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Processing of Bronchoalveolar Lavage Fluid and Matched Blood for Alveolar Macrophage and CD4+ T-cell Immunophenotyping and HIV Reservoir Assessment
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[Pathogens and drug resistance of pulmonary infection in AIDS patients]

Ling-Hua Li1, Xiao-Ping Tang, Wei-Ping Cai

  • 1Department of Infectious Diseases, Guangzhou No.8 People's Hospital, Guangzhou 510060, China.

Zhonghua Nei Ke Za Zhi
|December 17, 2008
PubMed
Abstract

Insights

Pulmonary infections in AIDS patients are often caused by multiple drug-resistant bacteria and fungi. Rational antibiotic selection based on susceptibility testing is crucial for effective treatment.

Area of Science:

  • Infectious Diseases
  • Microbiology
  • Immunocompromised Hosts

Context:

  • Pulmonary infections are a significant cause of morbidity and mortality in patients with Acquired Immunodeficiency Syndrome (AIDS).
  • Understanding the spectrum of pathogens and their antimicrobial resistance patterns is essential for guiding clinical management.

Purpose:

  • To investigate the causative pathogens and antimicrobial resistance profiles of pulmonary infections in a cohort of 116 patients with AIDS.
  • To analyze the drug susceptibility of isolated bacterial and fungal strains.

Summary:

  • A study of 116 AIDS patients revealed that pulmonary infections are frequently polymicrobial (84.5%), involving bacteria, fungi, tubercle bacilli, Pneumocystis jiroveci, and cytomegalovirus.
  • Isolated bacteria exhibited resistance to common antibiotics, including beta-lactams, macrolides, quinolones, and aminoglycosides, with notable presence of methicillin-resistant Streptococci (MRS) and extended-spectrum beta-lactamases (ESBL) strains.
  • Fungal isolates, primarily Candida mycoderma, showed sensitivity to amphotericin B but resistance to fluconazole and itraconazole.

Impact:

  • The findings highlight the complex etiology of pneumonia in AIDS patients, emphasizing the prevalence of multidrug-resistant organisms.
  • Results underscore the critical need for empirical antibiotic therapy to be guided by local drug susceptibility data to optimize treatment outcomes and combat antimicrobial resistance.

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