Antibacterial Drug Use and Bacterial Resistance in Psychiatric Hospitals During the COVID-19 Epidemic

Study Background and Research Question

The ongoing COVID-19 pandemic has placed unprecedented stress on healthcare systems worldwide, with psychiatric hospitals facing unique challenges due to their patient populations and institutional structures. Patients in psychiatric settings are often at increased risk for infections because of impaired self-care, group living conditions, and immunosuppression related to both underlying disease and long-term psychotropic medication use. Previous World Health Organization (WHO) reports have indicated that approximately 8% of COVID-19 patients experience bacterial co-infections, highlighting the critical role of antibacterial therapy in clinical management (paper). However, global concern persists regarding the overuse and misuse of antibiotics, which accelerates the emergence of multi-drug-resistant organisms. Against this backdrop, Jiang et al. investigated the patterns of antibacterial drug use and the dynamics of bacterial resistance in a psychiatric hospital during the 2022 epidemic, aiming to provide evidence-based guidance for antimicrobial stewardship in these specialized settings.

Key Innovation from the Reference Study

The principal innovation of Jiang et al.'s work lies in its granular, retrospective analysis of antibiotic utilization and bacterial resistance specifically within a psychiatric hospital context during a pandemic year, leveraging both institutional data and national monitoring platforms. Unlike previous studies focused on general or acute-care hospitals, this study provides a focused assessment of rational antibiotic use and its direct relationship to resistance trends in a psychiatric population—a group often underrepresented in infection control research (paper). The high rate of microbiological submission for antibiotic use (77.78%) stands out as a best-practice benchmark, contrasting with lower rates both provincially and nationally, and suggests a model for evidence-driven prescribing.

Methods and Experimental Design Insights

Jiang et al. conducted a retrospective, cross-sectional analysis combining hospital-level data from the Affiliated Mental Health Center of Jiangnan University and province-wide and national datasets from the National Antibacterial Drug Clinical Application Monitoring Network. The study period encompassed the year 2022, coinciding with a significant wave of COVID-19. Key variables included:

• Antibiotic use rate and intensity (AUD)
• Combined medication rate
• Cumulative defined daily doses (DDDs) by drug type
• Proportion of antibiotic costs in total drug expenditures
• Microbiological submission rate for patients receiving antibiotics
• Distribution and resistance profiles of key bacterial pathogens

Data extraction employed the hospital information system for in-house samples and linked laboratory microbiology results with drug utilization metrics. Antibiotic types were classified according to cumulative DDDs, and susceptibility testing results provided quantitative resistance rates for both Gram-negative and Gram-positive organisms (paper).

Protocol Parameters

• antibiotic use rate | 5.00% | psychiatric hospital context | Demonstrates restrained and targeted antibiotic prescription during epidemic conditions | paper
• antibiotic usage intensity | 3.07 (unitless) | institutional benchmarking | Allows direct comparison with provincial and national norms | paper
• combined medication rate | 11.11% | infection risk management | Indicates frequency of multi-drug regimens, potentially reflecting complexity of infection cases | paper
• microbiological submission rate | 77.78% | stewardship quality assurance | Ensures most antibiotic prescriptions are guided by laboratory evidence | paper
• cumulative antibiotic DDDs | 12,039.04 | annual institutional consumption | Standardized measure for cross-institutional comparisons | paper
• antibiotic cost proportion | 3.95% | pharmaceutical budgeting | Reflects economic impact of antibiotic use within the hospital drug budget | paper

