms (e.g., symptom relief, stable vital signs) [7]. This dual criterion is a distinct measure in China’s pandemic response, designed to minimize transmission risks in healthcare facilities and communities.

Notably, the time to pharyngeal polymerase chain reaction (PCR) negativity (TPCRN) varies among individuals and is influenced by multiple factors. Existing studies have confirmed that age, sex, vaccination status, comorbidities, immune response, and lymphocyte count are associated with TPCRN [14–19], while treatment and clinical management measures also affect this indicator [20–26]. Meanwhile, as core indicators reflecting disease severity and patient experience, clinical symptoms and their association with TPCRN are crucial for optimizing treatment regimens and predicting prognosis [7, 27]. Previous studies have provided partial evidence for this: for instance, fever or nausea is associated with prolonged TPCRN [27]; patients with digestive symptoms have a significantly longer interval from symptom onset to viral clearance than those with only respiratory symptoms (P < 0.001) and a higher fecal viral positivity rate (P = 0.033) [28]; and presence of symptoms during SARS-CoV-2 infection delays viral clearance [29]. In addition, multiple studies have explored the symptom characteristics of COVID-19 patients, viral clearance dynamics, and predictive factors for TPCRN. For example, some analyzed the predictive efficacy of single symptoms for positive SARS-CoV-2 reverse transcription (RT)-PCR results and symptom persistence [30]; some focused on the association between olfactory/gustatory disorders and disease severity [31]; and others explored the diagnostic value of mild symptoms [32, 33] as well as the predictive significance of laboratory/clinical indicators [34, 35]. These findings have provided important references for understanding the disease course of COVID-19.

However, existing works have several gaps: amid the Omicron variant pandemic, studies targeting mild/asymptomatic infected individuals in China are relatively limited. Moreover, most studies did not adopt a standardized daily PCR testing protocol (with two consecutive negative results as the discharge criterion) and rarely evaluated both continuous outcome indicators (TPCRN) and categorical outcome indicators (e.g., 7-day negative nucleic acid conversion rate) simultaneously. Additionally, although some studies focused on the association between digestive symptoms and viral clearance, most concentrated on persistent viral presence in feces. Few studies have investigated the specific association between digestive symptoms and delayed viral clearance in respiratory samples.

Based on this, the primary objective of this study is to explore the association between clinical symptoms and TPCRN, as well as 7-day negative nucleic acid conversion rate, in patients infected with the Omicron variant. The secondary objective is to assess the impact of demographic factors, comorbidities, COVID-19 vaccination status, treatment modalities, and laboratory test indicators on the time to nucleic acid conversion to negative. To the best of our knowledge, during the prevalence of the Omicron strain, few studies have explored the association between specific symptoms and the time to pharyngeal PCR negativity under a standardized daily testing protocol. By focusing on mild/asymptomatic Omicron-infected individuals in China, incorporating both types of outcome indicators simultaneously, and adjusting for confounding factors (e.g., vaccination, autoimmune diseases), this study aims to clarify the clinical relevance of clinical symptoms to TPCRN and 7-day negative nucleic acid conversion rate in this population, thereby providing a scientific basis for formulating personalized treatment strategies, predicting rehabilitation outcomes, and optimizing pandemic control measures.

Methods

Study design and setting

This was a single-center retrospective observational study conducted at Shanghai Lingang Makeshift Hospital, which primarily admitted asymptomatic and mild COVID-19 patients during the study period. The study was carried out over 6 weeks (April–May 2022), coinciding with a local outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron BA.5.2 variant in Shanghai. The data collection period overlapped with the hospital’s peak admission period; however, standardized testing and data recording procedures were consistently followed to minimize bias. Clinical data were collected from hospitalized patients aged 18–89 years who were infected with the SARS-CoV-2 Omicron variant between April 10, 2022, and May 20, 2022.

The study protocol was approved by the Ethics Committee of Zhongda Hospital, Southeast University (Approval No. 2022ZDSYLL222-P01). Informed consent was waived due to the retrospective nature of the study.

Participants

Inclusion and exclusion criteria were formulated in accordance with the standards outlined in the Diagnosis and Treatment Protocol for Coronavirus Disease 2019 (Trial Version 9) issued by the National Health Commission of the People’s Republic of China [7].

The inclusion criteria were as follows: (1) Meeting the diagnostic criteria for “asymptomatic cases” or “mild cases“ [7]. “Asymptomatic cases” refer to individuals with positive COVID-19 nucleic acid test results but no clinical symptoms; “mild cases” refer to individuals with positive COVID-19 nucleic acid test results who present with symptoms (e.g., fever, cough) but no radiological evidence of pneumonia. (2) Aged 18–89 years. (3) Capable of independently completing all questionnaire items, with complete questionnaire data and no missing key information (i.e., valid questionnaires).

