Did patients with COVID-19 receive timely treatment in the early epidemic?—a systematic review and meta-analysis
Original Article

Did patients with COVID-19 receive timely treatment in the early epidemic?—a systematic review and meta-analysis

Peipei Du1,2#, Weixiang Chen1#, Xufei Luo3#, Yaolong Chen4,5,6,7, Qianling Shi8, Meng Lv3, Jie Wang2, Xuemei Shi9, Xiaofeng Ma2, Tianying Yang10, Shuya Lu11,12, Tingting Li13, Xiaokun Yang14, Shu Yang1, Xixi Feng2; COVID-19 Evidence and Recommendations Working Group

1College of Medical Information Engineering, Chengdu University of Traditional Chinese Medicine, Chengdu, China; 2School of Public Health, Chengdu Medical College, Chengdu, China; 3School of Public Health, Lanzhou University, Lanzhou, China; 4Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China; 5WHO Collaborating Centre for Guideline Implementation and Knowledge Translation, Lanzhou, China; 6GIN (Guidelines International Network) Asia, Lanzhou, China; 7Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province, Lanzhou University, Lanzhou, China; 8The First School of Clinical Medicine, Lanzhou University, Lanzhou, China; 9School of Clinical Medicine, Chengdu Medical College, Chengdu, China; 10The Second School of Clinical Medicine, Chongqing Medical University, Chongqing, China; 11Department of Pediatric, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China; 12Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu, China; 13School of Pharmacy, Chengdu Medical College, Chengdu, China; 14Department of Emergency Medicine, The General Hospital of Western Theater Command of PLA, Chengdu, China

Contributions: (I) Conception and design: P Du, W Chen, X Luo, S Yang, X Feng; (II) Administrative support: X Yang, Y Chen, S Yang, X Feng; (III) Provision of study materials or patients: P Du, Y Chen, X Luo, Q Shi; (IV) Collection and assembly of data: P Du, X Luo, Q Shi, M Lv, J Wang, X Shi; (V) Data analysis and interpretation: S Yang, X Feng, P Du, X Yang, X Ma, T Yang, T Li; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

#These authors contributed equally to this work.

Correspondence to: Dr. Xiaokun Yang. Department of Emergency Medicine, The General Hospital of Western Theater Command of PLA, No. 270 Rongdu Road, Chengdu, China. Email: bacelona1978@163.com; Dr. Shu Yang. College of Medical Information Engineering, Chengdu University of Traditional Chinese Medicine, No. 37, Twelve-bridge Road, Chengdu, China. Email: yangshu@cdutcm.edu.cn; Dr. Xixi Feng. School of Public Health, ChengDu Medical College, No. 783 Xindu Road, Chengdu, China. Email: fengxixi@163.com.

Background: Corona virus disease 2019 (COVID-19) showed a significant difference in case fatality rate between different regions at the early stage of the epidemic. In addition to the well-known factors such as age structure, detection efficiency, and race, there was also a possibility that medical resource shortage caused the increase of the case fatality rate in some regions.

Methods: Medline, Cochrane Library, Embase, Web of Science, CBM, CNKI, and Wanfang of identified articles were searched through 29 June 2020. Cohort studies and case series with duration information on COVID-19 patients were included. Two independent reviewers extracted the data using a standardized data collection form and assessed the risk of bias. Data were synthesized through description and analysis methods including a meta-analysis.

Results: A total of 109 articles were retrieved. The time interval from onset to the first medical visit of COVID-19 patients in China was 3.38±1.55 days (corresponding intervals in Hubei province, non-Hubei provinces, Wuhan, Hubei provinces without Wuhan were 4.22±1.13, 3.10±1.57, 4.20±0.97, and 4.34±1.72 days, respectively). The time interval from onset to the hospitalization of COVID-19 patients in China was 8.35±6.83 days (same corresponding intervals were 12.94±7.43, 4.17±1.45, 14.86±7.12, and 5.36±1.19 days, respectively), and when it was outside China, this interval was 5.27±1.19 days.

Discussion: In the early stage of the COVID-19 epidemic, patients with COVID-19 did not receive timely treatment, resulting in a higher case fatality rate in Hubei province, partly due to the relatively insufficient and unequal medical resources. This research suggested that additional deaths caused by the out-of-control epidemic can be avoided if prevention and control work is carried out at the early stage of the epidemic.

Trial Registration: CRD42020195606.

Keywords: Corona virus disease 2019 (COVID-19); first diagnosis; hospitalization; time interval; meta-analysis


Submitted Jul 18, 2021. Accepted for publication Sep 30, 2021.

doi: 10.21037/apm-21-1975


Introduction

The corona virus disease 2019 (COVID-19) epidemic outbreak began in December 2019 (1-3). By the end of 2020, the total number of confirmed cases worldwide had exceeded 80.64 million, and the death toll had exceeded 1.76 million (4). Currently, no specific medicine for the treatment of COVID-19 has been found globally (5,6). The World Health Organization (WHO) recommended that the treatment of COVID-19 should be mainly based on supportive treatment, including oxygen therapy for severe patients and those at risk of serious diseases, and more advanced respiratory support for critically ill patients (7). Timely hospitalization is a significant factor in prognosis and the risk of disease and death, especially patients with underlying diseases or the elderly (8-10). The timely treatment mainly depends on whether the medical resources in the area where patients live are sufficient, meanwhile, to a certain extent, it also depends on the patient’s willingness to pay a medical visit (11). Through the collection and analysis of articles, this research compared the time intervals from onset to first medical visit and onset to the hospitalization of COVID-19 patients in different regions and assessed the supply and demand status of medical resources, to provide an evidence-based reference for authorities to guide people’s health-related behaviors during epidemics, to stem the spread of the disease, reduce health care burden and death rate. We present the following article in according with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting checklist (available at https://apm.amegroups.com/article/view/10.21037/apm-21-1975/rc).


