What are routine laboratory tests?
Routine laboratory tests are blood tests that assess the health status of a patient. Tests include counts of different types of white blood cells (these help the body fight infection), and detection of markers (proteins) that indicate organ damage, and general inflammation. These tests are widely available and in some places they may be the only tests available for diagnosis of COVID-19.
What did we want to find out?
People with suspected COVID-19 need to know quickly whether they are infected so that they can self-isolate, receive treatment, and inform close contacts.
Currently, the standard test for COVID-19 is usually the RT-PCR test. In the RT-PCR, samples from the nose and throat are sent away for testing, usually to a large, central laboratory with specialist equipment. Other tests include imaging tests, like X-rays, which also require specialist equipment.
We wanted to know whether routine laboratory tests were sufficiently accurate to diagnose COVID-19 in people with suspected COVID-19. We also wanted to know whether they were accurate enough to prioritize patients for different levels of treatment.
What did we do?
We searched for studies that assessed the accuracy of routine laboratory tests to diagnose COVID-19 compared with RT-PCR or other tests. Studies could be of any design and be set anywhere in the world. Studies could include participants of any age or sex, with suspected COVID-19, or use samples from people known to have – or not to have - COVID-19.
What we found
We found 21 studies that looked at 67 different routine laboratory tests for COVID-19. Most of the studies looked at how accurately these tests diagnosed infection with the virus causing COVID-19. Four studies included both children and adults, 16 included only adults and one study only children. Seventeen studies were done in China, and one each in Iran, Italy, Taiwan and the USA. All studies took place in hospitals, except one that used samples from a database. Most studies used RT-PCR to confirm COVID-19 diagnosis.
Accuracy of tests is most often reported using ‘sensitivity’ and ‘specificity’. Sensitivity is the proportion of people with COVID-19 correctly detected by the test; specificity is the proportion of people without COVID-19 who are correctly identified by the test. The nearer sensitivity and specificity are to 100%, the better the test. A test to prioritize people for treatment would require a high sensitivity of more than 80%.
Where four or more studies evaluated a particular test, we pooled their results and analyzed them together. Our analyses showed that only three of the tests had both sensitivity and specificity over 50%. Two of these were markers for general inflammation (increases in interleukin-6 and C-reactive protein). The third was for lymphocyte count decrease. Lymphocytes are a type of white blood cell where a low count might indicate infection.
How reliable are the results?
Our confidence in the evidence from this review is low because the studies were different from each other, which made them difficult to compare. For example, some included very sick people, while some included people with hardly any COVID-19 symptoms. Also, the diagnosis of COVID-19 was confirmed in different ways: RT-PCR was sometimes used in combination with other tests.
Who do the results of this review apply to?
Routine laboratory tests can be issued by most healthcare facilities. However, our results are probably not representative of most clinical situations in which these tests are being used. Most studies included very sick people with high rates of COVID-19 virus infection of between 27% and 76%. In most primary healthcare facilities, this percentage will be lower.
What does this mean?
Routine laboratory tests cannot distinguish between COVID-19 and other diseases as the cause of infection, inflammation or tissue damage. None of the tests performed well enough to be a standalone diagnostic test for COVID-19 nor to prioritize patients for treatment. They will mainly be used to provide an overall picture about the health status of the patient. The final COVID-19 diagnosis has to be made based on other tests.
How up-to-date is this review?
We searched all COVID-19 studies up to 4 May 2020.
Although these tests give an indication about the general health status of patients and some tests may be specific indicators for inflammatory processes, none of the tests we investigated are useful for accurately ruling in or ruling out COVID-19 on their own. Studies were done in specific hospitalized populations, and future studies should consider non-hospital settings to evaluate how these tests would perform in people with milder symptoms.
Specific diagnostic tests to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and resulting COVID-19 disease are not always available and take time to obtain results. Routine laboratory markers such as white blood cell count, measures of anticoagulation, C-reactive protein (CRP) and procalcitonin, are used to assess the clinical status of a patient. These laboratory tests may be useful for the triage of people with potential COVID-19 to prioritize them for different levels of treatment, especially in situations where time and resources are limited.
To assess the diagnostic accuracy of routine laboratory testing as a triage test to determine if a person has COVID-19.
On 4 May 2020 we undertook electronic searches in the Cochrane COVID-19 Study Register and the COVID-19 Living Evidence Database from the University of Bern, which is updated daily with published articles from PubMed and Embase and with preprints from medRxiv and bioRxiv. In addition, we checked repositories of COVID-19 publications. We did not apply any language restrictions.
