Impact of antimicrobial de-escalation on mortality: a literature review of study methodology and recommendations for observational studies

Introduction: The safety of de-escalation of empirical antimicrobial therapy is largely based on observational data, with many reporting protective effects on mortality. As there is no plausible biological explanation for this phenomenon, it is most probably caused by confounding by indication. Areas covered: We evaluate the methodology used in observational studies on the effects of de-escalation of antimicrobial therapy on mortality. We extended the search for a recent systematic review and identified 52 observational studies. The heterogeneity in study populations was large. Only 19 (36.5%) studies adjusted for confounders and four (8%) adjusted for clinical stability during admission, all as a fixed variable. All studies had methodological limitations, most importantly the lack of adjustment for clinical stability, causing bias toward a protective effect. Expert opinion: The methodology used in studies evaluating the effects of de-escalation on mortality requires improvement. We depicted all potential confounders in a directed acyclic graph to illustrate all associations between exposure (de-escalation) and outcome (mortality). Clinical stability is an important confounder in this association and should be modeled as a time-varying variable. We recommend to include de-escalation as time-varying exposure and use inverse-probability-of-treatment weighted marginal structural models to properly adjust for time-varying confounders

Assessing accuracy of ChatGPT in response to questions from day to day pharmaceutical care in hospitals

Background: The advent of Large Language Models (LLMs) such as ChatGPT introduces opportunities within the medical field. Nonetheless, use of LLM poses a risk when healthcare practitioners and patients present clinical questions to these programs without a comprehensive understanding of its suitability for clinical contexts. Objective: The objective of this study was to assess ChatGPT's ability to generate appropriate responses to clinical questions that hospital pharmacists could encounter during routine patient care. Methods: Thirty questions from 10 different domains within clinical pharmacy were collected during routine care. Questions were presented to ChatGPT in a standardized format, including patients' age, sex, drug name, dose, and indication. Subsequently, relevant information regarding specific cases were provided, and the prompt was concluded with the query “what would a hospital pharmacist do?”. The impact on accuracy was assessed for each domain by modifying personification to “what would you do?”, presenting the question in Dutch, and regenerating the primary question. All responses were independently evaluated by two senior hospital pharmacists, focusing on the availability of an advice, accuracy and concordance. Results: In 77% of questions, ChatGPT provided an advice in response to the question. For these responses, accuracy and concordance were determined. Accuracy was correct and complete for 26% of responses, correct but incomplete for 22% of responses, partially correct and partially incorrect for 30% of responses and completely incorrect for 22% of responses. The reproducibility was poor, with merely 10% of responses remaining consistent upon regeneration of the primary question. Conclusions: While concordance of responses was excellent, the accuracy and reproducibility were poor. With the described method, ChatGPT should not be used to address questions encountered by hospital pharmacists during their shifts. However, it is important to acknowledge the limitations of our methodology, including potential biases, which may have influenced the findings

Inappropriate Use of Antimicrobials for Lower Respiratory Tract Infections in Elderly Patients : Patient- and Community-Related Implications and Possible Interventions

The elderly are more susceptible to infections, which is reflected in the incidence and mortality of lower respiratory tract infections (LRTIs) increasing with age. Several aspects of antimicrobial use for LRTIs in elderly patients should be considered to determine appropriateness. We discuss possible differences in microbial etiology between elderly and younger adults, definitions of inappropriate antimicrobial use for LRTIs currently found in the literature, along with their results, and the possible negative impact of antimicrobial therapy at both an individual and community level. Finally, we propose that both antimicrobial stewardship interventions and novel rapid diagnostic techniques may optimize antimicrobial use in elderly patients with LRTIs

The quality of studies evaluating antimicrobial stewardship interventions : a systematic review