The exclusion criteria were: (1) Meeting the diagnostic criteria for “moderate cases”, “severe cases”, or “critically severe cases“ [7]. “Moderate cases”: Patients with clinical manifestations of COVID-19 infection and radiological evidence of pneumonia. “Severe cases”: Patients with shortness of breath and a respiratory rate (RR) ≥ 30 breaths/min; resting oxygen saturation ≤ 93% on room air (measured by pulse oximetry); arterial partial pressure of oxygen (PaO₂)/fraction of inspired oxygen (FiO₂) ≤ 300 mmHg (1 mmHg = 0.133 kPa); or progressive deterioration of clinical symptoms with obvious progression of pulmonary lesions (> 50%) on imaging within 24–48 h. “Critically severe cases”: Patients with respiratory failure requiring mechanical ventilation; patients with shock; or patients with other organ failure requiring intensive care unit (ICU) monitoring and treatment. (2) Presence of severe cardiovascular or cerebrovascular diseases. (3) Severe diseases affecting the liver, kidneys, blood, or immune system. (4) History of major surgery. (5) Administration of antiviral drugs for COVID-19 treatment during enrollment. (6) Inability to complete the standardized questionnaire, with remaining missing items after re-collection by data collectors (resulting in invalid questionnaires). (7) Aged ≥ 90 years.

Data sources and measurement

Clinical symptom assessment

Baseline respiratory and systemic clinical symptoms were collected via a standardized questionnaire upon admission; symptom changes were recorded daily until nucleic acid conversion to negative. Respiratory symptoms included fever, cough, nasal congestion, runny nose, throat pain, dry mouth, bitter taste, chest tightness, shortness of breath, itchy throat, headache; systemic symptoms included fatigue, excessive sweating, muscle pain, palpitations, loss of appetite, gastrointestinal reactions (abdominal distension, constipation, diarrhea, nausea, vomiting), insomnia.

Covariate assessment

Baseline covariates were collected using a standardized questionnaire within 24 h of admission, with supplementary laboratory and imaging data retrieved from the hospital backend system at discharge. Variables included: demographic information (age, gender, BMI calculated from height and weight); smoking status (classified as current/non-current per CDC criteria [36], former smokers merged into the non-current group due to insufficient statistical power for subgroup analysis); time from first symptom onset to first pharyngeal swab PCR positivity; comorbidities (hypertension, diabetes, CHD, COPD, autoimmune diseases, cancers, etc.); COVID-19 vaccination status (classified as unvaccinated, 1/2/3 doses); medication history (only Chinese patent medicines or antipyretics for cough/fever management [7], no antiviral treatment); laboratory data (complete blood count with lymphocyte count, high-sensitivity CRP, liver and kidney function) and SpO2 test results, chest CT findings (if performed).

For statistical analysis, continuous covariates (age, BMI, CRP, lymphocyte count, time from symptom onset to first PCR positivity) were retained as continuous in regression models and dichotomized for univariate tests at the cut-offs of 60 years, 28 kg/m²(per the Chinese guidelines defining ≥ 28 kg/m² as the obesity threshold for Chinese adults) [37, 38], 10 mg/L [39–41], 0.8 × 10⁹/L [41, 42], and 0 days, respectively.

Outcome assessment

Outcome variables were time to pharyngeal PCR negativity (TPCRN) and 7-day negative nucleic acid conversion rate, defined in line with China’s Diagnosis and Treatment Protocol for Coronavirus Disease 2019 (9th Edition) (2022) [7]. TPCRN was the interval from the first positive pharyngeal swab PCR test to the first two consecutive negative results; the 7-day negative nucleic acid conversion rate was the proportion of patients with pharyngeal PCR negativity within 7 days [7].

Pharyngeal swabs were collected daily by trained nurses (sampling posterior pharyngeal wall and bilateral tonsillar fossae, avoiding tongue/teeth contact) and tested using the Da An Gene RT-PCR kit (Guangzhou, China; sensitivity 100 copies/mL, specificity 99.9%, false-positive rate ≤ 0.1%, false-negative rate ≤ 2.3%, primarily for low viral load samples). Per the kit’s 2022 standard operating procedures [43], a negative result required two consecutive tests with a cycle threshold (Ct) value > 35, with nucleic acid test results recorded daily.

Bias assessment

Standardized training

All physicians and nurses involved in data collection and sample handling received pre-study training. This training ensured uniformity in questionnaire administration, symptom recording, and pharyngeal swab collection, thereby minimizing inter-observer bias.