Methods

Search strategy

This systematic review was registered in International prospective register of systematic reviews (PROSPERO) on June 29, 2020, with the protocol of CRD42020195606. Articles publishing before June 29, 2020, that reported medical information of COVID-19 patients were included in this research, the following databases were comprehensively searched, including the Cochrane Library, PubMed, EMBASE, Web of Science, CBM (China Biology Medicine disc), CNKI (China National Knowledge Infrastructure), and Wanfang database. The following search formulas were used in this research, including (“COVID 19” OR “COVID-19” OR “SARS-CoV-2” OR “2019 novel coronavirus” OR “2019-nCoV” OR “2019-CoV” OR “coronavirus disease 2019” OR “coronavirus disease-19” OR “Novel coronavirus” OR “2019-novel coronavirus”) AND (“symptom onset” OR “illness onset” OR “first symptom” OR “onset of illness”) AND (“admission” OR “hospitalization”) AND (“see a doctor” OR “first medical visit” OR “first medical care” OR “visit hospital”). Besides, WHO, Chinese Center for Disease Control and Prevention (CCDC), National Health Commission of the People’s Republic of China, USA National Institutes of Health Ongoing Trials Register (ClinicalTrials.gov), International Standard Randomized Controlled Trial Number (ISRCTN) registry, Google Scholar, the preprint servers medRxiv (https://www.medrxiv.org/) and bioRxiv (https://www.biorxiv.org/), and Social Science Research Network (SSRN, https://www.ssrn.com/index.cfm/en/) were also included as retrieval sources. The retrieval strategy for this research was reviewed by information experts.

Inclusion and exclusion criteria

Case series and cohort studies that reported the medical visit time of COVID-19 patients were included. Abstracts, case reports, letters, news, guidelines, comments, and articles that were unable to obtain all relevant data or full texts were excluded. There were no restrictions on language or publication status.

Article screening

After deleting duplicates in all the retrieved articles, two reviewers (P Du and Q Shi) used EndNote to independently screen these articles in two steps. The first step was to filter the title and summary using predefined criteria. The second step was to review the articles that were likely to meet the requirements by reading the full text and determine whether they will be finally included. The reasons for the exclusion of all unqualified articles were recorded, PRISMA flowcharts were used to record the process of article screening, and screening objections were resolved through discussion or consultation with a third reviewer (X Luo).

Data extraction

Data were extracted independently by two reviewers (P Du and Q Shi) using a standardized data collection form, and all objections were resolved through discussion or consultation with a third reviewer (X Luo). The third reviewer was responsible for checking the consistency and accuracy of the data. Data extraction includes the following three aspects: (I) basic information (title, author, country, date of publication, research type), (II) patient information (number, gender, age, disease type, sample size, grouping variables), (III) result information (the interval from first symptom onset to the first medical visit, the interval from the first symptoms onset to the first hospitalization, clinical outcome).

Data analysis

The 1st time interval was defined as the interval from the first symptom onset to the first medical visit of COVID-19 patients, and the 2nd time interval was defined as the interval from the first symptoms onset to the first hospitalization of COVID-19 patients. The medical institution was defined as the designated hospitals which are accredited for COVID-19 detection and treatment, since general clinics and isolation sites are unable to provide systematic measures. The clinical classification of COVID-19 patients in China is based on Guidelines on the Novel Coronavirus-Infected Pneumonia Diagnosis and Treatment issued by the National Health Commission of People’s Republic of China (12). A mild case was defined as mild clinical symptoms and no radio graphic evidence of pneumonia. A moderate case was defined as a confirmed case with fever, respiratory symptoms and radio graphic evidence of pneumonia. A severe case was defined as a confirmed case meets any of the following criteria: (I) shortness of breath, RR ≥30 times/min; (II) oxygen saturation ≤93% at rest; (III) alveolar oxygen partial pressure/fraction of inspiration O2 (PaO2/FiO2) <300 mmHg. A critical case was defined as a confirmed case meets any of the following conditions: (I) respiratory failure requiring mechanical ventilation; (II) shock; (III) patients combined with other organ failure needed intensive care unit (ICU) monitoring and treatment. Exposure history was defined as COVID-19 patients with a history of travel to the source of the outbreak or a history of exposure to confirmed cases. The duration of viral shedding was defined as the number of days from the onset of the symptoms until the successive negative detection of SARS-CoV-2 RNA.

Statistical analysis

In the retrieval articles, the statistics of the 1st and 2nd time intervals were described by mean ± standard deviation or median (interquartile range), while some research only provided point estimates, maximum and minimum values. This research used an estimation method proposed by Luo (13) and Wan (14) et al. to unify the time intervals of all research as mean ± standard deviation, and the sample size weighting method was used to calculate the weighted mean of each time interval sample. Linear or nonlinear regression was used to fit the trend of time interval of patients in different periods. The patients were divided into two groups according to the severity of the disease: common patients (mild and moderate cases) and severe patients (severe and critical cases) in the meta-analysis. Heterogeneity was defined as P<0.05 and I2>50% (15). Mean difference (MD) with 95% confidence intervals (CI) was used as the effect size. Sensitivity analysis was conducted by comparing the difference between the fixed-effect model and the random effect model. Two-sided P values <0.05 were considered statistically significant. All statistical analysis was implemented on RStudio (Version 1.2.5033).