Core Findings and Why They Matter

Jiang et al. found that the psychiatric hospital demonstrated an antibiotic use rate (5.00%) and cost proportion (3.95%) substantially lower than both the provincial and national averages, suggesting a high level of stewardship and rational use despite the increased infection risk posed by the pandemic (paper). The most frequently used antibiotics were third-generation cephalosporins, penicillins, and quinolones, with cefodizime, amoxicillin, and piperacillin–tazobactam being the top choices. Notably, the rate of microbiological submission for antibiotic use was 77.78%, well above broader benchmarks. This high submission rate is critical for ensuring that antimicrobial therapy is targeted and evidence-based, reducing unnecessary exposure and selective pressure that drives resistance. Nevertheless, the study also documented rising resistance rates among both Gram-negative and Gram-positive bacteria. Specifically, Gram-negative isolates showed resistance to penicillins, cephalosporins, and quinolones (notably ampicillin, amoxicillin–clavulanic acid, ceftazidime, ceftriaxone, amikacin, and ciprofloxacin), while Gram-positive isolates were resistant to penicillins, macrolides, and quinolones (notably penicillin, benzylpenicillin, erythromycin, levofloxacin, and ciprofloxacin). The findings underscore the delicate balance between necessary infection control in vulnerable psychiatric populations and the risk of fostering antimicrobial resistance. The authors recommend regular surveillance, resistance data analysis, and ongoing stewardship interventions to maintain clinical efficacy and minimize the public health threat posed by resistant pathogens.

Comparison with Existing Internal Articles

Although the paper by Jiang et al. centers on antibacterial drug use and resistance in psychiatric settings, several internal resources provide context for experimental strategies and molecular targets relevant to infection and inflammation research. For instance, articles such as "QNZ (EVP4593): Advanced NF-κB Inhibition for Neuroinflamm..." and "Precision NF-κB Inhibition: QNZ (EVP4593) as a Strategic ..." discuss the role of the NF-κB signaling pathway in neuroinflammation, infection-driven inflammation, and neurodegenerative conditions such as Huntington’s disease. While QNZ (EVP4593) is primarily profiled as a potent anti-inflammatory compound and NF-κB pathway modulator, these articles highlight the growing relevance of targeted pathway inhibition in managing both acute and chronic inflammatory responses, which are also central to the pathology of infection and antibiotic resistance. The reference paper does not investigate direct molecular interventions such as NF-κB inhibition but instead provides the clinical and epidemiological foundation that could inform future experimental designs—particularly those seeking to dissect host-pathogen interactions and the cellular mechanisms underlying resistance phenomena. By bridging clinical epidemiology with molecular pharmacology, researchers may more effectively translate insights from resistance monitoring into next-generation therapeutic strategies (internal_article).

Limitations and Transferability

Several limitations should be considered when interpreting the findings of Jiang et al. First, the study is retrospective and limited to a single psychiatric hospital, which may reduce generalizability to other institutions or geographic regions. The unique patient demographics and management protocols of the hospital may not reflect broader trends. Additionally, while high microbiological submission rates are commendable, the specific drivers of resistance—such as patient comorbidities, infection control practices, or local microbial ecology—are not dissected in detail. Transferability to other clinical settings requires caution, especially where stewardship infrastructure or laboratory support differs. Nonetheless, the benchmarking methodology and focus on stewardship-linked microbiological data serve as an instructive model for similar studies elsewhere.

Why this cross-domain matters, maturity, and limitations

While the study underlines the importance of antibiotic stewardship and surveillance, it does not directly explore molecular or pathway-targeted interventions commonly highlighted in anti-inflammatory or neurodegenerative disease research. The cross-domain bridge—from institutional antibiotic management to targeted pathway modulation (e.g., NF-κB inhibitors like QNZ/EVP4593)—remains prospective rather than evidence-based in this context. However, the integration of clinical resistance data with mechanistic studies, as seen in internal resources, represents a significant future direction for translational research. Maturity in this area depends on further studies linking clinical epidemiology with molecular intervention outcomes (internal_article).

Research Support Resources

Researchers aiming to investigate the molecular mechanisms underlying bacterial resistance or inflammation in infection models may consider integrating pathway-targeted compounds into their workflows. For example, QNZ (EVP4593) (SKU A4217) is a nanomolar-potency quinazoline derivative inhibitor of the NF-κB signaling pathway, commonly used in studies of inflammation and neurodegenerative disease models such as Huntington’s disease research (source: product_spec). APExBIO provides detailed handling and solubility information to support reproducibility in cellular and animal assays. While the current study by Jiang et al. does not directly address molecular pathway interventions, such resources can be valuable for researchers designing mechanistic follow-up studies or translational workflows linked to infection and resistance phenomena.