Missing data handling

Initially, 544 COVID-19 patients met the inclusion criteria (identified as potential participants). Among these, 14 were excluded due to incomplete data, 38 due to undetermined TPCRN, and 6 due to age restrictions. This resulted in a final study cohort of 486 patients. The exclusion rate for incomplete data was 10.66%, which was deemed acceptable for reducing bias associated with missing data.

Sample size justification

Based on clinical experience and preliminary experiments, we hypothesized that the 7-day negative nucleic acid conversion rate is 30% lower in patients with throat pain compared to those without throat pain, OR = 0.7. The 7-day conversion rate for patients without throat pain is approximately 70%. Among COVID-19 patients, the proportion of those with throat pain is roughly 50%. With α set at 0.05 and statistical power (1-β) set at 90%, the minimum required sample size estimated using PASS 15 software is 246 participants. Considering that we also need to explore the impact of other accompanying symptoms on the 7-day conversion rate, we expanded the sample size by 1.5 times, resulting in a requirement of at least 369 cases. The final sample size included in our study meets this minimum requirement.

Statistical analysis

All statistical analyses were performed using SPSS 29.0 software. For testing data distribution, the characteristics of continuous data were determined via normality tests (Q-Q plot method): Q-Q plots were generated, and conformity to a normal distribution was assessed by observing whether data points approximately aligned with the theoretical normal distribution reference line. All continuous variables included in the analysis were normally distributed, so they were described as mean ± standard deviation (x̄ ± s); categorical variables were expressed as frequencies (%).

Analysis of clinical symptoms and TPCRN

Given that TPCRN is a normally distributed continuous variable, this study adopted an analytical approach combining parametric tests and stepwise regression analysis(forward selection method): Initially, t-tests were conducted to screen out variables that had a statistical association with TPCRN. Subsequently, variables with P < 0.05 in the univariate analysis and those with P ≥ 0.05 but of practical clinical significance, along with essential confounding variables including age, gender, BMI, smoking status, underlying diseases, medication status, vaccination status, time from first symptom onset to first pharyngeal PCR positivity (S-to-PCR), CRP, and lymphocyte count, were collectively incorporated to form a candidate variable pool. With TPCRN as the dependent variable, stepwise regression analysis was performed using the forward selection method (inclusion criterion: P ≤ 0.05; exclusion criterion: P ≥ 0.10). During the analysis process, collinearity diagnosis (ensuring the variance inflation factor [VIF] < 5) and outlier handling were simultaneously carried out to guarantee the robustness of the model.

Analysis of clinical symptoms and 7-day negative nucleic acid conversion rate

In exploring the association between patients' clinical symptoms and the 7-day nucleic acid negative conversion rate, this study adopted an analytical framework combining univariate screening and binary logistic regression. First, Pearson’s chi-square test was applied to screen for variables statistically associated with the 7-day conversion outcome. All variables with P<0.05 in univariate analyses, variables with P≥0.05 but with clear clinical relevance, and key confounders (age, gender, BMI, smoking status, underlying diseases, medication use, vaccination status,S-to-PCR, CRP and lymphocyte count) were pooled to establish a candidate variable set. The 7-day nucleic acid conversion status was defined as the dichotomous dependent variable, coded as 1 for conversion within 7 days and 0 for conversion after 7 days in the regression model.

Results

As of May 20, 2022, 544 COVID-19 patients were initially identified as potentially eligible for the study. However, 38 patients were excluded because their time to nucleic acid conversion to negative could not be determined (due to transfer to other makeshift or designated hospitals), 6 due to age restrictions, and 14 due to incomplete data. Consequently, 486 patients were included in the final analysis.

Demographic characteristics

The 486 participants were infected with the SARS-CoV-2 Omicron variant. Key demographic characteristics were as follows: 66.05% were male, with a median age of 38 years; 11.32% were asymptomatic, and 88.68% were symptomatic; the median BMI was 23.34. Regarding lifestyle and comorbidities: 153 patients (31.5%) had a smoking history, and 333 (68.52%) had no smoking history; comorbidities included hypertension (50 patients, 10.29%), diabetes (20 patients, 4.12%), CHD (15 patients, 3.09%), COPD (13 patients, 2.67%), autoimmune diseases (11 patients, 2.26%), and cancer (8 patients, 1.65%). Additionally, 454 patients (93.42%) had received COVID-19 vaccination, 219(45.06%) had received treatment with Chinese patent medicines， and 79 (16.26%) had used antipyretics (Table 1).

Table 1.

