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Clinical evaluation for sinusitis. Making the diagnosis by history and physical examination.

Publication ,  Journal Article
Williams, JW; Simel, DL; Roberts, L; Samsa, GP
Published in: Ann Intern Med
November 1, 1992

OBJECTIVE: To identify the most useful clinical examination findings for the diagnosis of acute and subacute sinusitis. DESIGN: Prospective comparison of clinical findings with radiographs. SETTING: General medicine clinics at a university-affiliated Veterans Affairs Medical Center. PATIENTS: Two hundred forty-seven consecutive adult men with rhinorrhea (51%), facial pain (22%) , or self-suspected sinusitis (27%) (median age, 50 years; median duration of symptoms, 11.5 days). MEASUREMENTS: Patients were examined by a principal investigator (86%) or by a staff general internist, internal medicine resident (postgraduate year 2 or 3), or physician assistant, all blinded to radiographic results. All examiners recorded the presence or absence of 16 historical items, 5 physical examination items, and the clinical impression for sinusitis (high, intermediate, or low probability). The criterion standard was paranasal sinus radiographs (4 views), which were interpreted by radiologists blinded to clinical findings. RESULTS: Thirty-eight percent of patients meeting entrance criteria had sinusitis. Sensitivity, specificity, and likelihood ratios were measured for clinical items. Logistic regression analysis showed five independent predictors of sinusitis: maxillary toothache (odds ratio, 2.9), transillumination (odds ratio, 2.7), poor response to nasal decongestants or antihistamines (odds ratio, 2.4), colored nasal discharge reported by the patient (odds ratio, 2.2), or mucopurulence seen during examination (odds ratio, 2.9). THe overall clinical impression was more accurate than any single finding: high probability (likelihood ratio, 4.7, intermediate (likelihood ratio, 1.4), low probability (likelihood ratio, 0.4). CONCLUSIONS: General internists, focusing on five clinical findings and their overall clinical impression, can effectively stratify male patients with sinus symptoms as having a high, intermediate, or low probability of sinusitis.

Duke Scholars

Published In

Ann Intern Med

DOI

ISSN

0003-4819

Publication Date

November 1, 1992

Volume

117

Issue

9

Start / End Page

705 / 710

Location

United States

Related Subject Headings

  • Transillumination
  • Statistics as Topic
  • Sinusitis
  • Sensitivity and Specificity
  • Radiography
  • Prospective Studies
  • Probability
  • Physical Examination
  • Observer Variation
  • Models, Statistical
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Williams, J. W., Simel, D. L., Roberts, L., & Samsa, G. P. (1992). Clinical evaluation for sinusitis. Making the diagnosis by history and physical examination. Ann Intern Med, 117(9), 705–710. https://doi.org/10.7326/0003-4819-117-9-705
Williams, J. W., D. L. Simel, L. Roberts, and G. P. Samsa. “Clinical evaluation for sinusitis. Making the diagnosis by history and physical examination.Ann Intern Med 117, no. 9 (November 1, 1992): 705–10. https://doi.org/10.7326/0003-4819-117-9-705.
Williams JW, Simel DL, Roberts L, Samsa GP. Clinical evaluation for sinusitis. Making the diagnosis by history and physical examination. Ann Intern Med. 1992 Nov 1;117(9):705–10.
Williams, J. W., et al. “Clinical evaluation for sinusitis. Making the diagnosis by history and physical examination.Ann Intern Med, vol. 117, no. 9, Nov. 1992, pp. 705–10. Pubmed, doi:10.7326/0003-4819-117-9-705.
Williams JW, Simel DL, Roberts L, Samsa GP. Clinical evaluation for sinusitis. Making the diagnosis by history and physical examination. Ann Intern Med. 1992 Nov 1;117(9):705–710.

Published In

Ann Intern Med

DOI

ISSN

0003-4819

Publication Date

November 1, 1992

Volume

117

Issue

9

Start / End Page

705 / 710

Location

United States

Related Subject Headings

  • Transillumination
  • Statistics as Topic
  • Sinusitis
  • Sensitivity and Specificity
  • Radiography
  • Prospective Studies
  • Probability
  • Physical Examination
  • Observer Variation
  • Models, Statistical