Drug related adverse event assessment in neonates in clinical trials and clinical care.

INTRODUCTION: Assessment of drug-related adverse events is essential to fully understand the benefit-risk balance of any drug exposure, weighing efficacy versus safety. This is needed for both drug labeling and clinical decision-making. Assessment is based on seriousness, severity and causality, be it more difficult to apply in neonates. Adverse event detection or prevention in the neonatal clinical setting is also more complicated because of polypharmacy, and off-label or unlicensed pharmacotherapy. AREAS COVERED: Tools became available to assess severity and causality of adverse events in neonates recruited in clinical trials. The first version of the Neonatal Adverse Event severity score (NAESS) reduced the inter-observer variability. Causality tools like the Naranjo score were also tailored to neonates. These tools are also instrumental to support proactive pharmacovigilance in clinical care, while multidisciplinary care teams and computerized pharmacovigilance using advanced data analysis, like machine learning are emerging approaches to develop effective decision strategies. EXPERT OPINION: All stakeholders involved in development of medicines or its clinical use should be aware of the limitations of the currently available assessment tools. Extension and optimization of these tools, advanced data analysis approaches, and capturing the variability in time-dependent physiology are warranted to improve pharmacovigilance in neonates.

A Novel Machine-Learning Algorithm to Predict the Early Termination of Nutrition Support Team Follow-Up in Hospitalized Adults: A Retrospective Cohort Study.

BACKGROUND: For hospitalized adults, it is important to initiate the early reintroduction of oral food in accordance with nutrition support team guidelines. The aim of this study was to develop and validate a machine learning-based algorithm that predicts the early termination of medical nutritional therapy (the transition to oral feeding). METHODS: This retrospective cohort study included consecutive adult patients admitted to the Hacettepe hospital (from 1 January 2018 to 31 December 2022). The outcome of the study was the prediction of an early transition to adequate oral feeding before discharge. The dataset was randomly (70/30) divided into training and test datasets. We used six ML algorithms with multiple features to construct prediction models. ML model performance was measured according to the accuracy, area under the receiver operating characteristic curve, and F1 score. We used the Boruta Method to determine the important features and interpret the selected features. RESULTS: A total of 2298 adult inpatients who were followed by a nutrition support team for medical nutritional therapy were included. Patients received parenteral nutrition (1471/2298, 64.01%), enteral nutrition (717/2298, 31.2%), or supplemental parenteral nutrition (110/2298, 4.79%). The median (interquartile range) Nutritional Risk Screening (NRS-2002) score was 5 (1). Six prediction algorithms were used, and the artificial neural network and elastic net models achieved the greatest area under the ROC in all outcomes (AUC = 0.770). Ranked by z-value, the 10 most important features in predicting an early transition to oral feeding in the artificial neural network and elastic net algorithms were parenteral nutrition, surgical wards, surgical outcomes, enteral nutrition, age, supplemental parenteral nutrition, digestive system diseases, gastrointestinal complications, NRS-2002, and impaired consciousness. CONCLUSIONS: We developed machine learning models for the prediction of an early transition to oral feeding before discharge. Overall, there was no discernible superiority among the models. Nevertheless, the artificial neural network and elastic net methods provided the highest AUC values. Since the machine learning model is interpretable, it can enable clinicians to better comprehend the features underlying the outcomes. Our study could support personalized treatment and nutritional follow-up strategies in clinical decision making for the prediction of an early transition to oral feeding in hospitalized adult patients.

Advancing patient care: novel scales for assessing adherence and attitudes toward medication among adolescents with psychiatric disorders and their parents.

Adolescents with psychiatric disorders may struggle with medication adherence and this can lead to ineffective treatment. Subjective factors, such as attitudes, beliefs, experiences, have a greater impact on adherence in adolescents than objective factors. To better understand these subjective attitudes, self-evaluation rating scales should be developed. The study aimed to develop two scales - Pediatric Medication Adherence Scale (PMAS) and Pediatric Attitudes toward Medication Scale (PAMS) - to assess adherence and attitudes toward medication for pediatric patients and their parents. Total of 288 pediatric patients (67% female) between the ages of 12-18 (mean [standard deviation] age of 15.25 [1.59] years) with psychiatric disorders and 255 parents (83.53% mothers) were administered the scales. The validity of the scales was evaluated through the content validity index and explanatory factor analyses. To evaluate reliability, Cronbach's alpha, and test-retest methods were utilized. The validity and reliability of the PMAS (9 questions for patients, 6 questions for parents) and PAMS (18 questions for patients, 20 questions for parents), Cronbach's alpha values and intraclass correlation coefficients were found above 0.7 for each scale and showed well establishment for this particular population. Analysis revealed that anxiety scores had a greater impact on total attitude scores than necessity scores (p < 0.05). Parent and patient adherence scores were similar, and negative parental attitudes toward medication were associated with lower patient adherence. The present study represents a novel attempt to design a medication adherence and attitude questionnaire for adolescents with psychiatric disorders, along with a parental version.