Baseline characteristics of patients with COVID-19 according to TPCRN

Variables		No. of cases (%)	TPCRN (d)	T	P
Sex	Men	321 (66.05%)	6.61 ± 3.94	0.22	0.829
	Women	165 (33.95%)	6.53 ± 3.28
Age	< 60 years	445 (91.56%)	6.53 ± 3.72	-1.01	0.313
	≥ 60 years	41 (8.44%)	7.15 ± 3.82
BMI	< 28 kg/m2	423 (87.04%)	6.59 ± 3.82	0.140	0.829
	≥ 28 kg/m2	63 (12.96%)	6.52 ± 3.07
Smoking	Non-current smokers	333 (68.52%)	6.75 ± 3.83	1.450	0.147
	Current smokers	153 (31.48%)	6.22 ± 3.48
Hypertension	Without	436 (89.71%)	6.48 ± 3.76	-1.801	0.072
	With	50 (10.29%)	7.48 ± 3.36
Diabetes	Without	466 (95.88%)	6.53 ± 3.74	-1.432	0.153
	With	20 (4.12%)	7.75 ± 3.40
CHD	Without	471 (96.91%)	6.59 ± 3.76	0.403	0.687
	With	15 (3.09%)	6.20 ± 2.60
COPD	Without	473 (97.33%)	6.55 ± 3.69	-0.872	0.400
	With	13 (2.67%)	7.77 ± 5.00
Autoimmune diseases	Without	475 (97.74%)	6.51 ± 3.65	-2.683	0.008
	With	11 (2.26%)	9.55 ± 5.85
Cancer	Without	478 (98.35%)	6.58 ± 3.74	-0.128	0.898
	With	8 (1.65%)	6.75 ± 3.06
Vaccination	Without	32 (6.58%)	7.41 ± 3.97	1.294	0.196
	With	454 (93.42%)	6.53 ± 3.71
Chinese patent medicine	Without	267(54.94%)	6.29 ± 4.17	-1.918	0.056
	With	219 (45.06%)	6.93 ± 3.10
Antipyretic	Without	407 (83.74%)	6.56 ± 3.82	-0.362	0.717
	With	79 (16.26%)	6.72 ± 3.25
CRP	≥ 10 mg/L	306 (62.96%)	6.75 ± 3.90	-1.256	0.210
	<10 mg/L	180 (37.04%)	6.31 ± 3.42
Lymphocyte count	≥ 0.8 × 10⁹/L	454 (93.42%)	6.61 ± 3.81	-0.891	0.378
	<0.8 × 10⁹/L	32 (6.58%)	6.22 ± 2.25
S-to-PCR	>0 day	186 (38.27%)	6.21 ± 3.37	1.738	0.083
	0 day	300 (61.73%)	6.81 ± 3.93
Fever	Without	264 (54.32%)	6.33 ± 3.91	-1.67	0.095
	With	222 (45.68%)	6.89 ± 3.47
Weakness	Without	319 (65.64%)	6.48 ± 3.96	-0.86	0.392
	With	167 (34.36%)	6.78 ± 3.23
Sweatiness	Without	312 (64.20%)	6.49 ± 3.97	-0.74	0.457
	With	174 (35.80%)	6.75 ± 3.24
Cough	Without	180 (37.04%)	6.19 ± 4.40	-1.77	0.077
	With	306 (62.96%)	6.81 ± 3.25
Itchy throat	Without	333 (68.52%)	6.40 ± 3.75	-1.59	0.112
	With	153 (31.48%)	6.98 ± 3.65
Throat pain	Without	321 (66.05%)	6.26 ± 3.50	-4.268	< 0.001
	With	165 (33.95%)	7.21 ± 4.07
Oral bitterness	Without	390 (80.25%)	6.56 ± 3.83	-0.30	0.762
	With	96 (19.75%)	6.69 ± 3.28
Dry mouth	Without	380 (78.19%)	6.47 ± 3.80	-1.145	0.253
	With	106 (21.81%)	6.99 ± 3.44
Chest distress and shortness of breath	Without	423 (87.04%)	6.53 ± 3.84	-0.84	0.401
	With	63 (12.96%)	6.95 ± 2.85
Inappetence	Without	403 (82.92%)	6.56 ± 3.84	-0.34	0.735
	With	83 (17.08%)	6.71 ± 3.13
Abdominal distension	Without	466 (95.88%)	6.55 ± 3.77	-0.88	0.381
	With	20 (4.12%)	7.30 ± 2.41
Constipation	Without	446 (91.77%)	6.56 ± 3.74	-0.43	0.670
	With	40 (8.23%)	6.83 ± 3.59
Diarrhea	Without	435 (89.51%)	6.49 ± 3.80	-1.64	0.102
	With	51 (10.49%)	7.39 ± 2.89
Palpitation	Without	470 (96.71%)	6.58 ± 3.71	-0.18	0.857
	With	16 (3.29%)	6.75 ± 4.31
Nasal obstruction	Without	334 (68.72%)	6.49 ± 3.98	-0.85	0.399
	With	152 (31.28%)	6.80 ± 3.11
Rhinorrhea	Without	358 (73.66%)	6.55 ± 3.95	-0.34	0.736
	With	128 (26.34%)	6.68 ± 3.03
Sleep disorders	Without	418 (86.01%)	6.52 ± 3.83	-0.99	0.322
	With	68 (13.99%)	7.00 ± 3.01
Nausea and vomiting	Without	457 (94.03%)	6.51 ± 3.75	-1.75	0.080
	With	29 (5.97%)	7.76 ± 3.23
Muscular soreness	Without	365 (75.10%)	6.39 ± 3.45	-1.99	0.047
	With	121 (24.90%)	7.17 ± 4.42
Headache	Without	328 (67.49%)	6.50 ± 3.98	0.69	0.489
	With	158 (32.51%)	6.75 ± 3.14
Asymptomatic	Symptomatic	431 (88.68%)	6.70 ± 3.61	1.57	0.121
	Asymptomatic	55 (11.32%)	5.71 ± 4.47

