key: cord-0803904-tpxpslnm
authors: Anderson, Gloria; Casasanta, Daniela; Cocchieri, Antonello; D'Agostino, Fabio; Zega, Maurizio; Damiani, Gianfranco; Rega, Maria Luisa
title: Diagnostic features of SARS‐COVID‐2‐positive patients: A rapid review and meta‐analysis
date: 2021-02-17
journal: J Clin Nurs
DOI: 10.1111/jocn.15688
sha: 7bb4952911cb09179d1bf57e122c4214f6633494
doc_id: 803904
cord_uid: tpxpslnm

AIMS: To identify the main diagnostic features of SARS‐CoV‐2‐positive patients at the time of hospitalisation and their prevalence. BACKGROUND: Since the COVID‐19 outbreak in China in December of 2019, several studies attempted to identify the epidemiological, viral and clinical characteristics of SARS‐CoV‐2. Given the rapid widespread transmission of the COVID‐19 disease worldwide, a more comprehensive and up‐to‐date understanding of its features is needed to better inform nurses, clinicians and public health policy makers. METHODS: A rapid review and meta‐analysis were carried out to identify the main diagnostic features of SARS‐CoV‐2‐positive patients at the time of hospitalisation. All case series, cross‐sectional, case–control and cohort studies published from 01/01/2020 till 30/06/2020 in English and Chinese that stated all or at least two of the outcomes of interest (clinical features, laboratory and radiological findings) were included. We performed a random‐effects model meta‐analysis to calculate pooled prevalence and 95% confidence intervals. Conduction of the review adheres to the PRISMA checklist. RESULTS: 21 studies involving 8837 patients were included in the quantitative synthesis. Fever, cough and fatigue were the most common clinical features, while the most relevant laboratory abnormalities at the time of hospitalisation were lymphopenia, elevated C‐reactive protein and lactate dehydrogenase. CT images showed a bilateral lung involvement, with ground glass infiltrates and patchy shadows on most patients. CONCLUSION: This review provides an up‐to‐date synthesis of main diagnostic features of SARS‐CoV‐2‐positive patients at the time of hospitalisation. RELEVANCE TO CLINICAL PRACTICE: Our findings could provide guidance for nurses and clinicians to early identification of positive patients at the time of the hospitalisation through a complete definition of main clinical features, laboratory and CT findings.

In late December 2019, several cases of viral pneumonia of unknown aetiology were first reported in Wuhan, capital of Hubei, China, with epidemiological links to the Huanan Seafood Wholesale Market. The Chinese Centre for Disease Control and Prevention isolated the causative agent of the outbreak as a novel Coronavirus (nCoV), namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) . Soon after, the number of cases increased exponentially, spreading across China and worldwide. On 11 March 2020, the World Health Organization (WHO) officially declared the COVID-19 outbreak a pandemic (Mahase, 2020) . At the time of writing, more than 51 million cases of SARS-CoV-2 have been confirmed and more than 1.270.000 people have died (WHO, 2020a).

Since then, several studies attempted to identify the epidemiological, viral and clinical characteristics of SARS-CoV-2 patients. The majority of those studies were case reports, case series and crosssectional studies, which described evolution and outcomes of the disease, as well as risk factors, clinical, laboratory and image findings Chu et al., 2020; Cheng et al., 2020; Ai et al., 2020) . Two systematic reviews published between March and April 2020 (Rodriguez-Morales et al., 2020; Fu et al., 2020) gave a preliminary characterisation of the disease, describing the most commonly reported clinical features, the laboratory abnormalities and CT images of SARS-CoV-2 patients, mostly from China.

However, the current literature on COVID-19 is rapidly evolving, with new peer-reviewed and preprint articles published every day across the world, and its main features remain unclear (Rodriguez-Morales et al., 2020; Struyf et al., 2020) . Given the rapid widespread transmission of the COVID-19 disease worldwide, a more comprehensive and up-to-date understanding of its features is needed to better inform clinicians, nurses and public health policy makers.

A rapid review was conducted to identify the main diagnostic features of SARS-CoV-2-positive patients at the time of hospitalisation, aiming to help stakeholders and clinicians optimise the diagnostic process.

To achieve our aim, we: 

Conduction of the review adheres to PRISMA checklist for systematic reviews and meta-analyses (Moher et al., 2009) . See File S1. The outcomes of interest were the reported clinical and diagnostic features and the laboratory findings. We chose to include all the case series, cross-sectional, case-control and cohort studies that stated all or at least two of the outcomes of interest (e.g. clinical and diagnostic features or clinical and laboratory findings). For the clinical features, all the reported signs and symptoms were collected. In the same way, all the image characteristics and the lesions region of the diagnostic imaging as well as the stated blood routine, coagulation function, infection-related biomarkers and blood biochemistry were collected.