Optimization of appropriate antimicrobial prophylaxis in general surgery: a prospective cohort study.

BACKGROUND: Surgical site infections (SSI) are characterized by infections occurring in the surgical incision site, organ or cavity in the postoperative period. Adherence to surgical antimicrobial prophylaxis (SAP) is paramount in mitigating the occurrence of SSIs. In this study, we aimed to evaluate the appropriateness of SAP use in patients undergoing surgical procedures in the field of general surgery according to the American Society of Health-System Pharmacists (ASHP) guideline and to determine the difference between the pre-training period (pre-TP) and the post-training period (post-TP) organized according to this guideline. METHODS: It is a single-center prospective study conducted in general surgery wards between January 2022 and May 2023, with 404 patients pre-TP and 406 patients post-TP. RESULTS: Cefazolin emerged as the predominant agent for SAP, favored in 86.8% (703/810) of cases. Appropriate cefazolin dosage increased significantly from 41% (129 patients) in pre-TP to 92.6% (276 patients) in post-TP (p < 0.001), along with a rise in adherence to recommended timing of administration from 42.2% (133 patients) to 62.8% (187 patients) (p < 0.001). The proportion of patients receiving antibiotics during hospitalization in the ward postoperatively decreased post-TP (21-14.3%; p = 0.012), as did antibiotic prescription at discharge (16.8-10.3%; p = 0.008). The incidence of SSI showed a slight increase from 9.9% in pre-TP to 13.3% in post-TP (p = 0.131). CONCLUSIONS: Routine training sessions for surgeons emerged as crucial strategies to optimize patient care and enhance SAP compliance rates, particularly given the burden of clinical responsibilities faced by surgical teams.

Effect of Modulator Therapies on Nutritional Risk Index in Adults with Cystic Fibrosis: A Prospective Cohort Study.

Background: Modulator therapies improve weight and body mass index (BMI) in cystic fibrosis (CF) patients. We aimed to compare the nutritional risk index (NRI) in adult CF patients receiving modulator (MT) or only non-modulator (conventional) therapies (non-MT). Methods: A single-center prospective cohort study was conducted between June and December 2023. The NRI based on weight gain and albumin was calculated at beginning and end of a 12-week period in both groups. This design was pragmatic, since it was based on individual patient access to MT for 12 weeks. Results: In total, 107 patients were included [mean (SD) age: 23.85 (4.98) years, 54.7% male, 46.7% MT]. In the MT group, mean (SD) weight (kg) and albumin (g/dL) increased significantly [changes: +3.09 (2.74) and +0.17 (0.37); p < 0.001]. In the non-MT group, weight and albumin decreased significantly [changes: -0.99 (1.73) and -0.12 (0.30); p < 0.001]. Compared to the MT group, baseline mean (SD) NRI in the non-MT group was significantly higher [100.65 (11.80) vs. 104.10 (10.10); p = 0.044]. At the end of the 12 weeks, mean (SD) NRI in the MT group was higher than in the non-MT group [104.18 (10.40) vs. 102.58 (12.39); p = 0.145]. In the MT group, the NRI category improved in 22 (44%), and worsened in 3 (6%) patients (p < 0.001). In the non-MT group, the NRI category improved in 2 (3.5%), and worsened in 10 (17.5%) patients (p < 0.001). Conclusions: This is the first study reporting on a positive effect of MT on NRIs, based on weight gain and albumin. Personalized nutrition and routine follow-up of adults with CF based on NRI is recommended prior to MT initiation.

Web Survey of Turkish Pharmacy Students Comparing First and Fifth Years' Antidepressant Awareness and Stigmatizing Attitudes Regarding Depression and Anxiety.