Continuous variables are presented as mean ± standard deviation (SD). Group differences were compared using Student’s t test

Abbreviations: TPCRN, time to pharyngeal PCR negativity; BMI, body mass index;CHD, Coronary Heart Disease; COPD, chronic obstructive pulmonary disease (COPD); CRP, C-reactive protein; S-to-PCR, time from first symptom onset to first PCR positivity

Association between clinical symptoms and TPCRN in COVID-19 patients

Univariate t-tests showed that patients with autoimmune diseases (p = 0.008), throat pain (p < 0.001), or muscle soreness (p = 0.047) had a longer TPCRN than those without these conditions (Table 1). This statistical approach was justified by a prior normality test (Q-Q plot method), which supported that all continuous data related to clinical symptoms included in the analysis conformed to a normal distribution.

After adjusting for confounding factors, stepwise regression analysis (forward selection) revealed that throat pain (B = 1.277, 95% CI = 0.592–1.962, p < 0.001) and diarrhea (B = 1.445, 95% CI = 0.382–2.508, p = 0.008) were positively associated with TPCRN; additionally, autoimmune diseases (B = 3.128, 95% CI = 0.985–5.270, p = 0.004) and CRP (B = 0.037, 95% CI = 0.004–0.070, p = 0.027) also showed positive associations with TPCRN, whereas time from first symptom onset to first pharyngeal PCR positivity (B = -0.194, 95% CI = -0.293 to -0.095, p < 0.001) was negatively associated with TPCRN (Table 2; Fig. 1).

Table 2.

Stepwise linear regression analysis of factors associated with time to pharyngeal PCR negativity in patients with COVID-19

Variables	B	95% CI		P
Intercept	5.600	4.953	6.247	< 0.001
Autoimmune diseases	3.128	0.985	5.270	0.004
CRP (mg/L)	0.037	0.004	0.070	0.027
S-to-PCR (d)	-0.194	-0.293	-0.095	< 0.001
Throat pain	1.277	0.592	1.962	< 0.001
Diarrhea	1.445	0.382	2.508	0.008

Results are presented as regression coefficients (B), 95% confidence intervals (CI), and P values from the final multivariable linear regression model. The dependent variable was TPCRN. The model was adjusted for demographic characteristics, comorbidities, vaccination status, medication use, laboratory parameters, and selected clinical symptoms

Abbreviations: S-to-PCR, time from first symptom onset to first PCR positivity; CHD, coronary heart disease; COPD, chronic obstructive pulmonary disease (COPD); CRP, C-reactive protein

Fig. 1.

Association between clinical symptoms and time to pharyngeal PCR negativity (TPCRN) in patients with COVID-19.Stepwise multiple linear regression (forward selection) was performed to identify factors associated with TPCRN. Clinical symptoms and potential confounding variables were entered into the model. Covariates included age, sex, BMI, smoking status, comorbidities, vaccination status, medication use, C-reactive protein (CRP), lymphocyte count, and time from symptom onset to first pharyngeal PCR positivity (S-to-PCR). TPCRN was the dependent variable.

Relationship between clinical symptoms and 7-day negative nucleic acid conversion rate in COVID-19 patients

Pearson’s chi-square test was used to analyze intergroup differences. Among the factors examined, patients with diabetes, autoimmune diseases, or symptoms including cough, throat pain, dry mouth, and diarrhea had a lower 7-day negative nucleic acid conversion rate (all p < 0.05) (Table 3; Fig. 2).

Table 3.