Assessment of risk of bias

Two reviewers (P Du and Q Shi) independently assessed the risk of bias for each research, resolved objections by discussion, and consulted a third reviewer (X Luo) if necessary. Appropriate assessment tools were selected to assess the risk of bias according to research types in the article: the Newcastle-Ottawa scale which consists of eight parts, with each part using a star rating, should be used for the cohort study (16). The more the stars, the lower the risk of bias. Furthermore, for a case series study, methodological assessment tools recommended by the National Institute for Health and Care Excellence (NICE) should be used (17). The risk of bias was assessed against 8 criteria, and the results were summarized using a scoring method with 1 point for “Yes” and 0 point for “No”. The higher the scores, the lower the risk of bias.

Quality of evidence assessment

Two reviewers (P Du and Q Shi) used Grading of Recommendations Assessment, Development and Evaluation (GRADE) guidelines (18,19) to independently assessed the quality of evidence and used GRADEpro to create a form, in which the results of each research included in the meta-analysis were classified for evidence quality. The overall quality was downgraded based on 5 factors (risk of bias, inconsistency, imprecision, indirectness, and publication bias) and upgraded based on 3 factors (large effect size, dose-effect relationship, and negative bias). The overall quality of evidence was classified as high, medium, low, or very low, reflecting the trust degree that the effect estimates were accurate.


Results

Article research results

After a systematic retrieval, 2,435 articles were retrieved for the first time. After deleting duplicates, 109 articles were finally included in the evaluation through screening titles, abstracts, and full texts, including 103 case series and 6 cohort studies, and the patient information of 101 articles (92.7%) was collected before April 2020. The processes of article retrieval and screening were shown in Figure 1. A total of 18,777 patients were included in this research, including 8,405 females (44.8%), 9,671 males (51.5%), and 701 patients (3.7%) with unknown gender. China contributed 100 (91.7%) articles, 38 (34.9%) of which were from Hubei province (the most affected province in China). The remaining 9 (8.3%) articles were from abroad shown in Table S1 [two articles from Singapore (20,21), two articles from Korea (22,23), two articles from the United States (24,25), one article from Germany (26), one article from Japan (27) and 1 article from French (28)].

Figure 1 The processes of article retrieval and screening.

This research intended to assess whether the patient had received treatment in time by collecting the 1st and 2nd time intervals. Among the included 109 articles, 30 articles only reported the 1st time interval, 73 articles only reported the 2nd time interval, and 6 articles reported both time intervals. The included articles’ assessment of the risk of bias was provided in Tables S2,S3.

Time interval from onset to the first medical visit

Figure 2 showed the 1st time interval in 36 articles, of which 10 articles (27.8%) were from Hubei Province and 26 articles (72.2%) were from non-Hubei provinces. The 1st time interval was not mentioned in the included articles outside China. The 1st time interval was mostly concentrated in about 5 days, the minimum time interval was 0 (median) days [an article from Shenyang, China (29), 65.38% (17 out of 26) of COVID-19 patients paid a medical visit on the day of onset), the maximum time interval was 7.52 (mean) days (an article from Hubei Province researching on severe patients (30)]. In terms of the 1st time interval, no significant difference was found between patients from Hubei province and non-Hubei provinces.

Figure 2 The distribution of the 1st time interval of COVID-19 patients in China. The articles are sorted by the follow-up time end date, with the most recent at the top. Hollow points and solid points represented articles from Hubei province and non-Hubei provinces respectively. The mean was represented by a triangle and the median was represented by a circle. The length of a line segment was determined by the standard deviation of the interval and the interquartile spacing, and the point estimate had no corresponding line segment. Patients with different severity of disease were shown in different colors. The sample size was represented by the size of the points. COVID-19, corona virus disease 2019.

Part of the articles made statistics of COVID-19 patients’ 1st time interval in groups according to the severity of the disease, exposure history, time around Wuhan’s cordon sanitaire, etc. Firstly, 6 articles grouped patients according to the severity of the disease, and the results showed that the longer the 1st time interval, the worse the patient’s health condition. However, a research of Wuhan showed that the 1st time interval in severe patients (7.52 days) was longer than that in common patients (5.35 days), whereas the 1st time interval of critically ill patients was shorter (4.8 days) (30). Secondly, an article from Shenyang grouped patients according to whether they had an exposure history, and the result showed that patients without an exposure history (4 days) had a longer 1st time interval compared with those who had one (0 days) (29). Thirdly, an article from Hunan province indicated that the 1st time interval of patients after January 23 (cordon sanitaire day of Wuhan) (1 day) was shorter than that before January 23 (3 days) (31).