We included both case-control designs and consecutive series of patients that assessed the diagnostic accuracy of routine laboratory testing as a triage test to determine if a person has COVID-19. The reference standard could be reverse transcriptase polymerase chain reaction (RT-PCR) alone; RT-PCR plus clinical expertise or and imaging; repeated RT-PCR several days apart or from different samples; WHO and other case definitions; and any other reference standard used by the study authors.
Two review authors independently extracted data from each included study. They also assessed the methodological quality of the studies, using QUADAS-2. We used the 'NLMIXED' procedure in SAS 9.4 for the hierarchical summary receiver operating characteristic (HSROC) meta-analyses of tests for which we included four or more studies. To facilitate interpretation of results, for each meta-analysis we estimated summary sensitivity at the points on the SROC curve that corresponded to the median and interquartile range boundaries of specificities in the included studies.
We included 21 studies in this review, including 14,126 COVID-19 patients and 56,585 non-COVID-19 patients in total. Studies evaluated a total of 67 different laboratory tests. Although we were interested in the diagnotic accuracy of routine tests for COVID-19, the included studies used detection of SARS-CoV-2 infection through RT-PCR as reference standard. There was considerable heterogeneity between tests, threshold values and the settings in which they were applied. For some tests a positive result was defined as a decrease compared to normal vaues, for other tests a positive result was defined as an increase, and for some tests both increase and decrease may have indicated test positivity. None of the studies had either low risk of bias on all domains or low concerns for applicability for all domains. Only three of the tests evaluated had a summary sensitivity and specificity over 50%. These were: increase in interleukin-6, increase in C-reactive protein and lymphocyte count decrease.
Blood count
Eleven studies evaluated a decrease in white blood cell count, with a median specificity of 93% and a summary sensitivity of 25% (95% CI 8.0% to 27%; very low-certainty evidence). The 15 studies that evaluated an increase in white blood cell count had a lower median specificity and a lower corresponding sensitivity. Four studies evaluated a decrease in neutrophil count. Their median specificity was 93%, corresponding to a summary sensitivity of 10% (95% CI 1.0% to 56%; low-certainty evidence). The 11 studies that evaluated an increase in neutrophil count had a lower median specificity and a lower corresponding sensitivity. The summary sensitivity of an increase in neutrophil percentage (4 studies) was 59% (95% CI 1.0% to 100%) at median specificity (38%; very low-certainty evidence). The summary sensitivity of an increase in monocyte count (4 studies) was 13% (95% CI 6.0% to 26%) at median specificity (73%; very low-certainty evidence). The summary sensitivity of a decrease in lymphocyte count (13 studies) was 64% (95% CI 28% to 89%) at median specificity (53%; low-certainty evidence). Four studies that evaluated a decrease in lymphocyte percentage showed a lower median specificity and lower corresponding sensitivity. The summary sensitivity of a decrease in platelets (4 studies) was 19% (95% CI 10% to 32%) at median specificity (88%; low-certainty evidence).
Liver function tests
The summary sensitivity of an increase in alanine aminotransferase (9 studies) was 12% (95% CI 3% to 34%) at median specificity (92%; low-certainty evidence). The summary sensitivity of an increase in aspartate aminotransferase (7 studies) was 29% (95% CI 17% to 45%) at median specificity (81%) (low-certainty evidence). The summary sensitivity of a decrease in albumin (4 studies) was 21% (95% CI 3% to 67%) at median specificity (66%; low-certainty evidence). The summary sensitivity of an increase in total bilirubin (4 studies) was 12% (95% CI 3.0% to 34%) at median specificity (92%; very low-certainty evidence).
Markers of inflammation
The summary sensitivity of an increase in CRP (14 studies) was 66% (95% CI 55% to 75%) at median specificity (44%; very low-certainty evidence). The summary sensitivity of an increase in procalcitonin (6 studies) was 3% (95% CI 1% to 19%) at median specificity (86%; very low-certainty evidence). The summary sensitivity of an increase in IL-6 (four studies) was 73% (95% CI 36% to 93%) at median specificity (58%) (very low-certainty evidence).
Other biomarkers
The summary sensitivity of an increase in creatine kinase (5 studies) was 11% (95% CI 6% to 19%) at median specificity (94%) (low-certainty evidence). The summary sensitivity of an increase in serum creatinine (four studies) was 7% (95% CI 1% to 37%) at median specificity (91%; low-certainty evidence). The summary sensitivity of an increase in lactate dehydrogenase (4 studies) was 25% (95% CI 15% to 38%) at median specificity (72%; very low-certainty evidence).