Univariate analysis of clinical characteristics associated with 7-day negative nucleic acid conversion rate among patients with COVID-19

Variables		7-day negative nucleic acid conversion status			P
		>7 ds, n (%)	≤ 7 ds, n (%)
Sex	Men	106 (33.02%)	215 (66.98%)	0.004	0.948
	Women	54 (32.73%)	111 (67.27%)
Age	< 60 years	142 (31.91%)	303 (68.09%)	2.445	0.118
	≥ 60 years	18 (43.90%)	23 (56.10%)
BMI	< 28 kg/m2	139 (32.86%)	284 (67.14%)	0.006	0.941
	≥ 28 kg/m2	21 (33.33%)	42 (66.67%)
Smoking	Non-current smokers	115 (34.53%)	218 (65.47%)	1.246	0.264
	Current smokers	45 (29.41%)	108 (70.59%)
Hypertension	Without	140 (32.11%)	296 (67.89)	1.264	0.261
	With	20 (40.00%)	30 (60.00%)
Diabetes	Without	148 (31.76%)	318 (68.24%)	6.926	0.008
	With	12 (60.00%)	8 (40.00%)
CHD	Without	155 (32.91%)	316 (67.09%)	0.001	0.585
	With	5 (33.33%)	10 (66.67%)
COPD	Without	155 (32.77%)	318 (67.23%)	0.186	0.766
	With	5 (38.46%)	8 (61.54%)
Autoimmune diseases	Without	153 (32.21%)	322 (67.79%)	4.808	0.046
	With	7 (63.64%)	4 (36.36%)
Cancer	Without	156 (32.64%)	322 (67.36%)	1.074	0.448
	With	4 (50.00%)	4 (50.00%)
Vaccination	Without	)18 (56.25%)	14 (43.75%)	8.442	0.004
	With	142 (31.28%)	312 (68.72%)
Chinese patent medicine	Without	79 (29.59%)	188 (70.41%)	2.982	0.084
	With	81 (36.99%)	138 (63.01%)
Antipyretic	Without	134 (32.92%)	273 (67.08%)	0.000	0.998
	With	26 (32.91%)	53 (67.09%)
CRP	≥ 10 mg/L	101 (33.01%)	205 (66.99%)	0.003	0.959
	<10 mg/L	59 (32.78%)	121 (67.22%)
Lymphocyte count	≥ 0.8 × 10⁹/L	152 (33.48%)	302 (66.52%)	0.973	0.324
	<0.8 × 10⁹/L	8 (25.00%)	24 (75.00%)
S-to-PCR	>0 day	45 (24.19%)	141 (75.81%)	10.395	0.001
	0 day	115 (38.33%)	185 (61.67%)
Fever	Without	78 (29.55%)	186 (70.45%)	2.983	0.084
	With	82 (36.94%)	140 (63.06%)
Weakness	Without	99 (31.03%)	220 (68.97%)	1.497	0.221
	With	61 (36.53%)	106 (63.47%)
Sweatiness	Without	94 (30.13%)	218 (69.87%)	3.080	0.079
	With	66 (37.93%)	108 (62.07%)
Cough	Without	46 (25.56%)	134 (74.44%)	7.025	0.008
	With	114 (37.25%)	192 (62.75%)
Itchy throat	Without	102 (30.63%)	231 (69.37%)	2.514	0.113
	With	58 (37.91%)	95 (62.09%)
Throat pain	Without	91 (28.35%)	230 (71.65%)	18.254	< 0.001
	With	69 (41.82%)	96 (58.18%)
Oral bitterness	Without	130 (33.33%)	260 (66.67%)	0.151	0.697
	With	30 (31.25%)	66 (68.75%)
Dry mouth	Without	115 (30.26%)	265 (69.74%)	6.989	0.008
	With	45 (42.45%)	61 (57.55%)
Chest distress and shortness of breath	Without	136 (32.15%)	287 (67.85%)	0.877	0.349
	With	24 (38.10%)	39 (61.90%)
Inappetence	Without	132 (32.75%)	271 (67.25%)	0.030	0.863
	With	28 (33.73%)	55 (66.27%)
Abdominal distension	Without	150 (32.19%)	316 (67.81%)	2.755	0.097
	With	10 (50.00%)	10 (50.00%)
Constipation	Without	145 (32.51%)	301 (67.49%)	0.414	0.520
	With	15 (37.50%)	25 (62.50%)
Diarrhea	Without	135 (31.03%)	300 (68.97%)	14.789	< 0.001
	With	25 (49.02%)	26 (50.98%)
Palpitation	Without	152 (32.34%)	318 (67.66%)	2.185	0.139
	With	8 (50.00%)	8 (50.00%)
Nasal obstruction	Without	106 (31.74%)	228 (68.26%)	0.679	0.410
	With	54 (35.53%)	98 (64.47%)
Rhinorrhea	Without	114 (31.84%)	244 (68.16%)	0.716	0.398
	With	46 (35.94%)	82 (64.06%)
Sleep disorders	Without	131 (31.34%)	287 (68.66%)	3.386	0.066
	With	29 (42.65%)	39 (57.35%)
Nausea and vomiting	Without	147 (32.17%)	310 (67.83%)	1.980	0.159
	With	13 (44.83%)	16 (55.17%)
Muscular soreness	Without	113 (30.96%)	252 (69.04%)	2.558	0.110
	With	47 (38.84%)	74 (61.16%)
Headache	Without	106 (32.32%)	222 (67.68%)	0.167	0.683
	With	54 (34.18%)	104 (65.82%)
Asymptomatic	Symptomatic	143 (33.18%)	288 (66.82%)	0.114	0.736
	Asymptomatic	17 (30.91%)	38 (69.09%)

