Severity of meningococcal disease: assessment by factors and scores and implications for patient management

Rev Infect Dis. 1990 Nov-Dec;12(6):973-92. doi: 10.1093/clinids/12.6.973.

Abstract

Results from our own and other published series of cases of meningococcal disease were used to study prognostic factors and to compose scores for assessment of severity of disease on admission to the hospital. The difference in risk for fatality was designated the factor fatality difference (FFD); the FFD was determined by subtracting the percent fatality for factor-negative patients from the percent fatality for factor-positive patients. FFD was useful for selection of good indicators of severity of disease. Blood pH of less than 7.35 was the best single factor; low platelet count came next, followed by low blood pressure, cyanosis, ecchymosis, and low blood leukocyte count. New scores were constructed based on multiple regression analyses. Several older and new scores seemed to be comparable. By combining age-adjusted systolic blood pressure (less than 100 mm Hg), cyanosis, ecchymosis, diarrhea before or at admission, cold extremities, absence of nuchal or back rigidity, and rectal temperature of greater than or equal to 40 degrees C, a simple bedside percentage score, the MenOPP bedside clinical score (MOC), was devised. Cross-evaluations on test materials generally confirmed the choice of score. The simplicity of this score made it more clinically suitable than laboratory or mixed laboratory and bedside scores.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Age Factors
  • Blood Pressure
  • Cyanosis
  • Ecchymosis
  • Female
  • Fever
  • Humans
  • Hydrogen-Ion Concentration
  • Leukocyte Count
  • Male
  • Meningitis, Meningococcal / blood
  • Meningitis, Meningococcal / mortality*
  • Meningitis, Meningococcal / physiopathology
  • Meningococcal Infections / blood
  • Meningococcal Infections / mortality*
  • Meningococcal Infections / physiopathology
  • Multivariate Analysis
  • Platelet Count
  • Prognosis
  • Prospective Studies
  • Regression Analysis
  • Retrospective Studies
  • Sex Factors