Time interval from onset to hospitalization

Figure 3 showed the 2nd time interval in 70 articles, of which 31 (44.3%) articles were from Hubei province (27 articles from Wuhan), and 39 (55.7%) articles were from non-Hubei provinces. The 2nd time interval was 1 (median) day to 25.9 (mean) days among the 70 articles, the minimum value appeared in an article from non-Hubei provinces (32) and the maximum value appeared in an article from Wuhan that researched 55 COVID-19 patients’ delayed treatment cases (33). The 2nd time interval of Hubei COVID-19 patients was 3 days to 25.9 days, and it was 1 day to 8.5 days for non-Hubei COVID-19 patients. In general, COVID-19 patients in Hubei province had a longer 2nd time interval than those in non-Hubei provinces. Equally, an included article showed the same research result (5.7 days in Hubei province and 4.5 days in non-Hubei provinces) after compared the 2nd time interval in 647 patients from Hubei province and 943 patients from non-Hubei provinces (34).

Figure 3 The distribution of the 2nd time interval of COVID-19 patients in China. The description was the same as Figure 2 except for the 2nd time interval. COVID-19, corona virus disease 2019.

Part of the articles made statistics of COVID-19 patients’ 2nd time interval in groups according to clinical outcome, the severity of the disease, and the duration of viral shedding. There were 4 articles from Hubei province dividing COVID-19 patients into two groups (cure and death) according to clinical outcome. Two of them indicated that the 2nd time interval of the cured group was shorter than that of the dead group clearly (35,36) (3 days/5 days and 7 days/10 days in the 2 articles respectively). Additionally, 8 articles grouped patients according to the severity of the disease, and the results showed that the longer the 2nd time interval, the worse the patients’ health condition. Moreover, 3 articles grouped patients by the duration of viral shedding (37-39), and the results showed that the longer the 2nd time interval, the longer the duration of viral shedding.

Figure 4 summarized the 2nd time interval in 9 articles outside China, ranging from 3.5 days to 8 days. An article from South Korea divided COVID-19 patients into two groups according to whether they were admitted to the ICU, and results showed that the 2nd time interval of the patients admitted to the ICU (4.7 days) was shorter than the patients did not admit to the ICU (8.2 days) (23). A German article divided COVID-19 patients into two groups according to whether they had ARDS, and the results showed that the 2nd time interval of ARDS patients (7 days) was longer than common patients (3 days) (26).

Figure 4 The distribution of the 2nd time interval of COVID-19 patients outside China. The articles are sorted by the follow-up time end date, with the most recent at the top. Hollow points and solid points represented articles from Hubei province and non-Hubei provinces. The mean was represented by a triangle and the median was represented by a circle. The length of a line segment was determined by the standard deviation of the interval and the interquartile spacing. The sample size was represented by the size of the points. COVID-19, corona virus disease 2019.

Estimation of the 1st time interval and the 2nd time interval

Figure 5A indicated the daily number of newly confirmed COVID-19 cases in Wuhan, Hubei province without Wuhan and non-Hubei provinces from January 20, 2020 to March 10, 2020. As shown in the figure, most of the new cases confirmed in the early and middle of February. In Figure 5B and 5C, this research took the median follow-up time point as the horizontal axis, and the 1st and 2nd time intervals were taken as the vertical axis to draw scatter plots. There was a decreasing trend for the 1st time interval in Wuhan, and no obvious trend in non-Hubei provinces or Hubei province without Wuhan. Figure 5C showed that the 2nd time interval of COVID-19 patients had a relatively obvious trend of gradual increase since February in Wuhan. Non-Hubei provinces had a trend of decrease, and no obvious trend was observed in Hubei province without Wuhan because only four articles were included.

Figure 5 Estimation of the 1st time interval and the 2nd time interval in China. (A) was a stacked histogram of the number of daily new confirmed COVID-19 cases in Wuhan, Hubei province without Wuhan, and non-Hubei provinces from January 20, 2020 to March 10, 2020. (B) was a scatter plot of the median follow-up time point and the 1st time interval. (C) was a scatter plot of the median follow-up time point and the 2nd time interval. COVID-19, corona virus disease 2019.

Through research, the 1st time interval of COVID-19 patients in China was approximately 3.38±1.55 days, with a median of 2.60 (2.35, 4.70) days. In Hubei province, it was 4.22±1.13 days, with a median of 4.35 (3.46, 4.84) days. In non-Hubei provinces, it was 3.10±1.57 days, with a median of 2.48 (2.31, 4.50) days. In Hubei province without Wuhan, it was 4.34±1.72 days, with a median of 3.79 (2.57, 5.35) days. In Wuhan, it was 4.20±0.97 days, with a median of 4.35 (3.46, 4.84) days. There was no estimation of patients’ the 1st time interval outside China due to a lack of relevant data.

The 2nd time interval of COVID-19 patients was approximately 8.35±6.83 days, with a median of 5.39 (3.35, 10.54) days. In Hubei province, it was 12.94±7.43 days, with a median of 10.81 (6.90, 24.65) days. In non-Hubei provinces, it was 4.17±1.45 days, with a median of 4.35 (3.20, 4.65) days. In Hubei province without Wuhan, it was 5.36±1.19 days, with a median of 5.7 (5.70, 6.00) days. In Wuhan, it was 14.86±7.12 days, with a median of 11.00 (9.35, 24.65) days. Outside China, it was 5.27±1.19 days, with a median of 4.65 (4.65, 5.00) days.

Meta-analysis of the time interval of common patients and severe patients

Six articles from China [one article (30) from Hubei province and five articles (31,40-43) from non-Hubei provinces] had reported the 1st time interval according to the severity of disease of COVID-19 patients. the meta-analysis results showed that compared with common patients, the 1st time interval of severe patients was longer MD =−1.25, 95% CI (−1.71, −0.80), P<0.01, I2=0% (Figure 6).