The Europe PMC, LitCovid Database, Medline, The Cochrane Library, Science Direct, Embase and The Cumulative Index to Nursing and Allied Health Literature (CINAHL) were screened independently by two experienced reviewers with the support of Zotero Reference Manager (V.5.0). In case of disagreement between the reviewers on eligibility, a senior author was consulted. Two different search strings were used (File S2), both combining different synonyms and mesh terms for SARS-CoV-2 and diagnosis or testing.

• This review provides an up-to-date summary of the main clinical characteristics of SARS-COV-2-positive patients at the time of hospitalisation.

• Among clinical symptoms, fever, cough and fatigue showed the highest pooled prevalence.

• The most common alterations of blood routine reported at the time of hospitalisation were lymphopenia, increased infection-related biomarkers and elevated liver functions values.

Since this is a rapid review, no specific searches of grey literature were done. After a discussion between the authors, we decided to include only peer-reviewed published articles. All the articles published in Chinese were summarised by a team member with a certified knowledge of the Chinese language and then discussed with another team member.

One experienced review author-extracted data from the included studies into a standardised table. A second review author checked the data extraction for completeness and correctness. Whether an article reported duplicate information from the same patient, the information of both reports was combined in order to obtain complete data, but only counted as a single case. Observational studies that stated the overall proportion of symptoms, laboratory characteristics and CT images or/and the mean values of clinical features or laboratory findings for SARS-CoV-2-positive patients at baseline were included for quantitative synthesis (meta-analysis). The data item included the following: author, country, year, study design, aim, characteristic of the study participants, diagnostic reference criteria, age, gender, comorbidities, clinical features (e.g. fever, cough), laboratory findings (e.g. lymphocytes count) and imaging (e.g. CT signs).

The risk of bias was assessed by one author with the Joanna Briggs institute (JBI) 'Checklist for case series' and 'Critical appraisal checklist for cohort'. A risk of bias judgement (Low; Moderate; High) was attributed to each included study following Melo et al. (2018) scoring system. Then, the 25% of the rating judgment was checked independently by another author, as suggested by the World Health Organization guidelines for rapid review (2017). Moreover, publication bias was assessed using a funnel plot and computing the Egger's test (Egger et al., 1997) .

All the different units of measure of the outcomes of interest were converted in the referred international unit (e.g. from mg/dl to mmol/L). All the data presented as median and interquartile range were converted to mean and standard deviation (SD) following the Cochrane handbook of systematic review of interventions (7.7.3.5).

Percentages or mean and standard deviation (SDs) were calculated to describe the distributions of categorical and continuous variables.

Pooled prevalence and its 95% confidence interval (CI) were used to summarise the weighed effect size for each study grouping variable in a random effect model. We chose a random effect model because we assumed high clinical, methodological and statistical heterogeneity. The proportion of cases (e.g. fever or lymphocytopenia) on the total number of cases for each outcome of interest was metaanalysed using the R function metaprop. Whether computed with function metamean in R, raw weighted mean and their 95% confidence intervals were reported (e.g. mean age in years).

Measure of heterogeneity, as the I 2 index and the tau squared test were estimated and reported for both pooled prevalence and pooled mean. We expected high heterogeneity from the results (Ioannidis et al., 2007) ; therefore, we chose to keep the pooled overall estimates but to estimate also a prediction interval for all the outcomes of interest as it presents the expected range of true effects in similar studies (IntHout et al., 2016) .

The literature search yielded 10727 references. After removal of duplicates, 7829 references were screened for title and abstract and 21 observational studies were identified, all included in the quantitative analysis ( Figure 1 ). The main descriptive characteristics of the included studies are shown in Table 1 .

The total sample of participants included 8837 adults with a laboratory-confirmed diagnosis of SARS-CoV-2 by real-time RT-PCR, accordingly to the World Health Organization or the National Health Commission diagnostic guidelines ( Table 1 ). The reasons for excluding the other records are listed in the PRISMA flow chart case ( Figure 1 ). All the included studies published before May 2020 were issued in Asia, while the latter were issued in USA and Europe too (Table 1 ). The most common type of studies included was retrospective case series or cross-sectional design (Table 1) . Data were primarily collected with the support of electronic records or by retrospective manual review of the clinical record at the time of hospitalisation; therefore, only one study provided baseline data for patients admitted at the emergency department ( Figure 1 ). All the included studies reported SARS-CoV-2 patients' clinical features and laboratory findings, while diagnostic imaging was less commonly and clearly stated especially in the recently issued articles (Table 1) .