The prevalence of depression and anxiety has increased day by day. Prejudice, self-stigma, and public stigma, on the other hand, continue to prevent patients from seeking adequate treatment, particularly in traditional communities. In this web-based, cross-sectional study, both the presence of depression and anxiety, and the knowledge, attitude, and awareness of first- and fifth (final)-year pharmacy students were examined via an online survey. The aim was to demonstrate the potential impact of public information and five years of pharmacy school on knowledge, attitude, and awareness. Our study population consisted of first- and fifth-year pharmacy students enrolled in one faculty of pharmacy during the spring semester of 2022-2023. The Beck Depression Inventory and Beck Anxiety Scale were utilized to measure the presence of depression and anxiety, while the Depression and Antidepressant Awareness and Knowledge Scale (DAKAS) was applied to assess their knowledge, attitude, and awareness. Fifth-year participants (n = 101) exhibited noticeably fewer stigmatizing attitudes than first-year participants (n = 104) (p < 0.05). There was no statistically significant difference between the mean Beck Depression Inventory and Beck Anxiety scores in first- and fifth-year pharmacy students. Being in the fifth class (OR: 3.690; p = 0.025), being of female gender (OR: 4.653; p < 0.001), and having a relationship with someone who took a psychotropic (OR: 3.060; p = 0.008) were associated with a lower overall stigma score by multiple linear regression analysis. The students' awareness of antidepressants and familiarity with mental health issues at the end of their pharmacy education were higher and stigmatization behavior was lower than in first-year students. The positive attitudes at the end of their training towards depression will reduce the likelihood of future pharmacists' patients from being exposed to stigmatization, prevents the formation of an additional stress factor, and likely will improve pharmacy practices.

Adherence to medical treatment for Wilson's disease in children and adolescents: a cohort study from Turkey.

BACKGROUND: This study aimed to assess medication adherence and demographic, clinical, and psychopathological parameters such as quality of life, depression, and anxiety levels that can affect pediatrics with Wilson's Disease (WD). METHODS: A prospective cohort study was conducted at an outpatient clinic in Turkey among pediatric patients (2 to 18 years) with WD between November 2022 and April 2023. The Medication Adherence Report Scale (MARS-5) as a subjective and Medication Possession Ratio (MPR) as an objective assessment were scored. Physical, genetic and biochemical parameters, the Pediatric Quality of Life Inventory (PedsQL) for both parents and patients, Childhood Depression Inventory, State Trait Anxiety Inventory were also administered. RESULTS: A total of 30 pediatric outpatients who were prescribed D-penicillamine (n = 27) or trientine (n = 3) as chelators and zinc (n = 29) and pyridoxine (n = 19) as supplements were included. Proteinuria (n = 3), skin rash (n = 2), and gastrointestinal upset (n = 2) were observed. When the correlation between MARS-5 and duration of follow-up was examined, a significant negative correlation was found (p = 0.014). According to MPRs, non-adherence rates (missed doses ≥ 20%) were 29.6%, 17.2% and 5.3% for D-penicillamine, zinc and pyridoxine, respectively. PedsQL scores were higher than those of parents, with a positive correlation between them (p < 0.001). Also, there was a significant positive correlation between PedsQL and State Anxiety Inventory (p < 0.001). Comparing the change in urinary copper levels between different levels of treatment knowledge, significant differences were observed between high- and low levels (p = 0.043). CONCLUSIONS: Overall, nonadherence rates were 23.3% based on MARS-5 and 5.3-29.6% based on MPR. It is essential to consider factors such as the duration of follow-up, biochemical parameters, treatment knowledge, quality of life and anxiety as potential influencers of medication adherence.

Clinical pharmacist-led assessment and management of anticholinergic burden and fall risk in geriatric patients.

