Usefulness of business intelligence to guide antimicrobial treatment decision in infections by infrequent microorganism such as Bordetella bronchiseptica

Introduction

Bordetella bronchiseptica is an aerobic, gram-negative coccobacillus that displays tropism for the respiratory tract of animals such as dogs, cats, pigs, rabbits, and horses. It causes tracheobronchitis or “kennel cough” in dogs, atrophic rhinitis in pigs, and snuffles in rabbits [1]. Typically, B. bronchiseptica infections in humans are uncommon and are considered zoonotic [1]. However, in recent years reports of B. bronchiseptica infections in humans have increased, especially respiratory tract infections (RTI) [2–10], but also in severe infections such as bacteremia [11,12] and meningitis [13,14]. The antimicrobial treatment of B. bronchiseptica infections is empirical most of the time. Neither the Clinical and Laboratory Standards Institute (CLSI) nor the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has established specific breakpoints for the antibiotics commonly used to treat these types of infections in humans. Thus, despite the increasing numbers of reports of B. bronchiseptica infections, there is a lack of guidance on the most effective treatment options. Business intelligence (BI) is an emerging tool that allows one to collect, store, and analyze data in a very short time. This type of data-driven system has already been used in Emergency Medical Services during the COVID-19 pandemic, with good results [15]. Focusing on infectious diseases, BI is a promising tool, as it could facilitate the creation of cumulative antibiograms for infections caused by infrequently isolated microorganisms, where no standardized treatment is available. Thus, the aim of this study was to describe 13 clinical cases of B. bronchiseptica RTI and how a BI system could optimize the antimicrobial treatment in these patients.

Material and methods 

Study design, patients and ethics We conducted a retrospective study between 2018 and 2023 at University Hospital Virgen del Rocío (Seville, Spain). All consecutive adult patients (≥18 years) with positive respiratory cultures by B. bronchiseptica were included in the study. The study was approved by the Ethics Committee of University Hospital Virgen del Rocío, Seville (approval number 1180-N-21). Business Intelligence and microbiological data Demographics and microbiological data were collected using MicroBI (Beckman Coulter, Spain), a Business Intelligence-based system which automatically obtains and analyzes data from the laboratory information system (LIS). MicroBI uses associative database engine, converting raw data into user-friendly dashboards where selection and filtering capabilities transform information into actionable knowledge. In addition, it allows to obtain statistical and epidemiological information, providing a positive impact on the quality and insight that the microbiology laboratory provides to improve the patient care. The tool provides multiple key resources, including bacterial incidence, sensitivity reports, temporal trends, distribution data, cumulative graphs, real-time epidemiological information, drug combination behavior, MIC₅₀ and MIC₉₀ reports, patient outcomes, and a conceptual mapping system.  A search was performed for microbiological isolates of B. bronchiseptica from 2018 to 2023. Positive results were analyzed, and MIC₅₀ and MIC₉₀ values were automatically calculated using MicroBI for the following previously tested antibiotic: ampicillin, piperacillin, ampicillin/sulbactam, amoxicillin/clavulanic acid, piperacillin/tazobactam, cefuroxime, cefotaxime, ceftazidime, cefepime, aztreonam, imipenem, meropenem, gentamycin, tobramycin, amikacin, ciprofloxacin, levofloxacin, tetracycline, doxycycline, and tigecycline. In all cases, MICs were determined using MicroScan Walkaway panels (Beckman Coulter, USA). Clinical data  The following variables were collected from patients’ medical records: age, sex, comorbidities, toxic habits, presence of bacterial coinfection, antimicrobial treatment received for the B. bronchiseptica infection episode, and patient outcome.

Results

Thirteen positive cultures for B. bronchiseptica were initially identified by the MicroBI system, belonging to 13 patients admitted to University Hospital Virgen del Rocío (Seville, Spain). All isolates were from respiratory samples, specifically sputum [n=8], bronchial aspirate (n=3), pharyngeal exudate (n=1)] and bronchoalveolar lavage (n=1). In all cases, the identification of B. bronchiseptica was performed using MALDI-TOF mass spectrometry. A score higher than 1.8 was considered adequate. Demographic and clinical data of these patients are summarized in Table 1. The median age was 56 years (range 51-61) and 9 (69%) were men. Regarding comorbidities, all patients had risk factors for B. bronchiseptica infection, such as lung diseases (9/13, 69.2%) or HIV (3/13, 23%). It would be interesting to have information on whether the patient had intimate contact with pets, but it is not specified in any of their medical records. Regarding treatment, 11 of the 13 patients received antibiotics to treat B. bronchiseptica infection. The antibiotics used varied significantly (Table 1). Remarkably, 4 patients (30.8%) died. Using BI, we calculated MIC₅₀ and MIC₉₀ values (Table 2). The lowest MIC₉₀ in our isolates was for imipenem (1 mg/L), meropenem (1 mg/L), gentamicin (4 mg/L), tobramycin (4 mg/L), ciprofloxacin (1 mg/L), levofloxacin (1 mg/L), tetracycline (4 mg/L) and minocycline (4 mg/L). In contrast, the highest MIC₉₀ was for cefotaxime (64-128 mg/L). The rest of the antibiotics such as penicillins, amoxicillin/clavulanic acid, cefuroxime, ceftazidime, cefepime and aztreonam had variable MICs_50/90 value (Table 2). Since there are no specific clinical breakpoints for B. bronchiseptica, we decided to use the PK-PD (non-species related) breakpoints according to the EUCAST [16]. According to these cut-off points, piperacillin/tazobactam, imipenem and meropenem would be the only appropriate antimicrobials for the treatment of B. bronchiseptica infections in our cases.

