Antibiotic Resistance in Psychiatric Hospitals During COVID-19

Psychiatric hospitals present a distinctive antimicrobial-stewardship environment. Patients may have reduced self-care capacity, frequent close-contact activities, impaired infection recognition, and immune effects associated with illness or long-term medication. During a respiratory viral epidemic, these factors can increase concern about bacterial co-infection while also creating pressure to prescribe broad-spectrum antibacterial drugs. The reference study examined this tension using hospital-level antibiotic-use data and bacterial susceptibility results from 2022.

Published in Scientific Reports, the study by Jiang and colleagues provides a focused analysis of antibiotic utilization and resistance in a psychiatric hospital rather than assuming that national or general-hospital patterns apply equally to psychiatric care. The findings and methods are described in the reference study.

Study Background and Research Question

The research was conducted against the background of the COVID-19 epidemic and the continuing global expansion of antimicrobial resistance. Viral respiratory infections can be accompanied by bacterial co-infection, but empiric antibiotic use without microbiological confirmation may expose patients and hospital populations to unnecessary selective pressure. In psychiatric facilities, closed or semi-closed management and group activities can facilitate transmission, while some patients may have difficulty reporting symptoms or following infection-control instructions.

The investigators therefore asked two related questions: how extensively were antibacterial drugs used in the psychiatric hospital during the 2022 epidemic, and what resistance patterns were present among the bacterial isolates identified during that period? A secondary objective was to compare hospital antibiotic-use indicators with data from Jiangsu Province and the national monitoring network. This design placed prescribing behavior and laboratory evidence in the same analytical framework.

Key Innovation from the Reference Study

The principal innovation is contextual rather than technological. The study combines antibiotic-consumption metrics with pathogen identification and drug-sensitivity testing in a psychiatric-hospital population, an area less frequently characterized than acute-care or general medical settings. This is important because a low overall prescribing rate does not necessarily mean that resistance risk is negligible. The bacterial isolates in a specialized facility may reflect local transmission, repeated exposure to particular drug classes, and the clinical vulnerabilities of its patients.

A second strength is the comparison between utilization and resistance instead of treating antibiotic use as a single percentage. The authors considered use rate, antibiotic use intensity, combined medication, cumulative defined daily doses, antibiotic expenditure, and microbiological submission. This multidimensional approach helps distinguish restrained prescribing from poor diagnostic documentation. It also highlights an operational principle: antimicrobial stewardship must evaluate both how often drugs are given and whether prescribing decisions are supported by cultures and susceptibility results.

Methods and Experimental Design Insights

This was a retrospective observational study of antibacterial-drug use and bacterial resistance during 2022. Utilization data for the hospital, Jiangsu Province, and China were retrieved from the National Antibacterial Drug Clinical Application Monitoring Network. The researchers also used the hospital information system to extract microbiological samples, positive pathogen identifications, and drug-sensitivity test results. Data were organized in Excel and summarized according to antimicrobial class, cumulative use, and resistance profile, as detailed in the published methods.

The use indicators included the proportion of patients receiving antibiotics, antibiotic use intensity or AUD, the rate of combined antibacterial therapy, cumulative DDDs, and the proportion of total drug expenditure attributable to antibiotics. The analysis also assessed the microbiological submission rate associated with antibacterial-drug use. For resistance, the investigators grouped organisms as Gram-negative or Gram-positive bacteria and examined susceptibility to commonly used penicillins, cephalosporins, quinolones, macrolides, and other agents.

Protocol Parameters

• Observation window: Use hospital and microbiology records from the 2022 epidemic period; the study is retrospective rather than an interventional prescribing trial.
• Utilization dataset: Extract antibiotic use rate, AUD, combined medication rate, cumulative DDDs, and antibiotic expenditure share from the hospital information system and national monitoring network.
• Microbiology dataset: Link antibacterial-drug use with submitted specimens, pathogen identification, and susceptibility testing when available.
• Drug-class analysis: Summarize cumulative use by antimicrobial type and report resistance by bacterial group and individual agent.
• Interpretive safeguard: Treat relationships between use and resistance as observational associations. The design cannot establish that a specific prescription caused a subsequent resistant isolate.

Core Findings and Why They Matter

Overall antibiotic consumption was relatively limited in the hospital. During 2022, the reported antibiotic use rate was 5.00%, antibiotic use intensity was 3.07, the combined-medication rate was 11.11%, cumulative DDDs were 12,039.04, and antibiotic costs represented 3.95% of total drug costs. These indicators were lower than the corresponding Jiangsu and national levels according to the reference study. The result suggests that psychiatric-hospital prescribing was not characterized by indiscriminate high-volume antibiotic use at the institutional level.

