Nathan Kuppermann1, Peter S Dayan2, Deborah A Levine3, Melissa Vitale4, Leah Tzimenatos5, Michael G Tunik3, Mary Saunders6,7, Richard M Ruddy8,9, Genie Roosevelt10, Alexander J Rogers11, Elizabeth C Powell12, Lise E Nigrovic13, Jared Muenzer14,15, James G Linakis16,17, Kathleen Grisanti18, David M Jaffe14, John D Hoyle19,20, Richard Greenberg21, Rajender Gattu22, Andrea T Cruz23, Ellen F Crain24, Daniel M Cohen25,26, Anne Brayer27, Dominic Borgialli28,29, Bema Bonsu25,26, Lorin Browne30, Stephen Blumberg24, Jonathan E Bennett31, Shireen M Atabaki32, Jennifer Anders33, Elizabeth R Alpern34,35, Benjamin Miller36, T Charles Casper36, J Michael Dean36, Octavio Ramilo26,37, Prashant Mahajan38,39. 1. Departments of Emergency Medicine and Pediatrics, University of California, Davis School of Medicine, Sacramento. 2. Division of Emergency Medicine, Department of Pediatrics, Columbia University College of Physicians and Surgeons, New York, New York. 3. Department of Pediatrics, Bellevue Hospital, New York University Langone Medical Center, New York, New York. 4. Division of Emergency Medicine, Department of Pediatrics, Children's Hospital of Pittsburgh, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania. 5. Department of Emergency Medicine, University of California, Davis School of Medicine, Sacramento. 6. Department of Pediatrics, Children's Hospital of Wisconsin, Medical College of Wisconsin, Milwaukee. 7. Children's Hospital of Colorado, University of Colorado School of Medicine, Aurora. 8. Division of Emergency Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio. 9. Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio. 10. Department of Pediatrics, The Colorado Children's Hospital, University of Colorado, Denver. 11. Departments of Emergency Medicine and Pediatrics, University of Michigan School of Medicine, Ann Arbor. 12. Division of Emergency Medicine, Department of Pediatrics, Ann & Robert H. Lurie Children's Hospital, Northwestern University Feinberg School of Medicine, Chicago, Illinois. 13. Division of Emergency Medicine, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts. 14. Division of Emergency Medicine, Department of Pediatrics, St Louis Children's Hospital, Washington University, St Louis, Missouri. 15. Division of Emergency Medicine, Phoenix Children's Hospital, Phoenix, Arizona. 16. Department of Emergency Medicine and Pediatrics, Hasbro Children's Hospital, Providence, Rhode Island. 17. Brown University School of Medicine, Providence, Rhode Island. 18. Department of Pediatrics, Women and Children's Hospital of Buffalo, State University of New York at Buffalo School of Medicine. 19. Department of Emergency Medicine, Helen DeVos Children's Hospital of Spectrum Health, Grand Rapids, Michigan. 20. Departments of Emergency Medicine and Pediatrics, Western Michigan University Homer Stryker MD School of Medicine, Kalamazoo. 21. Division of Emergency Medicine, Department of Pediatrics, Primary Children's Medical Center, University of Utah, Salt Lake City. 22. Division of Emergency Medicine, Department of Pediatrics, University of Maryland Medical Center, Baltimore. 23. Sections of Emergency Medicine and Infectious Diseases, Department of Pediatrics, Texas Children's Hospital, Baylor College of Medicine, Houston. 24. Department of Pediatrics, Jacobi Medical Center, Albert Einstein College of Medicine, Bronx, New York. 25. Division of Emergency Medicine, Department of Pediatrics, Nationwide Children's Hospital, Columbus, Ohio. 26. The Ohio State University School of Medicine, Columbus. 27. Departments of Emergency Medicine and Pediatrics, University of Rochester Medical Center, Rochester, New York. 28. Department of Emergency Medicine, Hurley Medical Center, Flint, Michigan. 29. University of Michigan School of Medicine, Ann Arbor. 30. Departments of Pediatrics and Emergency Medicine, Children's Hospital of Wisconsin, Medical College of Wisconsin, Milwaukee. 31. Division of Emergency Medicine, Alfred I. duPont Hospital for Children, Nemours Children's Health System, Thomas Jefferson School of Medicine, Wilmington, Delaware. 32. Division of Emergency Medicine, Department of Pediatrics, Children's National Medical Center, The George Washington School of Medicine and Health Sciences, Washington, DC. 33. Department of Pediatrics, Johns Hopkins University, Baltimore, Maryland. 34. Division of Emergency Medicine, Department of Pediatrics, Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia. 35. Ann and Robert H. Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine, Chicago, Illinois. 36. Department of Pediatrics, University of Utah School of Medicine, Salt Lake City. 37. Division of Pediatric Infectious Diseases and Center for Vaccines and Immunity, Nationwide Children's Hospital, Columbus, Ohio. 38. Division of Emergency Medicine, Department of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit, Michigan. 39. Department of Emergency Medicine, University of Michigan School of Medicine, Ann Arbor.
