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Peer-reviewedCC BY-NC-ND 4.0Clinical infectious diseases : an official publication of the Infectious Diseases Society of America

Development and Application of an Anaerobic Activity Index

  • Natalie A. Mackow1,2,3
  • Lauren Komarow4
  • Sonia Napravnik3
  • Tessa M. Andermann3,5
  • Luther Bartelt3,6,5
  • Lauren M. DiBiase7
  • Billy Williams8
  • Felicia N. Williams9,10
  • Vincent B. Young11,12
  • David M. Aronoff13
  • David J. Weber3,7
  • Rishi Chanderraj11,14
1 more authors
  • David van Duin3,6
14 affiliations
  1. 1Division of Infectious Diseases, Department of Medicine, Renaissance School of Medicine at Stony Brook University, Stony Brook, New York, USA
  2. 2Department of Infection Prevention and Control, Stony Brook University Hospital, Stony Brook, New York, USA
  3. 3Division of Infectious Diseases, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
  4. 4Biostatistics Center, George Washington University, Rockville, Maryland, USA
  5. 5Center for Gastrointestinal Biology and Diseases, Division of Gastroenterology, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
  6. 6Department of Microbiology and Immunology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
  7. 7Department of Infection Prevention, University of North Carolina Medical Center, Chapel Hill, North Carolina, USA
  8. 8Clinical Microbiology Laboratory, University of North Carolina Hospitals, Chapel Hill, North Carolina, USA
  9. 9Department of Surgery, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
  10. 10North Carolina Jaycee Burn Center, University of North Carolina, Chapel Hill, North Carolina, USA
  11. 11Department of Internal Medicine/Infectious Diseases Division, University of Michigan Medical School, Ann Arbor, Michigan, USA
  12. 12Department of Microbiology & Immunology, University of Michigan Medical School, Ann Arbor, Michigan, USA
  13. 13Division of Infectious Diseases, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
  14. 14Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor, Michigan, USA
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Abstract

Background.: Antibiotics with anaerobic activity may result in adverse patient outcomes. Here, we report the development and application of an Anaerobic Activity Index (AAI) to quantify antianaerobic antibiotic exposure.

Methods.: The numeric AAI was generated for 21 antibiotics using in vitro susceptibility data for 7 anaerobic bacterial groups. A binning strategy was applied to susceptibility proportions to result in the fewest antibiotic tied scores. In a cohort of patients with burns, 7-day anaerobic exposure was calculated, multiplied by days of therapy, and summed. Multivariable logistic regression models assessed the association between AAI quartiles and a 90-day composite outcome including culture positivity with bacteria of interest, healthcare-associated infection, and/or death.

Results.: We included 88 papers reporting on anaerobic activity. The AAI ranged from 4 to 59. Meropenem (59), ertapenem (58), and tigecycline (57) were the highest ranked antibiotics, whereas penicillin (20), doxycycline (13), and aztreonam (4) had the lowest scores. Several antibiotics could not be included for lack of data. In a cohort of patients with burns, the highest 7-day AAI quartile was associated with increased odds of the 90-day composite outcome compared with the lowest quartile (OR: 2.90; 95% CI: 1.65–5.08), adjusting for Baux score and Charlson comorbidity index.

Conclusions.: We propose an Anaerobic Activity Index (AAI) assigning numeric scores to commonly used antibiotics. We anticipate that this score will require updating as additional susceptibility data become available. The AAI may be used as a research tool evaluating the impact of antianaerobic antibiotics on patient outcomes.

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Cite

BibTeXRIS
BibTeX
@article{mackow2026development,
  title = {{Development and Application of an Anaerobic Activity Index}},
  author = {Natalie A. Mackow and Lauren Komarow and Sonia Napravnik and Tessa M. Andermann and Luther Bartelt and Lauren M. DiBiase and Billy Williams and Felicia N. Williams and Vincent B. Young and David M. Aronoff and David J. Weber and Rishi Chanderraj and David van Duin},
  journal = {Clinical infectious diseases : an official publication of the Infectious Diseases Society of America},
  year = {2026},
  month = aug,
  doi = {10.1093/cid/ciag470},
  url = {https://doi.org/10.1093/cid/ciag470},
  note = {CC BY-NC-ND 4.0},
}
RIS
TY  - JOUR
TI  - Development and Application of an Anaerobic Activity Index
AU  - Natalie A. Mackow
AU  - Lauren Komarow
AU  - Sonia Napravnik
AU  - Tessa M. Andermann
AU  - Luther Bartelt
AU  - Lauren M. DiBiase
AU  - Billy Williams
AU  - Felicia N. Williams
AU  - Vincent B. Young
AU  - David M. Aronoff
AU  - David J. Weber
AU  - Rishi Chanderraj
AU  - David van Duin
PY  - 2026
DA  - 2026/08/04
JO  - Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
DO  - 10.1093/cid/ciag470
UR  - https://doi.org/10.1093/cid/ciag470
AB  - Background.: Antibiotics with anaerobic activity may result in adverse patient outcomes. Here, we report the development and application of an Anaerobic Activity Index (AAI) to quantify antianaerobic antibiotic exposure.  Methods.: The numeric AAI was generated for 21 antibiotics using in vitro susceptibility data for 7 anaerobic bacterial groups. A binning strategy was applied to susceptibility proportions to result in the fewest antibiotic tied scores. In a cohort of patients with burns, 7-day anaerobic exposure was calculated, multiplied by days of therapy, and summed. Multivariable logistic regression models assessed the association between AAI quartiles and a 90-day composite outcome including culture positivity with bacteria of interest, healthcare-associated infection, and/or death.  Results.: We included 88 papers reporting on anaerobic activity. The AAI ranged from 4 to 59. Meropenem (59), ertapenem (58), and tigecycline (57) were the highest ranked antibiotics, whereas penicillin (20), doxycycline (13), and aztreonam (4) had the lowest scores. Several antibiotics could not be included for lack of data. In a cohort of patients with burns, the highest 7-day AAI quartile was associated with increased odds of the 90-day composite outcome compared with the lowest quartile (OR: 2.90; 95% CI: 1.65–5.08), adjusting for Baux score and Charlson comorbidity index.  Conclusions.: We propose an Anaerobic Activity Index (AAI) assigning numeric scores to commonly used antibiotics. We anticipate that this score will require updating as additional susceptibility data become available. The AAI may be used as a research tool evaluating the impact of antianaerobic antibiotics on patient outcomes.
SN  - 1058-4838
SN  - 1537-6591
ER  -