Data are presented as n (%). Group differences were compared using Pearson’s chi-square test

Abbreviations: BMI, body mass index; CHD, Coronary Heart Disease; COPD, Chronic obstructive pulmonary disease (COPD); CRP, C-reactive protein; S-to-PCR, time from first symptom onset to first PCR positivity

Fig. 2.

Association between clinical characteristics and the 7-day negative nucleic acid conversion rate in patients with COVID-19.Associations were evaluated using Pearson's chi-square test. The bars represent the proportions of patients who achieved or did not achieve a 7-day negative nucleic acid conversion.

After adjusting for confounding factors, binary logistic regression analysis revealed that vaccination (OR = 2.628, p = 0.025), and time from first symptom onset to first pharyngeal PCR positivity (OR = 1.316, p = 0.002) exerted a significant positive effect on 7-day negative nucleic acid conversion rate; In contrast, autoimmune diseases (OR = 0.186, p= 0.049), throat pain (OR = 0.584, p = 0.028) and diarrhea (OR = 0.435, p = 0.017) were negatively associated with the 7-day negative nucleic acid conversion rate (Fig. 3).

Fig. 3.

Forest plot of factors associated with 7-day negative nucleic acid conversion rate in patients with COVID-19.Forest plot showing adjusted odds ratios (ORs) and 95% confidence intervals from the multivariable logistic regression model. The outcome variable was 7-day negative nucleic acid conversion rate (coded as 1 = negative conversion within 7 days and 0 = conversion after 7 days). Covariates included demographic characteristics, comorbidities, vaccination status, medication history, laboratory parameters, and clinical symptoms.

Discussion

This study systematically explored the association between clinical symptoms and time to pharyngeal PCR negativity (TPCRN) in patients with mild Omicron COVID-19, with 7-day negative nucleic acid conversion rate as a complementary outcome indicator. The core findings confirmed that throat pain and diarrhea were independently associated with prolonged TPCRN (B = 1.277, 95% CI = 0.592–1.962, P < 0.001; B = 1.445, 95% CI = 0.382–2.508, P = 0.008) and reduced 7-day negative nucleic acid conversion rate (OR = 0.584, 95% CI = 0.362–0.943, P = 0.028; OR = 0.435, 95% CI = 0.220–0.860, P = 0.017). Additionally, autoimmune diseases and elevated C-reactive protein (CRP) were positively correlated with TPCRN, while the S-to-PCR showed a negative association with TPCRN, and vaccination improved the 7-day conversion rate. These results highlight that specific clinical symptoms can serve as potential markers for predicting delayed viral clearance in mild Omicron infections.

TPCRN is a critical indicator for assessing viral clearance, discharge timing, and transmission risk in COVID-19 patients [9–13]. Previous studies have identified age, comorbidities, vaccination status [44], and immune function as key influencing factors [14–19], while the association between specific clinical symptoms and TPCRN in mild Omicron cases remains insufficiently clarified [45–48]. Our findings supplement this evidence gap: throat pain, as a typical upper respiratory symptom, was linked to prolonged TPCRN, which may be attributed to two pathological mechanisms [49–52]. First, SARS-CoV-2 infection induces local inflammatory responses in the pharyngeal mucosa, releasing inflammatory mediators that damage mucosal barriers and delay repair, creating a microenvironment conducive to persistent viral replication. Second, throat pain may reflect heightened local inflammatory responses and ongoing viral replication in the upper respiratory tract [49, 50], which are associated with prolonged viral shedding and delayed nucleic acid negativity.

Diarrhea, a common digestive symptom in COVID-19, also emerged as an independent predictor of delayed viral clearance. This is consistent with Han et al.’s [28] observation that digestive symptoms are associated with prolonged viral shedding.The underlying mechanism may involve the high expression of angiotensin-converting enzyme 2 (ACE2)—the receptor for SARS-CoV-2—in gastrointestinal mucosal cells [28, 53, 54], enabling the virus to replicate in the digestive tract and form an additional viral reservoir, thereby extending systemic viral clearance time. Furthermore, diarrhea-induced water-electrolyte imbalance and impaired nutrient absorption may compromise immune function, indirectly delaying viral clearance [49, 55–57].