Figure 6 Meta-analysis of the 1st time interval of common and severe patients.

Eight articles from China [two articles (44,45) from Hubei province and six articles (31,41,46-49) from non-Hubei provinces] had reported the 2nd time interval according to the severity of disease of COVID-19 patients. One of the eight articles (44) showed that the 2nd time interval for severe patients and common patients in Wuhan were 6 and 5 days, respectively, however, it was excluded from the meta-analysis since it only provided a point estimate. The meta-analysis results showed that compared with common patients, the 2nd time interval of severe patients was longer MD =−1.92, 95% CI (−2.55, −1.30), P<0.01, I2=0% (Figure 7).

Figure 7 Meta-analysis of the 2nd time interval of common and severe patients.

Sensitivity analysis and quality of evidence

By comparing the difference between the fixed-effect model and the random effect model, the results of the sensitivity analysis showed that MD values and 95% CI results were close either in the 1st time interval or in the 2nd time interval, which indicated that the meta-analysis in this research was stable. The details of the sensitivity analysis can be found in Table 1.

Table 1

Sensitivity-analysis of the time interval of common patients and severe patients

Research factors Fixed effect model, MD (95% CI) Random effect model, MD (95% CI)
Duration from symptom onset to first medical visit −1.25 (−1.71, −0.80) −1.25 (−1.71, −0.80)
Duration from symptom onset to admission −1.92 (−2.55, −1.30) −1.92 (−2.55, −1.30)

MD, mean difference; CI, confidence interval.

The qualities of the evidence included in the articles were very low according to the GRADE quality assessment. Details were provided in Table S4.


Discussion

COVID-19 was a highly infectious emerging disease that had caused a global pandemic (50). The rapid development of the epidemic had exposed the deficiencies in epidemic prevention and control, public health systems, and health care systems of various countries. In some areas, the unequal allocation of medical resources directly led to the delay of patient medical visits and treatment (51).

The results of this research showed that the 1st time interval of COVID-19 patients in China was 0 days to 7.52 days, with an estimated value of 3.38±1.55 days, and it was 4.22±1.13 days in Hubei Province and 3.10±1.57 days in non-Hubei provinces. Overseas articles did not involve the time data. The 1st time interval was approximately 1 day longer for COVID-19 patients in Hubei than in non-Hubei areas, whereas the time interval between Wuhan and the rest of Hubei province was relatively similar. This indicated that people in Hubei province had poorer access to health care than other provinces during the outbreak, which had further contributed to the spread of COVID-19 there.

The lack of public awareness of COVID-19 at the beginning of the epidemic, coupled with the fact that most SARS-CoV-2 infected individuals have mild symptoms and the early clinical manifestations of the disease are difficult to distinguish from the common cold, might lead infected individuals to ignore the initial mild symptoms and not pay a timely medical visit. As shown in Figure 5B, the cordon sanitaire policies implemented from January 23 in Wuhan had strengthened people’s attention to COVID-19, and the 1st time interval had been significantly shortened after these cordon sanitaire policies (31). Therefore, timely disclosure of the outbreak and strong preventive and control measures can help raise the awareness of the public.

At the end of January, China implemented the highest level of public health emergency response policies, including quarantine and medical observation for people with an exposure history, case tracing, and screening of close contacts. An article from Shenyang showed that the 1st time interval of patients with an exposure history was shorter than that of those without an exposure history, which was related to these policies (29). Nevertheless, the outbreak of COVID-19 caused a certain degree of social panic, and some suspected patients were afraid of paying a medical visit and handled by themselves through home isolation, which was also a reason leading to the delay of patients’ medical visits and treatment (52,53). Therefore, during the critical period of epidemic prevention and control, national and local authorities should disclose information in an understandable, timely, transparent and coordinated manner to reduce public panic. At the same time, the authorities should strengthen epidemiological investigation, health education, public awareness of medical visits, to urge the patients to pay a medical visit in time.

The 2nd time interval of COVID-19 patients in China was 1 to 15 days, with an estimated value of 8.35±6.83 days, and it was 12.94±7.43 days in Hubei Province, and 4.17±1.45 days in non-Hubei provinces. The 2nd time interval outside China was 3 days to 8 days, with an estimated value of 4.89±0.89 days. If the regional disparities in the 2nd time interval of COVID-19 patients between China and outside China might be influenced by lifestyle, health systems, and patient treatment (26), then the more obvious differences among multiple regions in China were more likely due to the variances in the supply and demand status of medical resources. The mean of the 2nd time interval in Hubei provinces was obviously longer and the standard deviation was strongly bigger than those non-Hubei provinces of China may indicate that Hubei Province had not only the longest 2nd time interval but also a huge difference in system composition compared with other regions. Figure 5B showed that there was a slight difference in the 1st time interval of patients between Wuhan and non-Hubei provinces, while Figure 5C showed that the 2nd time interval of patients in Wuhan was significantly longer than that in non-Hubei provinces, and the trend of increasing over time in Figure 5C could be considered consequently caused by medical overwhelmed in Wuhan with the rapid accumulation of cases (48,54). Therefore, the length of the 2nd time interval, to some extent, reflected the inadequacy of medical resources in Wuhan during the health emergency. However, as a provincial capital city, the number of tertiary hospitals in Wuhan ranked ahead in China (55), and the proportion of medical staffs (10.19 health technical personnel per thousand, 3.69 licensed physicians per thousand, 5.07 registered nurses per thousand) were much higher than national average level, in which corresponding numbers were 7.26, 2.77 and 3.18 (56,57). If the outbreak is out of control at the initial stage, the shortage of medical resources in a specific period cannot be avoided even in an area with relatively sufficient self-resource reserves and supplements mobilized from other areas.

