1. Roland C. Merchant, MD, MPH, ScD
Clinical Prediction Rule for Chlamydia and/or Gonorrhea Urethritis Among Adult Male Emergency Department Patients
Roland C. Merchant, MD, MPH, ScD
Dina M. DePalo, BA
Tao Liu, PhD
Josiah D. Rich, MD, MPH
Michael D. Stein, MD

2. Background
Males with signs and symptoms of urethritis frequently present to emergency departments (EDs) for medical care
No commercially-available rapid tests for chlamydia/gonorrhea
Empiric treatment vs. waiting for test results
CDC guidance on when to initiate empiric treatment for chlamydia and/or gonorrhea can lead to antibiotic overusage
Methods of limiting antibiotic usage to when it is indicated are needed to avoid antibiotic overusage, reduce antibiotic resistance, reduce costs, and avoid adverse reactions

3. Objectives
Create a clinical prediction rule for predicting laboratory-confirmed chlamydia and/or gonorrhea infections among adult male ED patients
Help ED clinicians determine when to begin antibiotic treatment empirically or defer antibiotics pending test results

4. Methods (1) Study design Study setting: Rhode Island Hospital ED
Retrospective study of adult male ED patients
Medical record and laboratory database review of patients diagnosed in the ED with a possible urethral infection prior to laboratory results of testing
Study setting: Rhode Island Hospital ED
Providence, Rhode Island
Level I trauma center and academic medical center affiliated with Brown University
>95,000 adult patient visits annually

5. Methods (2) Study participants
Adult (≥18 years-old) males whose ED clinician diagnosed them with possible chlamydia and/or gonorrhea urethritis
Exclusion criteria
Known chlamydia/gonorrhea
Repeat visits for the same infection
Did not have laboratory testing performed for chlamydia and/or gonorrhea
Urine ligase nucleic acid amplification tests (NAATS) for both chlamydia and gonorrhea

6. Methods (3) Data collection January 1998-December 2004
Hospital and ED provider billing record computerized databases were independently searched for subjects
Cases of interest to the study were identified using International Classification of Disease, 9th revision, Clinical Modification (ICD-9) codes
Captured visits from both databases
Medical records and laboratory databases reviewed for subjects identified for the study

7. Methods (4) Prediction rule construction
Selected demographic and clinical characteristics associated with the presence of a laboratory-confirmed infection
Best functional form of variables selected
Pearson’s χ2 testing
Likelihood ratios (LRs)
Logistic regression for odds ratios (ORs)
Receiver-operator characteristic (ROC) curve plots

8. Methods (5) Prediction rule construction (cont.)
Created a training dataset (75% of patients) and testing dataset (25%) by random assignment
Using the training dataset
Used multivariable logistic regression to establish the final components of the prediction rule
Grouped and ranked factors by their ability to identify the presence/absence of an infection
Established five hierarchical risk levels for the presence/absence of an infection
Internally validated the prediction rule using the testing dataset

9. Results (1) ICD-9 code search
1,218 ED visits identified and 1,166 (95.7%) could be reviewed
985 had a possible chlamydia/gonorrhea infection as diagnosed by the ED clinician
822 had chlamydia/gonorrhea testing
29.2% had chlamydia, gonorrhea, or both
13.8% had chlamydia alone
12.1% had gonorrhea alone
3.3% had both

10. Results (2)

11. Demographic Profiles

12. History of Present Illness Profiles

13. History of Known STD Contact Profiles

14. Demographic Variables

15. Symptoms and STD Contact History Variables

16. Prediction Rule for the Presence of a Chlamydia, Gonorrhea, or Both Infections

17. Prediction Rule for the Absence of a Chlamydia, Gonorrhea, or Both Infections

18. Predicted Probabilities of Infection by Baseline Prevalence Using the Prediction Rule
Plot A Plot B
Presence of an infection Absence of an infection
*DC=discharge, C/G contact=sexual contact with someone known to have chlamydia and/or gonorrhea
*Diagonal lines indicate when pre-test and post-test probability of infection are equal.
*Horizontal lines indicate when the post-test probability of infection is equal to chance

19. Conclusions and Implications
A combination of demographic and clinical factors can modestly assist ED clinicians in predicting which patients are more likely to have chlamydia/gonorrhea urethritis
Needs prospective, external validation
May help promote more effective empiric treatment

20. Questions