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Critical Care and Resuscitation :... Jun 2022Medications prescribed for indications or at doses, frequencies or durations not approved by the Australian Therapeutic Goods Administration are considered "off- label"....
Medications prescribed for indications or at doses, frequencies or durations not approved by the Australian Therapeutic Goods Administration are considered "off- label". Critical illness makes seeking consent for off-label medication use impractical. We aimed to characterise the extent of off-label medication use in a tertiary medical- surgical intensive care unit (ICU) by auditing the electronic health records of all patients admitted over a one-month period. We found 25.4% of 2292 prescriptions made for 142 patients were off-label. Eighty-one (37.2%) of the total of 218 different prescribed medications were used at least once for an off-label indication. Medications commonly prescribed off-label included antacids (pantoprazole, esomeprazole), analgesics (fentanyl, morphine, ketamine, pregabalin), anticonvulsants (levetiracetam), antibiotics (cefazolin, erythromycin), antipsychotics (quetiapine, haloperidol), and cardiovascular agents (metoprolol, clonidine). Nearly all patients (88.0%) received at least one off-label medication during their ICU stay. Most off- label medications were used for conventional (albeit not licensed) reasons, but nine out of 81 (11.1%) were not; for example, acetazolamide for hypertension, aminophylline for oliguria, and dexmedetomidine for seizures. Recognising the challenges of formally registering an indication with the Therapeutic Goods Administration, but also the value of reducing the incidence of medications used for potentially incorrect purposes, we suggest guideline endorsement of what constitutes standard critical care practice as an alternative to regulatory control.
PubMed: 38045597
DOI: 10.51893/2022.2.OA8 -
Minerva Medica Dec 2023
Topics: Humans; Metoprolol; Atrial Fibrillation; Amiodarone; Anti-Arrhythmia Agents; Heart Failure
PubMed: 37021474
DOI: 10.23736/S0026-4806.23.08618-4 -
Clinical Kidney Journal May 2024Despite a lack of clinical trial data, β-blockers are widely prescribed to dialysis patients. Whether specific β-blocker agents are associated with improved long-term...
BACKGROUND
Despite a lack of clinical trial data, β-blockers are widely prescribed to dialysis patients. Whether specific β-blocker agents are associated with improved long-term outcomes compared with alternative β-blocker agents in the dialysis population remains uncertain.
METHODS
We analyzed data from an international cohort study of 10 125 patients on maintenance hemodialysis across 18 countries that were newly prescribed a β-blocker medication within the Dialysis Outcomes and Practice Patterns Study (DOPPS). The following β-blocker agents were compared: metoprolol, atenolol, bisoprolol and carvedilol. Multivariable Cox proportional hazards models were used to estimate the association between the newly prescribed β-blocker agent and all-cause mortality. Stratified analyses were performed on patients with and without a prior history of cardiovascular disease.
RESULTS
The mean (standard deviation) age in the cohort was 63 (15) years and 57% of participants were male. The most commonly prescribed β-blocker agent was metoprolol (49%), followed by carvedilol (29%), atenolol (11%) and bisoprolol (11%). Compared with metoprolol, atenolol {adjusted hazard ratio (HR) 0.77 [95% confidence interval (CI) 0.65-0.90]} was associated with a lower mortality risk. There was no difference in mortality risk with bisoprolol [adjusted HR 0.99 (95% CI 0.82-1.20)] or carvedilol [adjusted HR 0.95 (95% CI 0.82-1.09)] compared with metoprolol. These results were consistent upon stratification of patients by presence or absence of a prior history of cardiovascular disease.
CONCLUSIONS
Among patients on maintenance hemodialysis who were newly prescribed β-blocker medications, atenolol was associated with the lowest mortality risk compared with alternative agents.
PubMed: 38887596
DOI: 10.1093/ckj/sfae087 -
Chemosphere May 2024At present the information regarding the occurrence of human pharmaceuticals (PhaCs) in coral reefs and their potential impacts on the associated fauna is limited. To...