Discussion

This study analyzes the clinical and microbiological characteristics of a cohort of patients with B. bronchiseptica infections, focusing on how the BI-based systems could help guide antimicrobial therapy appropriately. The patients included were mainly men, and the majority had some type of immunosuppression (AIDS, neoplasia, solid organ transplantation, diabetes mellitus) associated with B. bronchiseptica infections.  Treatment of infections by these infrequently isolated microorganisms is sometimes problematic due to the absence of specific guidelines to guide antibiotic therapy. Several studies have reported the antibiotic treatment decision based on isolate MICs [7,8,13], some of them reporting susceptibility/resistance categorization. However, none of them specify any guidance document.  Based on the MIC₅₀ and MIC₉₀ values obtained, piperacillin/tazobactam, imipenem and meropenem could be the best option to be used as empirical treatment in patients with B. bronchiseptica infections in our hospital, according to the microbiological criteria of susceptibility/resistance based on PK/PD (EUCAST) [16]. However, it is crucial to emphasize that, particularly for low-prevalence microorganisms, the small sample size imposes limitations that require careful interpretation of the results. Although representativeness may be limited and MIC values potentially affected by outliers, even a small dataset can offer valuable insights to inform therapeutic decisions in the context of rare microorganisms. Furthermore, in line with our results, a recent study carried out in northern Spain, García-de la fuente et al. [17] reported low MIC₉₀ to imipenem (2 mg/L) and meropenem (0.5 mg/L), although piperacillin/tazobactam was not tested. However, it is important to consider that our results could not be extrapolated to other centers and more studies are necessary to define global clinical breakpoints to B. bronchiseptica. In the case of B. bronchiseptica, a microorganism with low prevalence in human infections but significant in certain clinical contexts (e.g., immunocompromised patients or individuals exposed to animals), the use of BI systems connected to the Laboratory Information System (LIS) is particularly advantageous. These systems can maximize the utility of limited data and uncover patterns that might be difficult to identify manually. Because low-prevalence microorganisms often involve a small number of isolates within a laboratory, traditional methods may fall short in assessing antibiotic susceptibility, resistance trends, or epidemiological correlations. BI systems overcome these challenges by enabling multivariate and contextualized analyses, even with minimal datasets. From a technical standpoint, BI systems integrate diverse data sources, including phenotypic and clinical information, to construct a comprehensive microbiological profile. For B. bronchiseptica, these systems can detect variations in resistance patterns linked to factors such as sample type (e.g., respiratory, blood), patient antibiotic history, or associations with zoonotic infections. Furthermore, BI systems employ advanced methods, such as frequency distribution analysis, to accurately calculate metrics like MIC₅₀ and MIC₉₀, even with limited isolate numbers, while also identifying outliers that may signal emerging resistance mechanisms or laboratory inconsistencies. Automated comparisons with national and international databases, such as those provided by EUCAST or CLSI, contextualize local susceptibility data for B. bronchiseptica against global trends. This helps to identify discrepancies that may reflect unique geographical or epidemiological factors. Such functionality is particularly valuable for low-prevalence microorganisms, where global data are often insufficient for guiding local decisions. BI systems also enable longitudinal monitoring of resistance patterns, making it possible to detect increases in B. bronchiseptica infections or the emergence of novel resistance profiles that require adjustments to empirical treatment protocols.  In conclusion, MicroBI is a promising tool in Clinical Microbiology services that will help combat infections caused by infrequent microorganisms such as B. bronchiseptica, reducing the probabilities of therapeutic failures. Funding A.R.V. is supported by the Juan Rodés Subprogram, Instituto de Salud Carlos III, Subdirección General de Redes y Centros de Investigación Cooperativa, Ministerio de Ciencia, Innovación y Universidades, Spain (JR20/00023). Conflict of interest Authors declare no have conflict of interest. Authors contributions Conceptualization, A.R.V.; methodology, R.D.J.; formal analysis, M.V.H.A. and A.R.V.; writing—original draft preparation, M.V.H.A. and A.R.V.; writing—review and editing, J.A.L. All authors have read and agreed to the published version of the manuscript.