The methodological quality of included studies was assessed according to the study designs with the Joanna Briggs Institute (JBI) checklists. As shown in Table 1 , nearly half of included studies were rated as 'Low' risk of bias. Only four studies were rated as 'Moderate' and even fewer as 'High' ( Table 1 ). The lack of consecutive inclusion or a clear description of participants, as well as many imprecisely reported outcomes, elevated the risk of bias in nearly half of the included studies. None of the cross-sectional designs provide any measure or adjustment for potential confounding variables.

Publication bias was assessed with a funnel plot for the standard error, with no evidence of bias (File S3). Additionally, the Egger's test (p =.61) performed by the gender variable suggested no notable evidence of publication bias.

The pooled mean age of the patients across the 21 studies was 51.43 years old (95%CI 48.35;54.52), with a prediction interval ranging from 41.54 to 61.32 mean years as in shown in Table 2 . However, the pooled mean age of the sample was fairly lowered by the pooled mean age of the studies issued in Asia, in which the mean age was 50 years old versus 65 years old of the studies issued in Western regions (e.g. America or Europe). Male was only slightly more prevalent than female in the total sample (Table 2) . Common comorbidities were hypertension (22.49%, 95%CI 15.49;31.49) and diabetes (13%, 95%CI 8.82;18.88), both with prediction intervals ranging from less than 5% to more than 50% ( Table 2 ). The rate of obesity was reported only by two studies (Table 2 ) and, despite only including estimates, it appears to be the most prevalent comorbidity of hospitalised SARS-CoV-2-positive patients (40.19%, 95%CI 29.23; 52.22) .

Surprisingly, both chronic obstructive pulmonary disease (3.66%, 95%CI 2.41;5.52) and malignancies (3.19%, 95%CI 2.07;4.87) were not very prevalent comorbidities in SARS-CoV-2-positive patients (Table 2) .

Symptoms were commonly reported in the included articles, while signs were often missing or described approximately as shown in Table 3 . Fever and cough were the only clinical features reported by the totality of the included studies as commonly associated to SARS-CoV-2 patients (Table 2) . However, cough, which was stated in all of the included studies, showed an overall pooled prevalence of only 64% (95%CI 60.33;67.60) and a large prediction interval ranging from less than 50% to more than 80% (Table 2 ). Fever, as a self-reported symptom, showed a pooled prevalence of 77.5% with a pretty narrow confidence interval (95%CI 71.45;82.58) but a fairly larger prediction interval (Table 2) . Only 6 studies reported the rate of SARS-CoV-2-positive patients with a temperature >38° Celsius, and the overall pooled prevalence of the sign was 38.96% (95%CI 25.65;54.14), while 5 studies clearly stated the mean temperature of the sample with thresholds ranging from 36.7° to 38.5° and with a non-statistically significant pooled mean of 36.96° Celsius (Table 2) . Other signs mean values (e.g. respiratory or heart rate) were reported only by four included studies (Table 3) , and despite pooled, they did not result statistically significant in the quantitative synthesis.

Diarrhoea was the most commonly reported gastrointestinal symptom (Table 3) and showed a pooled prevalence of 9.42% (95%CI 7.34;12.01). Instead, anorexia was recorded only by 7 included studies, but showed a pooled prevalence of 19.40% (95%CI 12.70;28.48) and a higher prediction interval than diarrhoea (Table 2) . Respiratory symptoms, like dyspnoea, pharyngalgia and rhinorrhoea, were not commonly reported in the included studies (Table 2) , and when pooled, did not show a high pooled prevalence ( using terms such 'sore throats', 'shortness of breath' or 'runny nose' as synonymous for pharyngalgia, dyspnoea and rhinorrhoea.

Neuromotor symptoms, such as myalgia and headache, were frequently reported in the included studies (Table 3) , but both showed low prevalence with prediction interval narrow than 50% (Table 2) .

Other possible relevant symptoms of SARS-CoV-2, such as loss of smell or taste and conjunctivitis, were stated only by one included article. 

Among the 21 studies which reported the laboratory findings of SARS-CoV-2 patients (Table 3) , 18 studies stated a widespread decrease of the lymphocyte count. Other commonly reported alterations of the blood routine in the included articles involved a general decrease of the leucocyte count, while the haemoglobin level did not seem to vary much (Table 3) . Indeed, a decrease in lymphocytes counts was present in the 50% of the total sample (95%CI 33.81;65.62), while leucocyte count showed a pooled prevalence of only 21.5% (Table 2) .