At present the information regarding the occurrence of human pharmaceuticals (PhaCs) in coral reefs and their potential impacts on the associated fauna is limited. To optimize the collection of data in these delicate environments, we employed a solid-phase microextraction (bioSPME) and liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) procedure that enabled in vivo determinations in soft corals. Specifically, we researched the antibiotics Ofloxacin Sulfamethoxazole and Clarithromycin, the anti-inflammatory Diclofenac Propyphenazone Ketoprofen and Amisulpride, the neuroactive compounds Gabapentin-lactam, the beta-blocker Metoprolol and the antiepileptic Carbamazepine. Reproducibility was between 2.1% and 9.9% and method detection limits LODs) were between 0.2 and 1.6 ng/g and LOQs between 0.8 and 5.4 mg/g. The method was then applied to establish a baseline for the occurrence of these compounds in the Maldivian archipelago. Colonies of Sarcophyton sp. and Sinularia sp. were sampled along an inner-outer reef transect. Five of the ten targeted PhaCs were identified, and 40% of the surveyed coral colonies showed the occurrence of at least one of the selected compounds. The highest concentrations were found inside the atoll rim. Oxoflacin (9.5 ± 3.9 ng/g) and Ketoprofen (4.5 ± 2.3 ng/g) were the compounds with the highest average concentrations. Outside the atoll rim, only one sample showed contamination levels above the detection limit. No significant differences were highlighted among the two surveyed soft coral species, both in terms of average concentrations and bioconcentration factors (BCFs).
Topics: Animals; Tandem Mass Spectrometry; Chromatography, Liquid; Water Pollutants, Chemical; Environmental Monitoring; Anthozoa; Pharmaceutical Preparations; Solid Phase Microextraction; Humans; Indian Ocean Islands; Coral Reefs; Limit of Detection; Maldives; Liquid Chromatography-Mass Spectrometry
PubMed: 38554875
DOI: 10.1016/j.chemosphere.2024.141781 -
Computers in Biology and Medicine May 2024Predicting Intensive Care Unit (ICU) Length of Stay (LOS) accurately can improve patient wellness, hospital operations, and the health system's financial status. This...
OBJECTIVE
Predicting Intensive Care Unit (ICU) Length of Stay (LOS) accurately can improve patient wellness, hospital operations, and the health system's financial status. This study focuses on predicting the prolonged ICU LOS (≥3 days) of the 2nd admission, utilizing short historical data (1st admission only) for early-stage prediction, as well as incorporating medication information.
MATERIALS AND METHODS
We selected 18,572 ICU patients' records from the MIMIC-IV database for this study. We applied five machine learning classifiers: Logistic regression (LR), Random Forest (RF), Support Vector Machine (SVM), AdaBoost (AB) and XGBoost (XGB). We computed both the sum dose and the average dose for the medication and included them in our model.
RESULTS
The performance of the RF model demonstrates the highest level of accuracy compared to other models, as indicated by an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.716 and an Expected Calibration Error (ECE) of 0.023.
DISCUSSION
The calibration improved all five classifiers (LR, RF, SVC, AB, XGB) in terms of ECE. The most important two features for RF are the length of 1st admission and the patient's age when they visited the hospital. The most important medication features are Phytonadione and Metoprolol Succinate XL. Also, both the sum and the average dose for the medication features contributed to the prediction task.
CONCLUSION
Our model showed the capability to predict the prolonged ICU LOS of the 2nd admission by utilizing the demographic, diagnosis, and medication information from the 1st admission. This method can potentially support the prevention of patient complications and enhance resource allocation in hospitals.
Topics: Humans; Intensive Care Units; Length of Stay; Female; Male; Middle Aged; Aged; Patient Readmission; Machine Learning; Databases, Factual; Adult
PubMed: 38603899
DOI: 10.1016/j.compbiomed.2024.108451 -
Environmental Science & Technology Oct 2023Subsurface treatment systems, such as constructed wetlands, riverbank filtration systems, and managed aquifer recharge systems, offer a low-cost means of removing trace...
