Identify Drug-Resistant Pathogens in Patients with Community-Acquired Pneumonia

Community-acquired pneumonia: The importance of the early detection of drug-resistant organisms

Pneumonia is a disease associated with significant healthcare burden with over 1.5 million hospitalizations annually and is the eighth leading cause of death in the United States. While community-acquired pneumonia (CAP) is generally considered an acute time-limited illness, it is associated with high long-term mortality, with nearly one-third of patients requiring hospitalization dying within one year. An increasing trend of detecting multidrug-resistant (MDR) organisms causing CAP has been observed, especially in the Western world. In this editorial, we discuss about a publication by Jatteppanavar et al which reported that a case of a MDR organism was the culprit in developing pneumonia, bacteremia, and infective endocarditis that led to the patient's death. The early detection of these resistant organisms helps improve patient outcomes. Significant advances have been made in the biotechnological and research space, but preventive measures, diagnostic techniques, and treatment strategies need to be developed.

Development of an enzyme-linked phage receptor-binding protein assay (ELPRA) based on a novel biorecognition molecule- receptor-binding protein Gp130 of Pseudomonas aeruginosa bacteriophage Henu5

Pseudomonas aeruginosa is a Gram-negative bacterium associated with life-threatening healthcare-associated infections (HAIs), including burn wound infections, pneumonia and sepsis. Moreover, P. aeruginosa has been considered a pathogen of global concern due to its rising antibiotic resistance. Efficient identification of P. aeruginosa would significantly benefit the containment of bacterial infections, prevent pathogen transmission, and provide orientated treatment options. The accuracy and specificity of bacterial detection are primarily dictated by the biorecognition molecules employed. Lytic bacteriophages (or phages) could specifically attach to and lyse host bacterial cells. Phages' host specificity is typically determined by their receptor-binding proteins (RBPs), which recognize and adsorb phages to particular bacterial host receptors. This makes RBPs promising biorecognition molecules in bacterial detection. This study identified a novel RBP (Gp130) from the P. aeruginosa phage Henu5. A modified enzyme-linked phage receptor-binding protein assay (ELPRA) was developed for P. aeruginosa detection employing Gp130 as biorecognition molecules. Optimized conditions provided a calibration curve for P. aeruginosa with a range from 1.0 × 103 to 1.0 × 107 CFU/mL, with a limit of detection as low as 10 CFU/mL in phosphate-buffered saline (PBS). With VITEKⓇ 2 Compact system identification (40 positives and 21 negatives) as the gold standard, the sensitivity of ELPRA was 0.950 (0.818-0.991), and the specificity was 0.905 (0.682-0.983) within a 95 %confidence interval. Moreover, the recovery test in spiked mouse serum showed recovery rates ranging from 82.79 %to 98.17%, demonstrating the prospect of the proposed ELPRA for detecting P. aeruginosa in biological samples.

Risk of Multidrug-Resistant Pathogens in Severe Community-Acquired Pneumonia

Severe community-acquired pneumonia (SCAP) is difficult to treat when caused by difficult-to-treat (DTR) pathogens because of limited treatment options and poorer clinical outcomes. Over time, several predictive scoring systems based on risk factors for infection with multidrug resistant pathogens have been developed. We reviewed the available tools for identifying DTR pathogens as the cause of SCAP, both predictive scoring systems and rapid diagnostic methods, to develop management strategies aimed at early identification of DTR pathogens, reducing broad-spectrum antibiotic use and improving clinical outcomes. The scoring systems reviewed show considerable heterogeneity among them at the level of the region studied, the definition of risk factors, as well as which DTR pathogens are the target pathogens. The models described have shown limited effectiveness in reducing inappropriate antibiotic treatment or improving patient outcomes by themselves. However, predictive models could serve as a first step in identifying DTR pathogen infections as part of a larger detection algorithm. Rapid diagnostic tools, such as multiplex polymerase chain reaction, would be useful for the rapid identification of pneumonia-causing pathogens and their resistance mechanisms. In resource-limited settings, rapid tests should be limited to patients at high risk of developing SCAP due to DTR pathogens. We propose an integrative algorithm based on the different scores, taking into account local epidemiological data, where ideally each center should have an antimicrobial stewardship program.

Ten Issues for Updating in Community-Acquired Pneumonia: An Expert Review

Community-acquired pneumonia represents the third-highest cause of mortality in industrialized countries and the first due to infection. Although guidelines for the approach to this infection model are widely implemented in international health schemes, information continually emerges that generates controversy or requires updating its management. This paper reviews the most important issues in the approach to this process, such as an aetiologic update using new molecular platforms or imaging techniques, including the diagnostic stewardship in different clinical settings. It also reviews both the Intensive Care Unit admission criteria and those of clinical stability to discharge. An update in antibiotic, in oxygen, or steroidal therapy is presented. It also analyzes the management out-of-hospital in CAP requiring hospitalization, the main factors for readmission, and an approach to therapeutic failure or rescue. Finally, the main strategies for prevention and vaccination in both immunocompetent and immunocompromised hosts are reviewed.

Predictors of Length of Stay, Rehospitalization and Mortality in Community-Acquired Pneumonia Patients: A Retrospective Cohort Study

BACKGROUND

Community-acquired pneumonia (CAP) represents one of the leading causes of hospitalization and has a substantial impact on the financial burden of healthcare. The aim of this study was to identify factors associated with the length of hospital stay (LOHS), rehospitalization and mortality of patients admitted for CAP.

METHODS

A retrospective cohort study was conducted with patients presenting to a Swiss public hospital between January 2019 and December 2019. Zero-truncated negative binomial and multivariable logistic regression analyses were performed to assess risk factors.

RESULTS

A total of 300 patients were analyzed (median 78 years, IQR [67.56, 85.50] and 53% males) with an average LOHS of 7 days (IQR [5.00, 9.00]). Of the 300 patients, 31.6% (97/300) were re-hospitalized within 6 months, 2.7% (8/300) died within 30 days and 11.7% (35/300) died within 1 year. The results showed that sex (IRR = 0.877, 95% CI = 0.776-0.992, p-value = 0.036), age (IRR = 1.007, 95% CI = 1.002-1.012, p-value = 0.003), qSOFA score (IRR = 1.143, 95% CI = 1.049-1.246, p-value = 0.002) and atypical pneumonia (IRR = 1.357, 95% CI = 1.012-1.819, p-value = 0.04) were predictive of LOHS. Diabetes (OR = 2.149, 95% CI = 1.104-4.172, p-value = 0.024), a higher qSOFA score (OR = 1.958, 95% CI = 1.295-3.002, p-value = 0.002) and rehabilitation after discharge (OR = 2.222, 95% CI = 1.017-4.855, p-value = 0.044) were associated with a higher chance of being re-hospitalized within 6 months, whereas mortality within 30 days and within one year were both associated with older age (OR = 1.248, 95% CI = 1.056-1.562, p-value = 0.026 and OR = 1.073, 95% CI = 1.025-1.132, p-value = 0.005, respectively) and the presence of a cancer diagnosis (OR = 32.671, 95% CI = 4.787-369.1, p-value = 0.001 and OR = 4.408, 95% CI = 1.680-11.43, p-value = 0.002, respectively).

CONCLUSION

This study identified routinely available predictors for LOHS, rehospitalization and mortality in patients with CAP, which may further advance our understanding of CAP and thereby improve patient management, discharge planning and hospital costs.