Our study also confirmed that autoimmune diseases were associated with prolonged TPCRN (B = 3.128, 95% CI = 0.985–5.270, P = 0.004) and reduced 7-day conversion rate (OR = 0.186, P = 0.049), which aligns with the notion that immune dysfunction impairs viral clearance [58]. Elevated CRP, a marker of systemic inflammation, was positively correlated with TPCRN (B = 0.037, 95% CI = 0.004–0.070, P = 0.027), supporting the hypothesis that inflammatory responses are linked to prolonged viral shedding [52]. In contrast, vaccination significantly improved the 7-day conversion rate (OR = 2.628, P = 0.025), consistent with evidence that vaccines enhance immune protection against Omicron [59]. Notably, Chinese patent medicines and antipyretics did not show independent effects on viral clearance, suggesting their role may be limited to symptomatic relief rather than direct antiviral activity.

Compared with previous research, this study has three distinct strengths. First, it focused on mild/asymptomatic Omicron-infected patients, a population that is clinically relevant but understudied, providing targeted evidence for pandemic management. Second, a standardized daily PCR testing protocol (with two consecutive negative results as the discharge criterion) ensured the accuracy and comparability of TPCRN measurements. Third, the simultaneous use of continuous (TPCRN) and categorical (7-day conversion rate) outcome indicators mutually validated the findings, enhancing result robustness. Additionally, potential confounding factors such as age, BMI, comorbidities, and vaccination status were comprehensively adjusted for, reducing bias.

This study also has limitations. First, the single-center retrospective design and short study period (April-May 2022) limit the generalizability of results to other variants or regions. Second, This study only focuses on the correlation analysis between clinical symptoms and TPCRN. However, PCR testing cannot distinguish between active viral infection and non-infectious residual viral RNA fragments. Therefore, the results of prolonged time to PCR negativity derived from this assay may have the potential for false positivity, and the clinical interpretation of such results requires further verification with gold standard detection methods such as viral culture. Third, initial viral load and Ct value data were not collected, which may influence TPCRN.Future studies should adopt multi-center prospective designs, incorporate viral load and Ct value measurements, and explore the mechanism linking symptoms to viral clearance through immune function and mucosal barrier assessments.

Conclusion

In conclusion, throat pain and diarrhea are independent predictors of prolonged TPCRN and reduced 7-day negative nucleic acid conversion rate in mild Omicron COVID-19 patients. These findings provide practical clinical value: identifying patients with these symptoms as high-risk for delayed viral clearance can guide personalized management strategies, such as intensified symptomatic treatment and extended monitoring, to optimize recovery outcomes and reduce transmission risks.

Abbreviations

SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2

PCR

Polymerase chain reaction

TPCRN

Time to pharyngeal PCR negativity

BMI

Body Mass Index

CHD

Coronary heart disease

COPD

Chronic obstructive pulmonary disease

CRP

C-reactive protein

Author contributions

Hui Feng was responsible for the conception and design of the study. Under the supervision of Xiang Hong, Shanhu Qiu, and Shaolei Ma, Hui Feng completed the main data collection and analysis. Chen Zhou participated in the extraction, supplementation, and statistical analysis of laboratory data. Hui Feng drafted the manuscript. Yingzi Huang oversaw the overall direction of the research. All authors contributed to, reviewed, and approved the final submitted version of the manuscript.

Funding

This study was funded by National Key R&D Program of China (grant number 2022YFC2304600), National Natural Science Foundation of China (grant number 82272235), Jiangsu Province Key research and development Program (Social Development) Special Project (grant number BE2021734), Jiangsu Province Traditional Chinese and Western Medicine Collaborative Flagship Hospital Construction Project (grant number CZXM-ZK-33), National Traditional Chinese and Western Medicine Flagship Department Construction Project - Intensive Care Medicine (grant number CZXM-ZK-46). Jiangsu Provincial High-Level Hospital Discipline Construction Project (grant number 2024GSPKY24).

Data availability

De-identified patient-level data are available upon reasonable request to the first author or corresponding author.

Declarations

Ethics approval and consent to participate

This study was approved by the Ethics Commission for Clinical Research at Zhongda Hospital, Southeast University, registered under Approval No. 2022ZDSYLL222-P01. The research adhered to the principles outlined in the Declaration of Helsinki, ensuring the confidentiality of all patient information. Informed consent was waived due to the nature of the study as a retrospective study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.