Subsurface treatment systems, such as constructed wetlands, riverbank filtration systems, and managed aquifer recharge systems, offer a low-cost means of removing trace organic contaminants from treated municipal wastewater. To assess the processes through which trace organic contaminants are removed in subsurface treatment systems, pharmaceuticals and several major metabolites were measured in porewater, sediment, and plants within a horizontal levee (i.e., a subsurface flow wetland that receives treated municipal wastewater). Concentrations of trace organic contaminants in each wetland compartment rapidly declined along the flow path. Mass balance calculations, analysis of transformation products, microcosm experiments, and one-dimensional transport modeling demonstrated that more than 60% of the contaminant removal could be attributed to transformation. Monitoring of the system with and without nitrate in the wetland inflow indicated that relatively biodegradable trace organic contaminants, such as acyclovir and metoprolol, were rapidly transformed under both operating conditions. Trace organic contaminants that are normally persistent in biological treatment systems (e.g., sulfamethoxazole and carbamazepine) were removed only when Fe(III)- and sulfate-reducing conditions were observed. Minor structural modifications to trace organic contaminants (e.g., hydroxylation) altered the pathways and extents of trace organic contaminant transformation under different redox conditions. These findings indicate that subsurface treatment systems can be designed to remove both labile and persistent trace organic contaminants via transformation if they are designed and operated in a manner that results in sulfate-and Fe(III)-reducing conditions.
Topics: Wastewater; Ferric Compounds; Sulfates; Water Purification; Organic Chemicals; Water Pollutants, Chemical; Wetlands; Waste Disposal, Fluid
PubMed: 37856881
DOI: 10.1021/acs.est.3c03719 -
Journal of Hazardous Materials Sep 2023Biological oxygen-dosed activated carbon (BODAC) filters in an Ultrapure water plant were demonstrated to have the potential to further treat secondary wastewater...
Biological oxygen-dosed activated carbon (BODAC) filters in an Ultrapure water plant were demonstrated to have the potential to further treat secondary wastewater treatment effluent. The BODAC filters were operated for 11 years without carbon regeneration or replacement, while still functioning as pre-treatment step to reverse osmosis (RO) membranes by actively removing organic micropollutants (OMPs) and foulants. In this study, the removal of nutrients and 13 OMPs from secondary wastewater treatment effluent was investigated for 2 years and simultaneously, the granules' characterization and microbial community analysis were conducted to gain insights behind the stable long-term operation of the BODAC filters. The results showed that the BODAC granules' surface area was reduced by ∼70 % of what is in virgin carbon granules and covered by biofilm and inorganic depositions. The BODAC filters reduced the concentration of soluble organics, mainly proteins, performed as an effective nitrification system, and almost completely removed manganese. During the 2 years of observation, the filters consistently removed some OMPs such as hydrochlorothiazide, metoprolol, sotalol, and trimethoprim by at least 70 %. Finally, through microbial community analysis, we found that nitrifying and manganese-oxidizing bacteria were detected in high relative abundance on BODAC granules, supporting BODAC performance in removing OMPs and manganese as well as converting nitrogenous species in the water.
Topics: Charcoal; Oxygen; Manganese; Water Pollutants, Chemical; Water Purification; Nutrients
PubMed: 37356180
DOI: 10.1016/j.jhazmat.2023.131882 -
The Science of the Total Environment Jan 2024This study evaluates the effectiveness of a pilot-scale high-rate algae-bacteria pond (HRAP) to remove pharmaceutical compounds (PhACs) from municipal centrate. The...
This study evaluates the effectiveness of a pilot-scale high-rate algae-bacteria pond (HRAP) to remove pharmaceutical compounds (PhACs) from municipal centrate. The studied PhACs belonged to different classes of synthetic active compounds: antihypertensives, antiepileptics, antidepressants, neuroprotectors, and anti-inflammatory drugs. The HRAP, growing a mixed microalgal consortium made of Chlorella spp. and Scenedesmus spp., was operated in continuous mode (6 days hydraulic retention time) from May to November 2021. Removal efficiencies were high (>85 %) for Sulfamethoxazole and Lamotrigine, promising (65-70 %) for Metoprolol, Fluoxetine, and Diclofenac but low (30-40 %) for Amisulpride, Ofloxacin, Carbamazepine, and Clarithromycin. Propyphenazone and Irbesartan were not removed, and their concentrations increased after the treatment. The combination of abiotic and biotic drivers (mostly global radiation and the synergy between microalgae and bacteria metabolisms) fostered photo and biodegradation processes. Overall, results suggest that microalgae-based systems can be a valuable solution to remove PhACs from wastewater.