Abstract
Importance: In young febrile infants, serious bacterial infections (SBIs), including urinary tract infections, bacteremia, and meningitis, may lead to dangerous complications. However, lumbar punctures and hospitalizations involve risks and costs. Clinical prediction rules using biomarkers beyond the white blood cell count (WBC) may accurately identify febrile infants at low risk for SBIs. Objective: To derive and validate a prediction rule to identify febrile infants 60 days and younger at low risk for SBIs. Design, Setting, and Participants: Prospective, observational study between March 2011 and May 2013 at 26 emergency departments. Convenience sample of previously healthy febrile infants 60 days and younger who were evaluated for SBIs. Data were analyzed between April 2014 and April 2018. Exposures: Clinical and laboratory data (blood and urine) including patient demographics, fever height and duration, clinical appearance, WBC, absolute neutrophil count (ANC), serum procalcitonin, and urinalysis. We derived and validated a prediction rule based on these variables using binary recursive partitioning analysis. Main Outcomes and Measures: Serious bacterial infection, defined as urinary tract infection, bacteremia, or bacterial meningitis. Results: We derived the prediction rule on a random sample of 908 infants and validated it on 913 infants (mean age was 36 days, 765 were girls [42%], 781 were white and non-Hispanic [43%], 366 were black [20%], and 535 were Hispanic [29%]). Serious bacterial infections were present in 170 of 1821 infants (9.3%), including 26 (1.4%) with bacteremia, 151 (8.3%) with urinary tract infections, and 10 (0.5%) with bacterial meningitis; 16 (0.9%) had concurrent SBIs. The prediction rule identified infants at low risk of SBI using a negative urinalysis result, an ANC of 4090/µL or less (to convert to ×109 per liter, multiply by 0.001), and serum procalcitonin of 1.71 ng/mL or less. In the validation cohort, the rule sensitivity was 97.7% (95% CI, 91.3-99.6), specificity was 60.0% (95% CI, 56.6-63.3), negative predictive value was 99.6% (95% CI, 98.4-99.9), and negative likelihood ratio was 0.04 (95% CI, 0.01-0.15). One infant with bacteremia and 2 infants with urinary tract infections were misclassified. No patients with bacterial meningitis were missed by the rule. The rule performance was nearly identical when the outcome was restricted to bacteremia and/or bacterial meningitis, missing the same infant with bacteremia. Conclusions and Relevance: We derived and validated an accurate prediction rule to identify febrile infants 60 days and younger at low risk for SBIs using the urinalysis, ANC, and procalcitonin levels. Once further validated on an independent cohort, clinical application of the rule has the potential to decrease unnecessary lumbar punctures, antibiotic administration, and hospitalizations.