Of the 109 articles included, 6 articles compared the 1st time interval, and 8 articles compared the 2nd time interval in COVID-19 patients with various disease severities. The results showed that both time intervals were longer in patients with severe disease than in patients with mild disease and common patients. Meta-analysis comparing the length of the 2nd time interval between common patients and severe patients revealed that delayed hospitalization may be an influential factor in the exacerbation of the patient’s condition. Although one research from Wuhan reported a shorter the 1st time interval in critically ill patients than in the common patients, this may be related to the fact that the average age of critically ill patients (69 yrs old) is higher than that of the common patients (43 yrs old) (30), and numerous researches have confirmed the strong correlation between age and severity of disease in patients with COVID-19 (6). Some research indicated that delayed treatment would also affect virus shedding time (37), resulting in a higher risk of infection among close contacts, easy spread, and the occurrence of cluster outbreaks, which was not conducive to the national epidemic prevention and control.

Advantages and limitations

This research analyzed whether COVID-19 patients receive treatment in time by summarizing the 1st and 2nd time intervals from the 109 articles. In terms of advantages, our research demonstrated the supply and demand status of medical resources in the early stage of the epidemic by comparing the differences in the 1st time interval and the 2nd time interval of patients in different regions and with various disease severities, to analyze whether there is an increase in case fatality rate caused by insufficient medical resources and provide a reference for national or regional medical resource allocation, personnel scheduling, and prevention and control policy decisions.

The research had several limitations. Firstly, only nine articles outside China were included in this research, which may have caused some bias. Secondly, the estimation of time intervals may affect the accuracy of the research results due to the sample size weighting method and the conversion method of median to estimate the mean, as well as missing data in some articles. Thirdly, the progression of the patient’s condition is not only related to the time of visit, but the patient’s gender, age, physical health status, and the medical resources will lead to the bias of the results.


Conclusions

It was found that the 1st time interval was similar between Hubei and non-Hubei patients, but the 2nd time interval of Hubei was much longer than that of non-Hubei patients. The 2nd time interval of COVID-19 patients outside China was close to that of non-Hubei provinces. Both the 1st and 2nd intervals were longer in severe patients than in common patients. This phenomenon supported that there was a medical overwhelmed resource and patients with COVID-19 did not receive timely treatment in Hubei province at the beginning of the epidemic, and this could explain why the case fatality rate in Hubei province was much higher than that in other parts of China at the beginning of the outbreak. Besides detection efficiency, the relative lack of medical resources was another important reason that was ignored.


Acknowledgments

We would like to thank all the primary authors of studies included in this systematic review and meta-analysis.

Funding: This work was supported by “Coronavirus Disease Special Project” of Xinglin Scholars of Chengdu University of Traditional Chinese Medicine (XGZX2013).


Footnote

Reporting Checklist: The authors have completed the PRISMA reporting checklist. Available at https://apm.amegroups.com/article/view/10.21037/apm-21-1975/rc

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://apm.amegroups.com/article/view/10.21037/apm-21-1975/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

