Antibacterial Drug Use and Resistance in Psychiatric Hospitals During the Epidemic

Study Background and Research Question

The COVID-19 pandemic introduced unprecedented challenges for healthcare institutions worldwide, including psychiatric hospitals, where patients' mental and physical health needs intersect. Psychiatric inpatients frequently present with comorbidities that reduce immunity, such as granulocytopenia or leukopenia induced by prolonged antipsychotic therapy. Additionally, the closed management systems and high-density group activities in psychiatric settings elevate the risk of infectious outbreaks. These factors collectively amplify the importance—and complexity—of antibacterial stewardship in these facilities. The central research question addressed by Jiang et al. (2025) was: how did the 2022 epidemic affect antibacterial drug use and patterns of bacterial resistance in a psychiatric hospital, and what can be learned to optimize future protocols?

Key Innovation from the Reference Study

Unlike many prior reports focused on general or acute-care hospitals, this study uniquely targets psychiatric institutions—a setting characterized by distinct patient vulnerabilities and care models. The authors implemented a systematic, data-driven approach utilizing both hospital information systems and the National Antibacterial Drug Clinical Application Monitoring Network. This allowed for an integrated retrospective analysis of antibiotic utilization rates, drug resistance trends, and stewardship practices during a pandemic year. Notably, the work delivers actionable metrics for rational antibiotic use—including antibiotic use rate, intensity, and the rate of microbiological submission—benchmarked against both provincial and national data. This provides a much-needed evidence base for stewardship initiatives tailored to psychiatric settings, where the risk factors for infection transmission and resistance emergence diverge from general hospitals.

Methods and Experimental Design Insights

The study adopted a retrospective observational design, collecting data from a major psychiatric hospital in Jiangsu Province for the year 2022. Data sources included the hospital's electronic medical records (EMR) and the National Antibacterial Drug Clinical Application Monitoring Network. Key parameters analyzed were:

• Antibiotic use rate (percentage of patients receiving antibiotics)
• Antibiotic use intensity (AUD: defined daily doses per 100 bed-days)
• Combined medication rate (proportion of cases receiving two or more antibiotics)
• Cumulative antibiotic DDDs (defined daily doses)
• Antibiotic expenditure as a proportion of total drug costs
• Rate of microbiological submission for patients prescribed antibiotics
• Distribution of antibiotic classes and individual agents by usage frequency
• Bacterial species isolated and their resistance profiles

By leveraging routine surveillance data and standardized reporting platforms, the authors ensured both comprehensive coverage and comparability across institutions and regions.

Core Findings and Why They Matter

The analysis revealed several meaningful patterns during the 2022 epidemic (Jiang et al., 2025):

• Antibiotic use rate was low (5.00%) compared to provincial and national averages, suggesting relatively conservative prescribing practices in the psychiatric hospital.
• Usage intensity (3.07) and combined medication rate (11.11%) were also below broader benchmarks.
• Cumulative DDDs totaled 12,039.04, with antibiotic costs at 3.95% of total drug expenditures.
• Microbiological submission rate for patients receiving antibiotics reached 77.78%, significantly higher than provincial and national rates, reflecting improved stewardship and diagnostic alignment.
• Most frequently used antibiotics included third-generation cephalosporins (notably cefodizime), penicillins (amoxicillin), and piperacillin–tazobactam.
• Bacterial resistance patterns:
  • Gram-negative pathogens exhibited resistance mainly toward penicillins, cephalosporins, and quinolones—especially ampicillin, amoxicillin–clavulanic acid, ceftazidime, ceftriaxone, amikacin, and ciprofloxacin.
  • Gram-positive bacteria predominantly resisted penicillins, macrolides, and quinolones, with notable resistance to penicillin, benzylpenicillin, erythromycin, levofloxacin, and ciprofloxacin.

Despite overall prudent antimicrobial use, the study identified a persistent rise in bacterial resistance, especially among Gram-negative organisms. This underscores the paradox that even well-managed prescribing can inadvertently select for resistant strains, particularly in vulnerable populations. The authors recommend continued vigilance, enhanced resistance monitoring, and regular resistance data analysis to inform future stewardship decisions and safeguard effective treatment options.

Comparison with Existing Internal Articles

Recent internal publications provide context for the study's findings, particularly regarding anti-inflammatory interventions and research methodologies:

• The article "Gamma-linolenic Acid (GLA): Mechanistic Benchmarks and Research Utility" discusses GLA as a weak Leukotriene B4 receptor antagonist and omega-6 polyunsaturated fatty acid with anti-inflammatory and cytotoxic properties. While this work focuses on cellular and immunological models, it highlights the importance of robust assay design and validated workflow standards, aligning with the rigorous data collection and analysis protocols adopted by Jiang et al.
• The publication "Gamma-linolenic acid (GLA): Reliable Solutions for Cell Assays" details GLA's roles in anti-inflammatory research and apoptosis assay optimization. Though primarily centered on bench workflows, it echoes the reference study's emphasis on evidence-based, reproducible research and the significance of rational therapeutic selection in complex biological contexts.
• For direct thematic overlap, "Antibacterial Drug Use and Resistance in Psychiatric Hospitals During COVID-19" provides a complementary retrospective analysis, reinforcing the need for setting-specific stewardship protocols and ongoing resistance surveillance.

Together, these resources illustrate a convergent focus across domains: the necessity of integrating mechanistic insights, workflow reproducibility, and population-specific data to guide both laboratory and clinical decision-making.

Limitations and Transferability

While the reference study offers robust findings, several limitations merit consideration:

• The retrospective design precludes causal inference; observed associations between antibiotic use and resistance may be influenced by unmeasured confounders.
• Data pertain to a single psychiatric hospital in Jiangsu Province, potentially limiting generalizability to other regions or healthcare systems with different patient demographics or prescribing cultures.
• The focus on 2022, a year marked by pandemic disruptions, may not fully reflect longer-term, post-pandemic trends in antimicrobial stewardship or resistance dynamics.
• Microbiological submission rates, though high, do not guarantee optimal sampling quality or timing, which can affect pathogen detection and resistance profiling.

Nonetheless, the study's systematic approach and benchmarking against broader datasets enhance its utility as a reference point for similar institutions seeking to balance effective infection control with the minimization of resistance emergence.

Protocol Parameters

• Antibiotic use rate monitoring: Record the proportion of inpatients receiving antibiotics monthly; compare against institutional and regional targets to identify overuse or underuse trends.
• Microbiological submission protocols: For each new antibiotic prescription, submit cultures prior to therapy initiation whenever feasible; aim for submission rates above 70% to support stewardship.
• Antibiotic selection criteria: Prioritize narrow-spectrum agents guided by local resistance data; reserve broad-spectrum antibiotics for confirmed or strongly suspected multi-drug resistant infections.
• Resistance trend analysis: Review cumulative antibiogram data quarterly to adjust empirical therapy protocols and inform prescriber education.

Research Support Resources

For researchers advancing anti-inflammatory research or exploring the interplay between immune modulation and antimicrobial response, high-quality reagents are essential. Gamma-linolenic acid (GLA) (SKU C5518) from APExBIO is widely used in studies investigating inflammation, apoptosis assays, and atopic dermatitis treatment. Its documented properties as a weak Leukotriene B4 receptor antagonist and omega-6 polyunsaturated fatty acid make it a valuable tool for modeling anti-inflammatory mechanisms and supporting translational workflows. GLA's utility has been detailed in internal literature, emphasizing its reproducibility and compatibility with a variety of biomedical assays. Researchers are encouraged to consult the product dossier for detailed specifications and recommended storage conditions to maximize experimental reliability.