Background: Antimicrobial stewardship aims to optimize antibiotic use and minimize selection of antimicrobial resistance. The methodological quality of published studies in this field is unknown. Aims: Our objective was to perform a comprehensive systematic review of antimicrobial stewardship research design and identify features which limit validity and translation of research findings into clinical practice. Sources: The following online database was searched: PubMed. Study eligibility criteria: Studies published between January 1950 and January 2017, evaluating any antimicrobial stewardship intervention in the community or hospital setting, without restriction on study design or outcome. Content: We extracted data on pre-specified design quality features and factors that may influence design choices including (1) clinical setting, (2) age group studied, (3) when the study was conducted, (4) geographical region, and (5) financial support received. The initial search yielded 17 382 articles; 1008 were selected for full-text screening, of which 825 were included. Most studies (675/825, 82%) were non-experimental; 104 (15%) used interrupted time series analysis, 41 (6%) used external controls, and 19 (3%) used both. Studies in the community setting fulfilled a median of five out of 10 quality features (IQR 3–7) and 3 (IQR 2–4) in the hospital setting. Community setting studies (25%, 205/825) were significantly more likely to use randomization (OR 5.9; 95% CI 3.8–9.2), external controls (OR 5.6; 95% CI 3.6–8.5), and multiple centres (OR 10.5; 95% CI 7.1–15.7). From all studies, only 48% (398/825) reported clinical and 23% (190/825) reported microbiological outcomes. Quality did not improve over time. Implications: Overall quality of antimicrobial stewardship studies is low and has not improved over time. Most studies do not report clinical and microbiological outcome data. Studies conducted in the community setting were associated with better quality. These limitations should inform the design of future stewardship evaluations so that a robust evidence base can be built to guide clinical practice

Confounding by indication of the safety of de-escalation in community-acquired pneumonia: A simulation study embedded in a prospective cohort.

Observational studies have demonstrated that de-escalation of antimicrobial therapy is independently associated with lower mortality. This most probably results from confounding by indication. Reaching clinical stability is associated with the decision to de-escalate and with survival. However, studies rarely adjust for this confounder. We quantified the potential confounding effect of clinical stability on the estimated impact of de-escalation on mortality in patients with community-acquired pneumonia. Data were used from the Community-Acquired Pneumonia immunization Trial in Adults (CAPiTA). The primary outcome was 30-day mortality. We performed Cox proportional-hazards regression with de-escalation as time-dependent variable and adjusted for baseline characteristics using propensity scores. The potential impact of unmeasured confounding was quantified through simulating a variable representing clinical stability on day three, using data on prevalence and associations with mortality from the literature. Of 1,536 included patients, 257 (16.7%) were de-escalated, 123 (8.0%) were escalated and in 1156 (75.3%) the antibiotic spectrum remained unchanged. Crude 30-day mortality was 3.5% (9/257) and 10.9% (107/986) in the de-escalation and continuation groups, respectively. The adjusted hazard ratio of de-escalation for 30-day mortality (compared to patients with unchanged coverage), without adjustment for clinical stability, was 0.39 (95%CI: 0.19-0.79). If 90% to 100% of de-escalated patients were clinically stable on day three, the fully adjusted hazard ratio would be 0.56 (95%CI: 0.27-1.12) to 1.04 (95%CI: 0.49-2.23), respectively. The simulated confounder was substantially stronger than any of the baseline confounders in our dataset. Quantification of effects of de-escalation on patient outcomes without proper adjustment for clinical stability results in strong negative bias. This study suggests the effect of de-escalation on mortality needs further well-designed prospective research to determine effect size more accurately

Confounding by indication of the safety of de-escalation in community-acquired pneumonia : A simulation study embedded in a prospective cohort

Observational studies have demonstrated that de-escalation of antimicrobial therapy is independently associated with lower mortality. This most probably results from confounding by indication. Reaching clinical stability is associated with the decision to de-escalate and with survival. However, studies rarely adjust for this confounder. We quantified the potential confounding effect of clinical stability on the estimated impact of de-escalation on mortality in patients with community-acquired pneumonia. Data were used from the Community-Acquired Pneumonia immunization Trial in Adults (CAPiTA). The primary outcome was 30-day mortality. We performed Cox proportional-hazards regression with de-escalation as time-dependent variable and adjusted for baseline characteristics using propensity scores. The potential impact of unmeasured confounding was quantified through simulating a variable representing clinical stability on day three, using data on prevalence and associations with mortality from the literature. Of 1,536 included patients, 257 (16.7%) were de-escalated, 123 (8.0%) were escalated and in 1156 (75.3%) the antibiotic spectrum remained unchanged. Crude 30-day mortality was 3.5% (9/257) and 10.9% (107/986) in the de-escalation and continuation groups, respectively. The adjusted hazard ratio of de-escalation for 30-day mortality (compared to patients with unchanged coverage), without adjustment for clinical stability, was 0.39 (95%CI: 0.19-0.79). If 90% to 100% of de-escalated patients were clinically stable on day three, the fully adjusted hazard ratio would be 0.56 (95%CI: 0.27-1.12) to 1.04 (95%CI: 0.49-2.23), respectively. The simulated confounder was substantially stronger than any of the baseline confounders in our dataset. Quantification of effects of de-escalation on patient outcomes without proper adjustment for clinical stability results in strong negative bias. This study suggests the effect of de-escalation on mortality needs further well-designed prospective research to determine effect size more accurately