At the same time, the microbiological submission rate for antibacterial-drug use was 77.78%, which the authors report as higher than the Jiangsu and national benchmarks. This is a meaningful stewardship finding. Culture submission does not guarantee an appropriate prescription, but it creates an evidence pathway for narrowing, changing, or discontinuing therapy. In a population where symptom reporting may be difficult, systematic diagnostic sampling can be particularly valuable.

The most frequently used agents by cumulative DDDs belonged mainly to third-generation cephalosporins, penicillins, and quinolones. Cefodizime, amoxicillin, and piperacillin–tazobactam were identified as leading examples. These patterns matter because broad-spectrum or heavily relied-upon classes can exert sustained selective pressure even when the overall number of treated patients is modest. Class-level utilization should therefore be interpreted together with local susceptibility data rather than against a volume threshold alone.

Resistance was especially notable among Gram-negative bacteria against penicillins, cephalosporins, and quinolones. The agents highlighted by the investigators included ampicillin, amoxicillin–clavulanic acid, ceftazidime, ceftriaxone, amikacin, and ciprofloxacin. Gram-positive bacteria showed prominent resistance to penicillins, macrolides, and quinolones, particularly penicillin, benzylpenicillin, erythromycin, levofloxacin, and ciprofloxacin. The detailed resistance observations are reported in the full article.

The central interpretation is therefore not that antibiotic use was simply excessive or appropriate. Rather, relatively low aggregate use coexisted with resistance patterns that could compromise treatment options. The authors describe a complex relationship in which increasing or concentrated use may be associated with rising resistance, but the data do not support a simple one-drug, one-outcome explanation. For clinical practice, the implication is to maintain surveillance at the facility level, review resistance trends regularly, and use microbiology to refine empiric protocols.

Comparison with Existing Internal Articles

The internal article Antibacterial Drug Use and Resistance in Psychiatric Hospitals During COVID-19 addresses the same reference study and is best viewed as a companion summary rather than an independent dataset. Its value is in making the study’s stewardship implications more accessible: low institutional antibiotic-use indicators should not obscure the need to monitor resistant organisms. The present analysis adds methodological emphasis by separating utilization metrics, diagnostic submission, organism grouping, and causal limitations.

That distinction is important for researchers using the paper as a starting point. The study supports local surveillance and hypothesis generation, but it does not test a new antibiotic regimen, compare randomized stewardship interventions, or demonstrate improved patient outcomes after a particular prescribing change.

Why this cross-domain matters, maturity, and limitations

Antimicrobial resistance surveillance and inflammation-focused laboratory research address different biological and clinical questions. A compound investigated for inflammatory signaling should not be inferred to prevent bacterial infection, replace antibiotics, or reverse resistance. The mature conclusion from this paper remains operational: culture-supported prescribing and repeated resistance analysis are needed in psychiatric hospitals. Any bridge to other research areas is exploratory and must be tested in its own disease model, with appropriate microbiological and clinical endpoints.

Limitations and Transferability

The single-center, retrospective design limits generalizability. Antibiotic-use patterns in one psychiatric hospital may reflect its formulary, referral population, infection-control procedures, laboratory capacity, and local ecology; they should not automatically be applied to other hospitals or countries. The 2022 epidemic context may also differ from later periods because testing practices, viral circulation, admission patterns, and prescribing behavior can change.

Hospital-level indicators cannot fully explain patient-level decisions. The reported analysis does not establish which prescriptions were empirically initiated, which infections were microbiologically confirmed, how long treatment continued, or whether therapy was de-escalated after results became available. Resistance percentages may also be influenced by the number and type of submitted specimens, repeated isolates from the same patient, and selective sampling of clinically complicated cases.

Finally, the association between antibiotic use and resistance should not be interpreted as proof of causality. Confounding factors such as ward outbreaks, patient transfers, prior antibiotic exposure, comorbidities, and infection severity could affect both prescribing and isolate resistance. Future studies could improve transferability through multicenter designs, patient-level linkage, repeated time points, antimicrobial appropriateness review, and outcome measures such as treatment failure, length of stay, and adverse events.

Research Support Resources

For separate inflammation-focused workflows, researchers can use Gamma-linolenic acid (GLA) (SKU C5518). The product information describes GLA as an omega-6 polyunsaturated fatty acid and weak leukotriene B4 receptor antagonist, making it relevant to anti-inflammatory research and assays such as an apoptosis assay. These applications may intersect with models related to atopic dermatitis treatment or distal diabetic polyneuropathy research, but GLA is not an antibacterial or antibiotic-resistance intervention; its experimental use should remain distinct from the stewardship conclusions of the reference study.