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References

  1. Zhu N, Zhang D, Wang W, et al. A Novel Coronavirus from Patients with Pneumonia in China, 2019. N Engl J Med 2020;382:727-33. [Crossref] [PubMed]
  2. Huang C, Wang Y, Li X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 2020;395:497-506. [Crossref] [PubMed]
  3. World Health Organization. Coronavirus disease (COVID-19) outbreak; 2019. Available online: https://www.who.int [accessed 24.12.20].
  4. Coronavirus disease (COVID-19) Weekly Epidemiological Update and Weekly Operational Update. Available online: https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports [accessed 26.12.20].
  5. Bloch EM, Shoham S, Casadevall A, et al. Deployment of convalescent plasma for the prevention and treatment of COVID-19. J Clin Invest 2020;130:2757-65. [Crossref] [PubMed]
  6. Wu Z, McGoogan JM. Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention. JAMA 2020;323:1239-42. [Crossref] [PubMed]
  7. World Health Organization. (2020). COVID-19 Clinical management: living guidance. Available online: https://www.who.int/publications/i/item/WHO-2019-nCoV-clinical-2021-1
  8. Du RH, Liu LM, Yin W, et al. Hospitalization and Critical Care of 109 Decedents with COVID-19 Pneumonia in Wuhan, China. Ann Am Thorac Soc 2020;17:839-46. [Crossref] [PubMed]
  9. Chen N, Zhou M, Dong X, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet 2020;395:507-13. [Crossref] [PubMed]
  10. Guan WJ, Ni ZY, Hu Y, et al. Clinical Characteristics of Coronavirus Disease 2019 in China. N Engl J Med 2020;382:1708-20. [Crossref] [PubMed]
  11. Luo XM, Zhou W, Xia H, et al. Characteristics of SARS-CoV-2 Infected Patients with Clinical Outcome During Epidemic Ongoing Outbreak in Wuhan, China[J]. SSRN Electronic Journal 2020. 10.2139/ssrn.355281210.2139/ssrn.3552812
  12. National Health Commission. The Guidelines for the Diagnosis and Treatment of COVID-19 (Trial, 7th edition). Available online: http://www.gov.cn/zhengce/zhengceku/2020-03/04/content_5486705.htm
  13. Luo D, Wan X, Liu J, et al. Optimally estimating the sample mean from the sample size, median, mid-range, and/or mid-quartile range. Stat Methods Med Res 2018;27:1785-805. [Crossref] [PubMed]
  14. Wan X, Wang W, Liu J, et al. Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range. BMC Med Res Methodol 2014;14:135. [Crossref] [PubMed]
  15. Cumpston M, Li T, Page MJ, et al. Updated guidance for trusted systematic reviews: a new edition of the Cochrane Handbook for Systematic Reviews of Interventions. Cochrane Database Syst Rev 2019;10:ED000142. [Crossref] [PubMed]
  16. Wells G, Shea B, O’Connell D, et al. Newcastle-Ottawa Quality Assessment Scale--Case Control Studies. Available online: http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp
  17. National Institute for Health and Care Excellence. Appendix 4. Quality assessment for Case series. 2013. Available online: https://www.nice.org.uk/guidance/cg3/documents/appendix-4-quality-of-case-series-form2
  18. Norris SL, Meerpohl JJ, Akl EA, et al. The skills and experience of GRADE methodologists can be assessed with a simple tool. J Clin Epidemiol 2016;79:150-158.e1. [Crossref] [PubMed]
  19. Guyatt GH, Oxman AD, Vist GE, et al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ 2008;336:924-6. [Crossref] [PubMed]
  20. Young BE, Ong SWX, Ng LF, et al. Immunological and Viral Correlates of COVID-19 Disease Severity: A Prospective Cohort Study of the First 100 Patients in Singapore. SSRN Electronic Journal 2020. 10.2139/ssrn.357684610.2139/ssrn.3576846
  21. Ng Y, Li Z, Chua YX, et al. Evaluation of the Effectiveness of Surveillance and Containment Measures for the First 100 Patients with COVID-19 in Singapore - January 2-February 29, 2020. MMWR Morb Mortal Wkly Rep 2020;69:307-11. [Crossref] [PubMed]
  22. Jung HY, Lim JH, Kang SH, et al. Outcomes of COVID-19 among Patients on In-Center Hemodialysis: An Experience from the Epicenter in South Korea. J Clin Med 2020;9:1688. [Crossref] [PubMed]
  23. Hong KS, Lee KH, Chung JH, et al. Clinical Features and Outcomes of 98 Patients Hospitalized with SARS-CoV-2 Infection in Daegu, South Korea: A Brief Descriptive Study. Yonsei Med J 2020;61:431-7. [Crossref] [PubMed]
  24. Husain SA, Dube G, Morris H, et al. Early Outcomes of Outpatient Management of Kidney Transplant Recipients with Coronavirus Disease 2019. Clin J Am Soc Nephrol 2020;15:1174-8. [Crossref] [PubMed]
  25. CummingsMJBaldwinMRAbramsDEpidemiology, clinical course, and outcomes of critically ill adults with COVID-19 in New York City: a prospective cohort study. Preprint. medRxiv. 2020;2020.04.15.20067157. 10.1101/2020.04.15.20067157
  26. Dreher M, Kersten A, Bickenbach J, et al. The Characteristics of 50 Hospitalized COVID-19 Patients With and Without ARDS. Dtsch Arztebl Int 2020;117:271-8. [Crossref] [PubMed]
  27. Imai K, Tabata S, Ikeda M, et al. Clinical evaluation of an immunochromatographic IgM/IgG antibody assay and chest computed tomography for the diagnosis of COVID-19. J Clin Virol 2020;128:104393. [Crossref] [PubMed]
  28. Mahévas M, Tran VT, Roumier M, et al. Clinical efficacy of hydroxychloroquine in patients with covid-19 pneumonia who require oxygen: observational comparative study using routine care data. BMJ 2020;369:m1844. [Crossref] [PubMed]
  29. Li J, Gong J, Yao M, et al. Epidemiological characteristics of COVID-19 patients in Shenyang. Anhui Medical Journal 2020;41:254-6.
  30. Wu W, Huang H, Zhang M, et al. Clinical features of COVID-19 patients:A 102 -case study. The Journal of Practical Medicine 2020;36:1569-73.