BACKGROUND: The aim of this study was to examine the risk of fall with the surrogate outcome of the Aachen Falls Prevention Scale and to assess the clinical pharmacist interventions in order to minimize anticholinergic drug burden and associated risk of fall according to a fall risk assessment scale in the older adults. METHODS: Patients who admitted to the geriatric outpatient clinic of a university hospital and taking at least one anticholinergic drug were evaluated both retrospectively and prospectively as groups of different patients by the clinical pharmacist. Patients' anticholinergic burden was assessed using the Anticholinergic Cognitive Burden Scale. For fall risk assessment, the Aachen Falls Prevention Scale was also administered to each patient whose anticholinergic burden was determined in the prospective phase of the study. RESULTS: A total of 601 patients were included. Risk of falls increased 2.50 times in patients with high anticholinergic burden (OR (95% CI) = 2.503 (1.071-5.852); p = 0.034), and the existing history of falls increased the risk of high anticholinergic burden 2.02 times (OR (95%CI) = 2.026 (1.059-3.876); p = 0.033). In addition, each unit increase in the fall scale score in the prospective phase increased the risk of high anticholinergic burden by 22% (p = 0.028). Anticholinergic burden was significantly reduced as a result of interventions by the clinical pharmacist in the prospective phase (p = 0.010). CONCLUSION: Our study revealed that incorporating a clinical pharmacist in the handling of geriatric patients aids in the detection, reduction, and prevention of anticholinergic adverse effects.

Education and clinical pharmacist-led management strategies for the risk and prophylaxis of venous thromboembolism in general surgery.

BACKGROUND: Despite the risks of venous thromboembolism (VTE) in surgical patients are well defined, primary thromboprophylaxis (TP) can be neglected. The aim of this study was to evaluate the risk of VTE and appropriateness of TP and to assess the effects of education and clinical pharmacy (CP) services. METHODS: This study was conducted in a total of 3 periods (n = 800): pre-education (n = 340), post-education (n = 269) and CP intervention period (n = 191) and the risk of VTE and the appropriateness of TP were evaluated. At the end of pre-education period, patients were re-evaluated after education was given about the guidelines on TP and an educative poster was posted in the services (post-education period). During the CP intervention period, the CP made recommendations in terms of optimal TP use to the physicians in charge. RESULTS: While there was no significant difference in the optimal TP rate administered to the patients before and after education (138/340, 40.6% vs. 122/269, 45.4%; p = 0.238); this rate was increased to 113/191 (59.2%) in the CP intervention period (p = 0.004). High-risk patients who received one type of TP constituted the majority of patients who did not receive optimal TP. While the ratio of high-risk patients undergoing a single type of TP in the pre- and post-education periods (104/340, 30.6% vs. 83/269, 30.9%), was similar (p = 0.819); with the CP interventions, this rate was reduced to 35/191 (18.3%) (p = 0.001). CONCLUSION: Even though education has positive influence on surgeons, the implementation of CP practices is more effective especially in terms of maintaining optimal TP.

Impact of clinical pharmacist-led intervention for drug-related problems in neonatal intensive care unit a randomized controlled trial.

Introduction: Drug-related problems (DRPs) incidence is higher in neonatal intensive care units (NICUs), compared to other pediatric wards due to aspects like off-label medications, pharmacokinetic/dynamic variability, or organ dysfunction/immaturity. This study aimed to determine whether and to what extent a clinical pharmacist intervention improves medication safety and prevents DRPs [medication errors (MEs), adverse drug reactions (ADRs), drug-drug interactions (DDIs)]. Methods: A prospective, randomized, double blind, controlled study in NICU-admitted neonates was conducted. NICU patients were randomly assigned to the intervention (clinical pharmacist-led) (IG) or control group (standard care such as clinical diagnosis, pharmacotherapy) (CG). The clinical pharmacist was involved in the IG to identify-prevent-intervene MEs, or identify and monitor ADRs and DDIs. The primary outcome was the number of neonates who developed at least one DRP compared with those seen across IG and CG. Secondary outcomes included length of hospital stay, total number of drugs or DRP type. Results: Neonates were randomly assigned to CG (n = 52) or IG (n = 48). In total, 45%, 42%, and 16% of patients had at least 1 MEs, ADRs, and clinically significant DDIs, respectively. The number of patients with at least 1 ME was 28 (53%) and 17 (35%) in the CG and IG (p>0.05). The median (range) number of ME was higher in CG [1 (0-7)] than in IG [0 (0-4)] (p = 0.003). Applying regression analysis, the CG had 2.849 times more MEs than the IG (p<0.001). Furthermore, the number of patients (CG to IG) with at least one detected ADR or clinical DDI was 19 (36%) to 23 (47%) (p>0.05) and 4 (7%) to 12 (25%), respectively (p = 0.028). Conclusion: Clinical pharmacist availability to systematically and standardized identify, prevent and resolve DRPs among NICU patients is effective. Daily detailed clinical pharmacist observations and interventions enables prevention and monitoring of DRPs. Clinical Trial Registration ClinicalTrials.gov, identifier NCT04899960.