Importance: In young febrile infants, serious bacterial infections (SBIs), including urinary tract infections, bacteremia, and meningitis, may lead to dangerous complications. However, lumbar punctures and hospitalizations involve risks and costs. Clinical prediction rules using biomarkers beyond the white blood cell count (WBC) may accurately identify febrile infants at low risk for SBIs. Objective: To derive and validate a prediction rule to identify febrile infants 60 days and younger at low risk for SBIs. Design, Setting, and Participants: Prospective, observational study between March 2011 and May 2013 at 26 emergency departments. Convenience sample of previously healthy febrile infants 60 days and younger who were evaluated for SBIs. Data were analyzed between April 2014 and April 2018. Exposures: Clinical and laboratory data (blood and urine) including patient demographics, fever height and duration, clinical appearance, WBC, absolute neutrophil count (ANC), serum procalcitonin, and urinalysis. We derived and validated a prediction rule based on these variables using binary recursive partitioning analysis. Main Outcomes and Measures: Serious bacterial infection, defined as urinary tract infection, bacteremia, or bacterial meningitis. Results: We derived the prediction rule on a random sample of 908 infants and validated it on 913 infants (mean age was 36 days, 765 were girls [42%], 781 were white and non-Hispanic [43%], 366 were black [20%], and 535 were Hispanic [29%]). Serious bacterial infections were present in 170 of 1821 infants (9.3%), including 26 (1.4%) with bacteremia, 151 (8.3%) with urinary tract infections, and 10 (0.5%) with bacterial meningitis; 16 (0.9%) had concurrent SBIs. The prediction rule identified infants at low risk of SBI using a negative urinalysis result, an ANC of 4090/µL or less (to convert to ×109 per liter, multiply by 0.001), and serum procalcitonin of 1.71 ng/mL or less. In the validation cohort, the rule sensitivity was 97.7% (95% CI, 91.3-99.6), specificity was 60.0% (95% CI, 56.6-63.3), negative predictive value was 99.6% (95% CI, 98.4-99.9), and negative likelihood ratio was 0.04 (95% CI, 0.01-0.15). One infant with bacteremia and 2 infants with urinary tract infections were misclassified. No patients with bacterial meningitis were missed by the rule. The rule performance was nearly identical when the outcome was restricted to bacteremia and/or bacterial meningitis, missing the same infant with bacteremia. Conclusions and Relevance: We derived and validated an accurate prediction rule to identify febrile infants 60 days and younger at low risk for SBIs using the urinalysis, ANC, and procalcitonin levels. Once further validated on an independent cohort, clinical application of the rule has the potential to decrease unnecessary lumbar punctures, antibiotic administration, and hospitalizations.
Authors: Laura H Brower; Paria M Wilson; Eileen Murtagh-Kurowski; Joshua D Courter; Samir S Shah; Amanda C Schondelmeyer Journal: Hosp Pediatr Date: 2020-05-08
Authors: Lyubina C Yankova; Mark I Neuman; Marie E Wang; Christopher Woll; Adrienne G DePorre; Sanyukta Desai; Laura F Sartori; Lise E Nigrovic; Christopher M Pruitt; Richard D Marble; Rianna C Leazer; Sahar N Rooholamini; Fran Balamuth; Paul L Aronson Journal: Hosp Pediatr Date: 2020-12
Authors: Marie E Wang; Mark I Neuman; Lise E Nigrovic; Christopher M Pruitt; Sanyukta Desai; Adrienne G DePorre; Laura F Sartori; Richard D Marble; Christopher Woll; Rianna C Leazer; Fran Balamuth; Sahar N Rooholamini; Paul L Aronson Journal: Hosp Pediatr Date: 2020-12-14
Authors: Paul L Aronson; Paula Schaeffer; Linda M Niccolai; Eugene D Shapiro; Liana Fraenkel Journal: Pediatr Emerg Care Date: 2021-12-01 Impact factor: 1.454
Authors: Paul L Aronson; Mary C Politi; Paula Schaeffer; Eduardo Fleischer; Eugene D Shapiro; Linda M Niccolai; Elizabeth R Alpern; Steven L Bernstein; Liana Fraenkel Journal: Acad Emerg Med Date: 2020-09-09 Impact factor: 3.451