Can history and exam alone reliably predict pneumonia?

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Original Research

Can history and exam alone reliably predict pneumonia?

J Fam Pract. 2007 June;56(6):465-470

By

Graffelman A W, MD, PhD

Trust your judgment (and your radiologist) when deciding whether to give antibiotics.

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References

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Practice recommendations

Models based on clinical information do not reliably predict the presence of pneumonia. Testing for elevated C-reactive protein added limited value.

Background Prediction rules based on clinical information have been developed to support the diagnosis of pneumonia and help limit the use of expensive diagnostic tests. However, these prediction rules need to be validated in the primary care setting.

Methods Adults who met our definition of lower respiratory tract infection (LRTI) were recruited for a prospective study on the causes of LRTI, between November 15, 1998 and June 1, 2001 in the Leiden region of the Netherlands. Clinical information was collected and chest radiography was performed. A literature search was also done to find prediction rules for pneumonia.

Results 129 patients—26 with pneumonia and 103 without—were included, and 6 prediction rules were applied. Only the model with the addition of a test for C-reactive protein had a significant area under the curve of 0.69 (95% confidence interval [CI], 0.58–0.80), with a positive predictive value of 47% (95% CI, 23–71) and a negative predictive value of 84% (95% CI, 77–91). The pretest probabilities for the presence and absence of pneumonia were 20% and 80%, respectively.

Conclusions Models based only on clinical information do not reliably predict the presence of pneumonia. The addition of an elevated C-reactive protein level seems of little value.

Few patients with lower respiratory tract infections (LRTIs) are actually diagnosed with pneumonia after a chest X-ray. Studies in general practice show radiographically confirmed pneumonia in 6% to 39% of these patients, depending on inclusion criteria.^1-5

Despite the vital role that X-rays play in separating those who have this lung ailment from those who do not, this imaging tool is not a standard of care throughout the world in the diagnosis of pneumonia. For instance, primary care physicians in the Netherlands usually diagnose pneumonia based on medical history and physical examination, despite Dutch guidelines⁶ that call for X-rays in cases of suspected pneumonia. The reason: patients have to be sent to a hospital for an X-ray. This contrasts sharply to the US, where most family practice settings have radiographic equipment “down the hall.”

Regardless, though, of whether a physician is in the Netherlands or the US, it would certainly be welcome news if physicians could turn to a reliable prediction model that would reduce our reliance on medical imaging that can be costly—and in the case of the Netherlands, involve a trip to the hospital.

The value of prediction rules

Several investigators created prediction rules for pneumonia using information from the clinical history, physical examination, and simple laboratory tests.^5,7-12 Although the variables in these prediction rules vary considerably, most include fever, dyspnea, and any abnormality on auscultation (the signs and symptoms of these rules are given in TABLE 1). However, these rules are not used much in primary care, even in Europe. They have proven their value, however, in emergency departments in Europe and the US, where they are used to guide treatment and to predict the prognosis of the disease.^13,14

Validation of the prediction rules is necessary to create reliable tools for clinicians to use in the general practice setting. Only one rule¹⁰ had already been validated in other populations. In this study, the value of published prediction rules was tested in our group of patients with LRTI in a general practice setting.¹⁵

TABLE 1
Signs, symptoms, and values for 6 prediction models

MODEL	REGRESSION EQUATION AND VARIABLES
Singal⁸	Y=–3.539
	+ 0.884 for cough
	+ 0.681 for fever
	+ 0.464 for crackles
	+ 0.030 for 20.16 (pretest probability of pneumonia)*
Heckerling¹⁰	Y=–1.705
	+ 0.494 for temperature >37.7°C
	+ 0.428 for pulse >100 beats/min
	+ 0.658 for rales
	+ 0.638 for decreased breath sounds
	+ 0.691 for absence of asthma
Melbye¹¹	Y=+ 4.7 for fever (reported by patient) with duration of illness of 1 week or more
	– 4.5 for coryza
	– 2.1 for sore throat
	+ 5.0 for dyspnea
	+ 8.2 for chest pain, lateral
	+ 0.9 for crackles
González Ortiz¹²	Y=–1.87
	1.3 for pathologic auscultation
	+ 1.64 for neutrophilia
	+ 1.70 for pleural pain
	+ 1.21 for dyspnea
Hopstaken I⁵	Y=–2.74
	+ 1.02 for dry cough
	+ 1.78 for diarrhea
	+ 1.13 for temperature ≥38°C
Hopstaken II⁵	Y=–4.15
	+ 0.91 for dry cough
	+ 1.01 for diarrhea
	+ 0.64 for temperature ≥38°C
	+ 2.78 for C-reactive protein ≥20 mg/L
“Fever” means self-reported fever; “temperature” means taken by physician.
*For the pretest probability of pneumonia, the frequency (20.16%) of patients with pneumonia found in our dataset was used.

Methods

Recruiting the patients

The study was conducted in the Leiden region of the Netherlands between November 15, 1998 and June 1, 2001 (with a summer break in June, July, and August 2000), with the assistance of 23 primary care practitioners serving a total population of 27,000 people. Patients were recruited as part of a study of the causes of LRTI.¹⁵ We included patients who were 18 years of age and older who consulted their primary care physician for signs and symptoms of LRTI and met the following criteria for it:¹⁴