Pharmacogenetic testing in psychiatry: Perspective on clinical utility.

Pharmacogenetic studies the influence of inherited characteristics on medication. While different from pharmacogenomics, which is a study of the entire genome in relation to medication effect, their distinction remains inconsistent, and the two terms are used interchangeably. Although the potential of pharmacogenomics in psychiatry is apparent and its clinical utility is suboptimal, the uptake of recommendations and guidelines is minimal and research into PGx is not diverse. This article offers an overview of pharmacogenetics (PGx) in psychiatry, explores the difficulties, and provides recommendations on improving its applicability and clinical utility.

Development and validation of a machine learning-based detection system to improve precision screening for medication errors in the neonatal intensive care unit.

Aim: To develop models that predict the presence of medication errors (MEs) (prescription, preparation, administration, and monitoring) using machine learning in NICU patients. Design: Prospective, observational cohort study randomized with machine learning (ML) algorithms. Setting: A 22-bed capacity NICU in Ankara, Turkey, between February 2020 and July 2021. Results: A total of 11,908 medication orders (28.9 orders/patient) for 412 NICU patients (5.53 drugs/patient/day) who received 2,280 prescriptions over 32,925 patient days were analyzed. At least one physician-related ME and nurse-related ME were found in 174 (42.2%) and 235 (57.0%) of the patients, respectively. The parameters that had the highest correlation with ME occurrence and subsequently included in the model were: total number of drugs, anti-infective drugs, nervous system drugs, 5-min APGAR score, postnatal age, alimentary tract and metabolism drugs, and respiratory system drugs as patient-related parameters, and weekly working hours of nurses, weekly working hours of physicians, and number of nurses' monthly shifts as care provider-related parameters. The obtained model showed high performance to predict ME (AUC: 0.920; 95% CI: 0.876-0.970) presence and is accessible online (http://softmed.hacettepe.edu.tr/NEO-DEER_Medication_Error/). Conclusion: This is the first developed and validated model to predict the presence of ME using work environment and pharmacotherapy parameters with high-performance ML algorithms in NICU patients. This approach and the current model hold the promise of implementation of targeted/precision screening to prevent MEs in neonates. Clinical Trial Registration: ClinicalTrials.gov, identifier NCT04899960.

Development and validation of machine learning-based clinical decision support tool for identifying malnutrition in NICU patients.

Hospitalized newborns have an increased risk of malnutrition and, especially preterm infants, often experience malnutrition-related extrauterine growth restriction (EUGR). The aim of this study was to predict the discharge weight and the presence of weight gain at discharge with machine learning (ML) algorithms. The demographic and clinical parameters were used to develop the models using fivefold cross-validation in the software-R with a neonatal nutritional screening tool (NNST). A total of 512 NICU patients were prospectively included in the study. Length of hospital stay (LOS), parenteral nutrition treatment (PN), postnatal age (PNA), surgery, and sodium were the most important variables in predicting the presence of weight gain at discharge with a random forest classification (AUROC:0.847). The AUROC of NNST-Plus, which was improved by adding LOS, PN, PNA, surgery, and sodium to NNST, increased by 16.5%. In addition, weight at admission, LOS, gestation-adjusted age at admission (> 40 weeks), sex, gestational age, birth weight, PNA, SGA, complications of labor and delivery, multiple birth, serum creatinine, and PN treatment were the most important variables in predicting discharge weight with an elastic net regression (R2 = 0.748). This is the first study on the early prediction of EUGR with promising clinical performance based on ML algorithms. It is estimated that the incidence of EUGR can be improved with the implementation of this ML-based web tool ( http://www.softmed.hacettepe.edu.tr/NEO-DEER/ ) in clinical practice.

Revisiting the surgical indication of mid-shaft clavicle fractures: Clavicle asymmetry.