Topics: Sewage; Waste Disposal, Fluid; Ponds; Chlorella; Anaerobiosis; Bacteria; Pharmaceutical Preparations; Microalgae; Biomass
PubMed: 37865249
DOI: 10.1016/j.scitotenv.2023.167881 -
Frontiers in Physiology 2023Atrial fibrillation (AF) is the most common arrhythmia, associated with significant burdens to patients and the healthcare system. The atrioventricular (AV) node plays...
Atrial fibrillation (AF) is the most common arrhythmia, associated with significant burdens to patients and the healthcare system. The atrioventricular (AV) node plays a vital role in regulating heart rate during AF by filtering electrical impulses from the atria. However, it is often insufficient in regards to maintaining a healthy heart rate, thus the AV node properties are modified using rate-control drugs. Moreover, treatment selection during permanent AF is currently done empirically. Quantifying individual differences in diurnal and short-term variability of AV-nodal function could aid in personalized treatment selection. This study presents a novel methodology for estimating the refractory period (RP) and conduction delay (CD) trends, and their uncertainty in the two pathways of the AV node during 24 h using non-invasive data. This was achieved by utilizing a network model together with a problem-specific genetic algorithm and an approximate Bayesian computation algorithm. Diurnal variability in the estimated RP and CD was quantified by the difference between the daytime and nighttime estimates, and short-term variability was quantified by the Kolmogorov-Smirnov distance between adjacent 10-min segments in the 24-h trends. Additionally, the predictive value of the derived parameter trends regarding drug outcome was investigated using several machine learning tools. Holter electrocardiograms from 51 patients with permanent AF during baseline were analyzed, and the predictive power of variations in RP and CD on the resulting heart rate reduction after treatment with four rate control drugs was investigated. Diurnal variability yielded no correlation to treatment outcome, and no prediction of drug outcome was possible using the machine learning tools. However, a correlation between the short-term variability for the RP and CD in the fast pathway and resulting heart rate reduction during treatment with metoprolol ( = 0.48, < 0.005 in RP, = 0.35, < 0.05 in CD) were found. The proposed methodology enables non-invasive estimation of the AV node properties during 24 h, which-indicated by the correlation between the short-term variability and heart rate reduction-may have the potential to assist in treatment selection.
PubMed: 38283279
DOI: 10.3389/fphys.2023.1287365 -
Polymers Oct 2023Nowadays, it is a challenge for a bone scaffold to achieve controllable drug release and a porous structure at the same time. Herein, we fabricated hydroxyapatite/poly...
Nowadays, it is a challenge for a bone scaffold to achieve controllable drug release and a porous structure at the same time. Herein, we fabricated hydroxyapatite/poly (butylene succinate)/metoprolol tartrate (HA/PBS/MPT) composites via melt blending, aiming to provide the option of an in situ pore-forming strategy. The introduction of HA not only significantly improved the hydrophilicity of the PBS matrix by reducing the hydrophilic contact angle by approximately 36% at a 10% content, but also damaged the integrity of the PBS crystal. Both were beneficial for the penetration of phosphate-buffered saline solution into matrix and the acceleration of MPT release. Accompanied with MPT release, porous structures were formed in situ, and the HA inside the matrix was exposed. With the increase in HA content, the MPT release rate accelerated and the pore size became larger. The in vitro cytocompatibility evaluation indicated that HA/PBS/MPT composites were conductive to the adhesion, growth, and proliferation of MC3T3-E1 cells due to the HA being exposed around the pores. Thus, the MPT release rate, pore size, and cell induction ability of the HA/PBS/MPT composites were flexibly and effectively adjusted by the composition at the same time. By introducing HA, we innovatively achieved the construction of porous structures during the drug release process, without the addition of pore-forming agents. This approach allows the drug delivery system to combine controllable drug release and biocompatibility effectively, offering a novel method for bone repair material preparation. This work might provide a convenient and robust strategy for the fabrication of bone scaffolds with controllable drug release and porous structures.
PubMed: 37959885
DOI: 10.3390/polym15214205