  31. Liu Z, Gao L, Hu S, et al. Seeking health services and diagnosis of 697 confirmed cases of coronavirus disease 2019 in Hunan province. Pract Prev Med 2020;27:513-7.
  32. Hu X, Xing Y, Jia J, et al. Factors associated with negative conversion of viral RNA in patients hospitalized with COVID-19. Sci Total Environ 2020;728:138812. [Crossref] [PubMed]
  33. Ye J, Yu Y, Lu Y, et al. CT image characteristics and clinical analysis of 55 patients with Corona Virus Disease 2019 and delayed diagnosis and treatment. Medical Journal of Chinese People’s Liberation Army 1-11[2020-12-04].
  34. Liang WH, Guan WJ, Li CC, et al. Clinical characteristics and outcomes of hospitalised patients with COVID-19 treated in Hubei (epicentre) and outside Hubei (non-epicentre): a nationwide analysis of China. Eur Respir J 2020;55:2000562. [Crossref] [PubMed]
  35. Huang J, Cheng A, Kumar R, et al. Hypoalbuminemia predicts the outcome of COVID-19 independent of age and co-morbidity. J Med Virol 2020;92:2152-8. [Crossref] [PubMed]
  36. Deng Y, Liu W, Liu K, et al. Clinical characteristics of fatal and recovered cases of coronavirus disease 2019 in Wuhan, China: a retrospective study. Chin Med J (Engl) 2020;133:1261-7. [Crossref] [PubMed]
  37. Xu K, Chen Y, Yuan J, et al. Factors Associated With Prolonged Viral RNA Shedding in Patients with Coronavirus Disease 2019 (COVID-19). Clin Infect Dis 2020;71:799-806. [Crossref] [PubMed]
  38. Qi L, Yang Y, Jiang D, et al. Factors associated with the duration of viral shedding in adults with COVID-19 outside of Wuhan, China: a retrospective cohort study. Int J Infect Dis 2020;96:531-7. [Crossref] [PubMed]
  39. ZhouYHeXZhangJProlonged SARS-CoV-2 Viral Shedding in Patients with COVID-19 was Associated with Delayed Initiation of Arbidol Treatment: a retrospective cohort study.MedRxiv 2020. doi: .10.1101/2020.06.09.20076646
  40. Liu Y, Fan Y, Deng X, et al. Early warning factors of severe patients with COVID -19. The Journal of Practical Medicine 2020;36:1574-8.
  41. Chen S, Jia P, Qiu L, et al. Epidemiological characteristics of COVID- - 19 in Hainan Province, China. Chinese Journal of Zoonoses 2020;36:372-6.
  42. Tian S, Hu N, Lou J, et al. Characteristics of COVID-19 infection in Beijing. J Infect 2020;80:401-6. [Crossref] [PubMed]
  43. Zhai H, Wu Q, Li W, et al. Analysis of the clinical characteristics of 74 cases with Corona Virus Disease 2019. Journal of Bengbu Medical College 2020;45:429-32.
  44. Han J, Dong X, Hu F, et al. Clinical characteristics of 120 patients infected with SARS-CoV-2 Guangdong Medical Journal 2020;41:772-5. [J].
  45. Li R, Tao J, Yao X, et al. Multi-Center Clinical Research of Risk Factors Associated with Severe and Critical Patients with Coronavirus Disease 2019. China Pharmaceuticals 2020;29:15-8.
  46. Yuan J, Sun Y, Zuo Y, et al. Clinical characteristics of 223 COVID-19 patients in Chongqing. Journal of Southwest University (Natural Science Edition) 2020;42:17-24.
  47. Huang Q, Deng X, Li Y, et al. Clinical characteristics and drug therapies in patients with the common-type coronavirus disease 2019 in Hunan, China. Int J Clin Pharm 2020;42:837-45. [Crossref] [PubMed]
  48. Jiang Y, He S, Zhang C, et al. Clinical characteristics of 60 discharged cases of 2019 novel coronavirus-infected pneumonia in Taizhou, China. Ann Transl Med 2020;8:547. [Crossref] [PubMed]
  49. Huang R, Zhu L, Xue L, et al. Clinical findings of patients with coronavirus disease 2019 in Jiangsu province, China: A retrospective, multi-center study. PLoS Negl Trop Dis 2020;14:e0008280. [Crossref] [PubMed]
  50. Li JY, You Z, Wang Q, et al. The epidemic of 2019-novel-coronavirus (2019-nCoV) pneumonia and insights for emerging infectious diseases in the future. Microbes Infect 2020;22:80-5. [Crossref] [PubMed]
  51. Emanuel EJ, Persad G, Upshur R, et al. Fair Allocation of Scarce Medical Resources in the Time of Covid-19. N Engl J Med 2020;382:2049-55. [Crossref] [PubMed]
  52. Centers for Disease Control and Prevention. Reducing Stigma. Available online: https://www.cdc.gov/coronavirus/2019-ncov/daily-life-coping/reducing-stigma.html
  53. World Health Organization, UNICEF and the Red Cross. Social Stigma Associated with COVID-19: A guide to preventing and addressing social stigma. Available online: https://www.unicef.org/documents/social-stigma-associated-coronavirus-disease-covid-19
  54. Xu XW, Wu XX, Jiang XG, et al. Clinical findings in a group of patients infected with the 2019 novel coronavirus (SARS-Cov-2) outside of Wuhan, China: retrospective case series. BMJ 2020;368:m606. [Crossref] [PubMed]
  55. The Lancet. Emerging understandings of 2019-nCoV. Lancet 2020;395:311. [Crossref] [PubMed]
  56. Wuhan Health and Health Care Development Bulletin 2019. Available online: http://wjw.wuhan.gov.cn/zwgk_28/fdzdgknr/tjsj/202010/P020201026595334757948.pdf. Accessed December 20, 2020.
  57. Compiled by National Bureau of Statistics of China.China Statistical Yearbook -2020. Beijing: China Statistics Press. Available online: http://www.stats.gov.cn/tjsj/ndsj/2020/indexeh.htm. Accessed December 20, 2020.
Cite this article as: Du P, Chen W, Luo X, Chen Y, Shi Q, Lv M, Wang J, Shi X, Ma X, Yang T, Lu S, Li T, Yang X, Yang S, Feng X; COVID-19 Evidence and Recommendations Working Group. Did patients with COVID-19 receive timely treatment in the early epidemic?—a systematic review and meta-analysis. Ann Palliat Med 2022;11(2):452-465. doi: 10.21037/apm-21-1975

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