References

1. Woolfrey BF, Moody JA. Human infections associated with Bordetella bronchiseptica. Clin Microbiol Rev. 1991;4(3):243-55. https://doi.org/10.1128/CMR.4.3.243.
2. Lorenzo-Pajuelo B, Villanueva JL, Rodríguez-Cuesta J, Vergara-Irigaray N, Bernabeu-Wittel M, Garcia-Curiel A, Martínez de Tejada G. Cavitary pneumonia in an AIDS patient caused by an unusual Bordetella bronchiseptica variant producing reduced amounts of pertactin and other major antigens. J Clin Microbiol. 2002;40(9):3146-54. https://doi.org/10.1128/JCM.40.9.3146-3154.2002.
3. Dlamini NR, Bhamjee A, Levick P, Uniacke E, Ismail H, Smith A. Spontaneous bacterial peritonitis and pneumonia caused by Bordetella bronchiseptica. J Infect Dev Ctries. 2012;6(7):588-91. https://doi.org/10.3855/jidc.2074.
4. Bhargava A, Eisenstadt R, Shih JA, Sueblinvong V. A Good Case of Recurrent Pneumonia. J Investig Med High Impact Case Rep. 2018;6:2324709618802869. https://doi.org/10.1177/2324709618802869.
5. Karamooz E, Yap VL, Barker AF, Metersky ML. Bordetella bronchiseptica in non-cystic fibrosis bronchiectasis. Respir Med Case Rep. 2018;25:187-188. https://doi.org/10.1016/j.rmcr.2018.08.023.
6. Gupta S, Goyal P, Mattana J. Bordetella bronchiseptica pneumonia a thread in the diagnosis of human immunodeficiency virus infection. IDCases. 2019;15:e00509. https://doi.org/10.1016/j.idcr.2019.e00509.
7. Monti M, Diano D, Allegrini F, Delmonte A, Fausti V, Cravero P, Marcantognini G, Frassineti GL. Bordetella bronchiseptica pneumonia in a patient with lung cancer; a case report of a rare infection. BMC Infect Dis. 2017;17(1):644. https://doi.org/10.1186/s12879-017-2736-7.
8. Woods P, Ordemann K, Stanecki C, Brown J, Uzodi A. Bordetella bronchiseptica Pneumonia in an Adolescent: Case Report and Review of the Pediatric Literature. Clin Pediatr (Phila). 2020;59(3):322-328. https://doi.org/10.1177/0009922819897355.
9. Clements J, McGrath C, McAllister C. Bordetella bronchiseptica pneumonia: beware of the dog! BMJ Case Rep. 2018;2018:bcr2018224588. https://doi.org/10.1136/bcr-2018-224588.
10. Sameed M, Sullivan S, Marciniak ET, Deepak J. Chronic cough and cystic lung disease caused by Bordetella bronchiseptica in a patient with AIDS. BMJ Case Rep. 2019;12(4):e228741. https://doi.org/10.1136/bcr-2018-228741.
11. Chan KH, Ajao SO, Farouji I, Slim J. A Case of Bordetella bronchiseptica Bacteremia in a Patient With Decompensated Liver Cirrhosis. Cureus. 2021;13(3):e13938. https://doi.org/10.7759/cureus.13938.
12. Powers HR, Shah K. Bordetella bronchiseptica bloodstream infection in a renal transplant patient. Transpl Infect Dis. 2017;19(6). https://doi.org/10.1111/tid.12774.
13. Radcliffe C, Lier A, Doilicho N, Parikh S, Kaddouh F. Bordetella bronchiseptica: a rare cause of meningitis. BMC Infect Dis. 2020;20(1):922. https://doi.org/10.1186/s12879-020-05668-2.
14. Belen O, Campos JM, Cogen PH, Jantausch BA. Postsurgical meningitis caused by Bordetella bronchiseptica. Pediatr Infect Dis J. 2003;22(4):380-1.
15. Sechi GM, Migliori M, Dassi G, Pagliosa A, Bonora R, Oradini-Alacreu A, Odone A, Signorelli C, Zoli A, Response Team AC. Business Intelligence applied to Emergency Medical Services in the Lombardy region during SARS-CoV-2 epidemic. Acta Biomed. 2020;91(2):39-44. https://doi.org/10.23750/abm.v91i2.9557.
16. The European Committee on Antimicrobial Susceptibility Testing. Breakpoint tables for interpretation of MICs and zone diameters. EUCAST; 2021. https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/v_11.0_Breakpoint_Tables.pdf
17. García-de-la-Fuente C, Guzmán L, Cano ME, Agüero J, Sanjuán C, Rodríguez C, Aguirre A, Martínez-Martínez L. Microbiological and clinical aspects of respiratory infections associated with Bordetella bronchiseptica. Diagn Microbiol Infect Dis. 2015;82(1):20-5. https://doi.org/10.1016/j.diagmicrobio.2015.01.011.