OBJECTIVES: The aim of the study was to investigate whether clavicular symmetry was a valid assumption and to assess the factors that could predict clavicular asymmetry. PATIENTS AND METHODS: Between January 2021 and April 2021, a total of 100 consecutive patients (61 males, 39 females; mean age: 63.6±15.5 years; range, 27 to 94 years) whose both clavicles were adequately seen on chest computed tomography (CT) were retrospectively analyzed. Clavicular lengths were measured on three-dimensional (3D) reconstruction of chest CTs by two independent orthopedic surgeons on two separate occasions. The longest distance passing the straight line between the most lateral part of the clavicle at the acromioclavicular joint and the most medial point of the clavicle on the sternoclavicular joint was given as the clavicle length after adjusting tilt of convertible 3D CTs. Clavicular length difference was calculated by subtracting the short clavicle's length from the long clavicle's length. Patients' age and sex were noted. The calculated clavicular length differences were assigned into three groups: ≤5 mm, >5 mm and ≤10 mm, and >10 mm. RESULTS: The mean right and left clavicle lengths were 13.9±1.3 cm and 14.1±1.2 cm, respectively (p<0.001). A total of 29 patients (29%) had >5 mm clavicle asymmetry and six patients (6%) had more than 10 mm clavicular length difference. Age, sex, and clavicular length were not associated with the clavicular length difference. CONCLUSION: Our study results showed that 29% of the patients had >5 mm clavicular length asymmetry. The clavicular symmetry may not be a valid assumption in the decision making for the surgical treatment of mid-shaft clavicle fractures; thus, this assumption may lead to maltreatment. More factors that can predict clavicle asymmetry should be investigated in future studies.

An Artificial Intelligence Approach to Support Detection of Neonatal Adverse Drug Reactions Based on Severity and Probability Scores: A New Risk Score as Web-Tool.

BACKGROUND: Critically ill neonates are at greater risk for adverse drug reactions (ADRs). The differentiation of ADRs from reactions associated with organ dysfunction/immaturity or genetic variability is difficult. METHODS: In this prospective cohort study, each ADR was assessed using newborn-specific severity and probability scales by the clinical pharmacist. Subsequently, a machine learning-based risk score was designed to predict ADR presence in neonates. RESULTS: In 98/412 (23.8%) of (56.3%; male) neonates included, 187 ADRs (0.42 ADR/patient) were determined related to 49 different drugs (37.12%). Drugs identified as high risk were enoxaparin, dexmedetomidine, vinblastine, dornase alfa, etoposide/carboplatin and prednisolone. The independent variables included in the risk score to predict ADR presence, according to the random forest importance criterion, were: systemic hormones (2 points), cardiovascular drugs (3 points), diseases of the circulatory system (1 point), nervous system drugs (1 point), and parenteral nutrition treatment (1 point), (cut-off value: 3 points). This risk score correctly classified 91.1% of the observations in the test set (c-index: 0.914). CONCLUSIONS: Using the high-performing risk score specific to neonates, it is expected that high-risk neonatal ADRs can be determined and prevented before they occur. Moreover, the awareness of clinicians of these drugs can be improved with this web-tool, and mitigation strategies (change of drug, dose, treatment duration, etc.) can be considered, based on a benefit-harm relationship for suspected drugs with a newborn-centered approach.

Population pharmacokinetics in critically ill neonates and infants undergoing extracorporeal membrane oxygenation: a literature review.

Extracorporeal membrane oxygenation (ECMO) increases circulating blood volume, causes capillary leak and temporarily alters kidney function. Consequently, pharmacokinetics (PK) can be affected. When applied to neonates and infants, additional dose adjustments are a major concern, as the volume of distribution (Vd) is already generally greater for water-soluble drugs and the clearance (Cl) of drugs eliminated by glomerular filtration is reduced. A systematic search was performed on MEDLINE (1994-2022) using a combination of the following search terms: "pharmacokinetics", "extracorporeal membrane oxygenation" and "infant, newborn" using Medical Subject Headings search strategy. Nine out of 18 studies on 11 different drugs (vancomycin, meropenem, fluconazole, gentamicin, midazolam, phenobarbital, theophylline, clonidine, morphine, cefotaxime and cefepime) recommended dose increase/decrease by determining PK parameters. In other studies, it has been suggested to adjust the dose intervals. While the elimination half-life (t1/2) and Vd mostly increased for all drugs, the Cl of the drugs has been shown to have variability except for midazolam and morphine. There are a limited number of population PK studies in neonates and infants undergoing ECMO circuits. Despite some divergences, the general pattern suggests an increase in Vd and t1/2, an increased, stable or decreased Cl, and an increase in variability. Consequently, and if possible, therapeutic drug monitoring and target concentration intervention are strongly recommended to determine appropriate exposure and doses for neonates and infants undergoing ECMO support.