ArticleBMC health services research2025
Clinical pharmacist-led medication review in patients with sepsis and septic shock in the intensive care unit: a non-randomized controlled study.
Article in BMC health services research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Article
- Knowledge, attitudes, and behaviors of pharmacy students towards clinical pharmacy in Türkiye: insights from a multicenter cross-sectional study.BMC medical education · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPolypharmacy, resulting from the medications used in the management of sepsis, along with the pharmacokinetic changes induced by sepsis, can place this patient population at increased risk for drug-related problems (DRPs). Clinical pharmacists contribute to reducing DRPs by providing medication review services, which involve a comprehensive evaluation of a patient's medications. The aim of this study was to identify and classify DRPs in patients with sepsis and septic shock who were hospitalized in the intensive care unit (ICU), and to evaluate the effect of clinical pharmacist-led medication review on DRPs.
methodsThe study was a prospective, non-randomized controlled study conducted in the medical ICU of a tertiary education and research hospital in Istanbul, Türkiye, from October 2023 to May 2024. The study design included both observation periods (OP) and intervention periods (IP). During the IP, the clinical pharmacist provided recommendations to prevent or resolve DRPs during daily rounds and conducted DRP-reducing presentations to the clinical team on DRPs frequently observed during the OP. DRPs were classified according to Pharmaceutical Care Network (PCNE) Version 9.1 and their clinical significance in collaboration with the chief of ICU.
resultsA total of 60 patients were included in the study. The mean age of all patients was 62.6 ± 17.4 years and 58.3% were male. A total of 354 (5.9/patient) DRPs were detected in all periods. Of these DRPs, 50.1% were classified as "adverse drug event (possibly) occurring", 30.8% as "effect of drug treatment not optimal", 5.6% as "unnecessary drug treatment", 2.8% as "untreated symptoms or indications", and 10.7% as "unclear problem/complaint". In the IP, the number of all DRPs decreased by 63.3% (p < 0.001) and the frequency of clinically significant major DRPs decreased by 84.8% (p = 0.008). During the IP, recommendations were made for 72 of the 95 DRPs identified and 70 of these recommendations (97.2%) were accepted by physicians.
conclusionA high incidence of DRP was detected in patients with sepsis hospitalized in the ICU. The majority of clinical pharmacist recommendations were accepted by the ICU team. The number of DRPs decreased significantly during the IP.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.