Between the infection-related biomarkers, an increased level of C-reactive protein level (CRP) was stated in all the articles except six ( predominantly as normal (Table 3) . Eight studies also reported normal values of coagulation function (Table 3) , except for D-dimer, which resulted increased in seven studies with a pooled prevalence of 27% (Table 2) .

Liver function values were reported by 17 of the included studies, mostly showing normal or increased levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST) and total bilirubin ( Table 2) . Both ALT and AST were increased in 11 included studies with an overall pooled prevalence of 18.3% (95%CI 8.95;33.78) and 26% (95%CI 14.82;40.56), respectively, and wide prediction intervals ( Table 2 ). Increase of total bilirubin was slightly less prevalent than ALT and AST, and it has an even wider prediction interval ( Table 2 ). Renal function (e.g. blood urea nitrogen, serum creatinine and glomerular filtration rate) was scarcely reported and referred predominantly as normal ( 

The processing of computed tomography (CT) images is often reported in the included studies as the fastest method to confirm a diagnosis of SARS-CoV-2 at the time of hospitalisation. Characteristic images of the SARS-CoV-2 patients in the CT scans were ground glass opacities (GGO) and consolidations (Table 3) . However, consolidation rates were reported only by 3 studies with an overall pooled prevalence of 7.2% (Table 2) . Instead, GGO were estimated in 38.2% (95%CI 24.89; 53.78 ) of the total sample (Table 2) . Moreover, only a few included studies provided a clear classification of how many patients have GGO, consolidation or both. Five articles stated the rate of observed patchy shadow without linking them to any possible causes such as pleural effusion or pneumonia (Table 3) , and despite pooled they were the most prevalent CT images reported in SARS-CoV-2 patients at hospitalisation ( Table 2 ).

The pulmonary opacifications or patchy shadows were stated in the included studies as located in the peripheral zones of both lungs (Table 3) , with the lower lobe of the left lung as the more involved one. However, while bilateral involvement is a prevalent clinical gauge of SAR-CoV-2-positive patients in the included studies, pleural effusion rates were reported only by 3 included articles and showed a pooled prevalence of only 3% (95%CI 0.78;11.26) with a wide prediction interval (Table 2) .

A rapid diagnosis is essential to ensure SARS-CoV-2 patients receive proper care and to reduce the risks of contagion, and this rapid review updates the diagnostic features of SARS-CoV-2 patients at the time of hospitalisation. Indeed, the actual golden standard tests for SARS-CoV-2 diagnosis are real-time RT-PCR by swab, which has low sensitivity (Carver & Jones, 2020) , and often it must be repeated one or more days apart. prevalence, which is a higher rate compared to those declared in a previous meta-analysis (Rodriguez-Morales et al., 2020) , but a wide prediction interval (Table 2) . Indeed, a recent Cochrane review (Struyf et al., 2020) highlighted how cough has a too poor specificity index to be considered a prominent diagnostic feature of SARS-CoV-2. Other respiratory symptoms, such as dyspnoea or pharyngalgia, are often reported in the included studies since ACE2 receptors appear to be the entry point for SARS-CoV-2 to into human cells, but both have an overall pooled prevalence lower than 30% with wide prediction intervals. Our estimated pooled prevalence for both dyspnoea and fatigue is lower than the one reported The WHO firstly called SARS-CoV-2 a 'novel coronavirusinfected pneumonia', since many image characteristics at first appeared to be consistent with viral pneumonia. The use of CT as a primary screening tool is discouraged, since it has a very low specificity . However, in resource-constrained environments, imaging is still indicated for triage of patient with suspected SARS-CoV-2 and we chose to report the main commonly reported However, in our meta-analysis consolidation has a consistently lower pooled proportion than the one stated by Bao et al. (2020) , and this could be probably due to the overall low reporting accuracy of the included articles. Most of the included articles were not accurate in the reporting of CT findings, providing more a generic description rather than a clear definition, especially the ones recently published or issued in America ( The predominantly altered laboratory findings are lymphocytes, prothrombin time, LDH, inflammatory markers and the indices of liver function (Table 2) 

We thank Miss Annalisa Dorbolò and Dr Barbara Pala for the advices.

The authors declare that there is no conflict of interest regarding the publication of these articles. 

Maria Luisa Rega https://orcid.org/0000-0003-3276-944X

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Additional supporting information may be found online in the Supporting Information section