Background Biomarkers such as C‐reactive protein (CRP) and procalcitonin may help distinguish community‐acquired pneumonia (CAP) from other causes of lower respiratory tract infection. Methods We performed a systematic review of the literature to identify prospective studies evaluating the accuracy of a biomarker in patients with acute cough or suspected CAP. We performed parallel abstraction of data regarding study inclusion, characteristics, quality, and test accuracy. Study quality was evaluated using QUADAS‐2. Bivariate meta‐analysis was performed using the mada package in R, and summary receiver operating characteristic (ROC) curves were created. Results Fourteen studies met our inclusion and exclusion criteria; three were at low risk of bias and four at moderate risk of bias, largely due to failure to prespecify diagnostic thresholds. Considering all studies regardless of the cutoff used, CRP was most accurate (area under the ROC curve = 0.802), followed by leukocytosis (0.777) and procalcitonin (0.771). Lipopolysaccharide‐binding protein and fibrinogen are promising, but were only studied in a single report. For CRP and procalcitonin, the positive and negative likelihood ratios (LR+ and LR–, respectively) varied inversely based on the cutoff. For CRP, LR+ and LR− were 2.08 and 0.32 for a cutoff of 20 mg/L, 3.64 and 0.36 for a cutoff of 50 mg/L, and 5.89 and 0.47 for a cutoff of 100 mg/L. For procalcitonin, LR+ and LR− were 2.50 and 0.39 for a cutoff of 0.10 µg/L, 5.43 and 0.62 for a cutoff of 0.25 µg/L, and 8.25 and 0.76 for a cutoff of 0.50 µg/L. The combination of CRP >49.5 mg/L and procalcitonin >0.1 µg/L had LR+ of 2.24 and LR− of 0.44. Conclusions The best evidence supports CRP as the preferred biomarker for diagnosis of outpatient CAP given its accuracy, low cost, and point‐of‐care availability.

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BackgroundCommunity‐acquired pneumonia (CAP) is an important source of morbidity and mortality. However, overtreatment of acute cough illness with antibiotics is an important problem, so improved diagnosis of CAP could help reduce inappropriate antibiotic use.MethodsThis was a meta‐analysis of prospective cohort studies of patients with clinically suspected pneumonia or acute cough that used imaging as the reference standard. All studies were reviewed in parallel by two researchers and quality was assessed using the QUADAS‐2 criteria. Summary measures of accuracy included sensitivity, specificity, likelihood ratios, the diagnostic odds ratio, and the area under the receiver operating characteristic curve (AUROCC) and were calculated using bivariate meta‐analysis.ResultsWe identified 17 studies, of which 12 were judged to be at low risk of bias and the remainder at moderate risk of bias. The prevalence of CAP was 10% in nine primary care studies and was 20% in seven emergency department studies. The probability of CAP is increased most by an abnormal overall clinical impression suggesting CAP (positive likelihood ratio [LR+] = 6.32, 95% CI = 3.58 to 10.5), egophony (LR+ = 6.17, 95% CI = 1.34 to 18.0), dullness to percussion (LR+ = 2.62, 95% CI = 1.14 to 5.30), and measured temperature (LR+ = 2.52, 95% CI = 2.02 to 3.20), while it is decreased most by the absence of abnormal vital signs (LR− = 0.25, 95% CI = 0.11 to 0.48). The overall clinical impression also had the highest AUROCC at 0.741.ConclusionsWhile most individual signs and symptoms were unhelpful, selected signs and symptoms are of value for diagnosing CAP. Teaching and performing these high value elements of the physical examination should be prioritized, with the goal of better targeting chest radiographs and ultimately antibiotics.

Background: The aim of this systematic review is to summarize the best available evidence regarding individual risk factors, simple risk scores, and multivariate models that use patient characteristics, vital signs, comorbidities, and laboratory tests relevant to outpatient and primary care settings.Methods: Medline, WHO COVID-19, and MedRxIV databases were searched; studies meeting inclusion criteria were reviewed in parallel, and variables describing study characteristics, study quality, and risk factor data were abstracted. Study quality was assessed using the Quality in Prognostic Studies tool. Random effects metaanalysis of relative risks (categorical variables) and unstandardized mean differences (continuous variables) was performed; multivariate models and clinical prediction rules were summarized qualitatively.Results: A total of 551 studies were identified and 22 studies were included. The median or mean age ranged from 38 to 68 years. All studies included only inpatients, and mortality rates ranged from 3.2% to 50.5%. Individual risk factors most strongly associated with mortality included increased age, c-reactive protein (CRP), d-dimer, heart rate, respiratory rate, lactate dehydrogenase, and procalcitonin as well as decreased oxygen saturation, the presence of dyspnea, and comorbid coronary heart and chronic kidney disease. Independent predictors of adverse outcomes reported most frequently by multivariate models include increasing age, increased CRP, decreased lymphocyte count, increased lactate dehydrogenase, elevated temperature, and the presence of any comorbidity. Simple risk scores and multivariate models have been proposed but are often complex, and most have not been validated.Conclusions: Our systematic review identifies several risk factors for adverse outcomes in COVID-19-infected inpatients that are often available in the outpatient and primary care settings: increasing age, increased CRP or procalcitonin, decreased lymphocyte count, decreased oxygen saturation, dyspnea on presentation, and the presence of comorbidities. Future research to develop clinical prediction models and rules should include these predictors as part of their core data set to develop and validate pragmatic outpatient risk scores. ( J Am Board Fam Med 2021;34:S113-S126.