Use of rapid point-of-care testing for infection to guide doctors prescribing antibiotics for acute respiratory infections in primary care settings

Review question
We reviewed the evidence of the effect and safety of a rapid test of infection at point-of-care for using antibiotics in people with acute respiratory infections (ARIs) (e.g. common colds) in primary care.

Antibiotic treatment is common in ARIs despite the fact that the vast majority are caused by viruses, against which antibiotics are ineffective and unnecessary. The concern is that antibiotics may cause side effects and are directly associated with antibiotic resistance in common bacteria, causing treatment failure and complications, including death. Antibiotics have a modest, if any, effect against the majority of ARIs. Their use must be balanced against risking higher levels of antibiotic resistance, side effects and costs. Biomarkers of infection are proteins or components of the immune system that participate in the body's acute response to infection. No tests are currently able to provide perfect diagnostic accuracy for infections. This could lead to over- as well as under-diagnosis. Some tests have been developed that assess the presence of infections by looking for certain of these biomarkers. These are rapid tests that may be used during the consultation by primary care doctors when people go to see them with symptoms of an ARI. In the correct clinical context these point-of-care tests could assist primary care doctors by identifying people with infections that are most likely to respond to antibiotics. We looked at the evidence for these tests to assess the possible harms and benefits of implementing such a strategy in primary health care.

Study characteristics
We included six studies with a total of 3284 participants with ARIs from primary care settings (point-of care test: C-reactive protein). Two of the included studies received direct financial support from manufacturers. The evidence is current to January 2014.

Key results
The only point-of-care biomarker of infection currently available to primary care identified in the review was C-reactive protein. A reduction in antibiotic use is likely to be achieved by a C-reactive protein point-of-care test but due to differences in the designs of the included studies, it was not possible to obtain a precise effect estimate of the reduction. There were no deaths in the studies and we did not find evidence suggesting that time to recovery from ARIs and their duration were longer, nor that levels of patient satisfaction or number of re-consultations were affected in the C-reactive protein group. However, a possible increase in the risk of hospital admission cannot be ruled out.

Quality of the evidence
We ranked the evidence as of moderate quality according to the GRADE levels due to an imprecise effect estimation.

Used as an adjunct to a doctor's clinical examination point-of-care tests (e.g. C-reactive protein) can reduce antibiotic use in ARIs in general practice. The possibility of an increased risk of hospital admission suggests that care must be taken in how these tests are used. A more precise effect estimate is needed to assess the costs of the intervention and compare the use of a point-of-care biomarker to other antibiotic-saving strategies.

Authors' conclusions: 

A point-of-care biomarker (e.g. C-reactive protein) to guide antibiotic treatment of ARIs in primary care can reduce antibiotic use, although the degree of reduction remains uncertain. Used as an adjunct to a doctor's clinical examination this reduction in antibiotic use did not affect patient-reported outcomes, including recovery from and duration of illness. However, a possible increase in hospitalisations is of concern. A more precise effect estimate is needed to assess the costs of the intervention and compare the use of a point-of-care biomarker to other antibiotic-saving strategies.

Read the full abstract...

Acute respiratory infections (ARIs) are by far the most common reason for prescribing an antibiotic in primary care, even though the majority of ARIs are of viral or non-severe bacterial aetiology. Unnecessary antibiotic use will, in many cases, not be beneficial to the patients' recovery and expose them to potential side effects. Furthermore, as a causal link exists between antibiotic use and antibiotic resistance, reducing unnecessary antibiotic use is a key factor in controlling this important problem. Antibiotic resistance puts increasing burdens on healthcare services and renders patients at risk of future ineffective treatments, in turn increasing morbidity and mortality from infectious diseases. One strategy aiming to reduce antibiotic use in primary care is the guidance of antibiotic treatment by use of a point-of-care biomarker. A point-of-care biomarker of infection forms part of the acute phase response to acute tissue injury regardless of the aetiology (infection, trauma and inflammation) and may in the correct clinical context be used as a surrogate marker of infection, possibly assisting the doctor in the clinical management of ARIs.


To assess the benefits and harms of point-of-care biomarker tests of infection to guide antibiotic treatment in patients presenting with symptoms of acute respiratory infections in primary care settings regardless of age.

Search strategy: 

We searched CENTRAL (2013, Issue 12), MEDLINE (1946 to January 2014), EMBASE (2010 to January 2014), CINAHL (1981 to January 2014), Web of Science (1955 to January 2014) and LILACS (1982 to January 2014).

Selection criteria: 

We included randomised controlled trials (RCTs) in primary care patients with ARIs that compared use of point-of-care biomarkers with standard of care. We included trials that randomised individual patients as well as trials that randomised clusters of patients (cluster-RCTs).

Data collection and analysis: 

Two review authors independently extracted data on the following outcomes: i) impact on antibiotic use; ii) duration of and recovery from infection; iii) complications including the number of re-consultations, hospitalisations and mortality; iv) patient satisfaction. We assessed the risk of bias of all included trials and applied GRADE. We used random-effects meta-analyses when feasible. We further analysed results with a high level of heterogeneity in pre-specified subgroups of individually and cluster-RCTs.

Main results: 

The only point-of-care biomarker of infection currently available to primary care identified in this review was C-reactive protein. We included six trials (3284 participants; 139 children) that evaluated a C-reactive protein point-of-care test. The available information was from trials with a low to moderate risk of bias that address the main objectives of this review.

Overall a reduction in the use of antibiotic treatments was found in the C-reactive protein group (631/1685) versus standard of care (785/1599). However, the high level of heterogeneity and the statistically significant test for subgroup differences between the three RCTs and three cluster-RCTs suggest that the results of the meta-analysis on antibiotic use should be interpreted with caution and the pooled effect estimate (risk ratio (RR) 0.78, 95% confidence interval (CI) 0.66 to 0.92; I2 statistic = 68%) may not be meaningful. The observed heterogeneity disappeared in our preplanned subgroup analysis based on study design: RR 0.90, 95% CI 0.80 to 1.02; I2 statistic = 5% for RCTs and RR 0.68, 95% CI 0.61 to 0.75; I2 statistic = 0% for cluster-RCTs, suggesting that this was the cause of the observed heterogeneity.

There was no difference between using a C-reactive protein point-of-care test and standard care in clinical recovery (defined as at least substantial improvement at day 7 and 28 or need for re-consultations day 28). However, we noted an increase in hospitalisations in the C-reactive protein group in one study, but this was based on few events and may be a chance finding. No deaths were reported in any of the included studies.

We classified the quality of the evidence as moderate according to GRADE due to imprecision of the main effect estimate.