Assessing the risk of tumor lysis syndrome associated with the use of antineoplastic agents: a real-world pharmacovigilance study based on the FDA Adverse Event Reporting System database.

Background: The use of antineoplastic agents is one of the important triggers of tumor lysis syndrome (TLS), but there is still a lack of comprehensive understanding of antineoplastic agents that may trigger TLS and the TLS risk differences between different antineoplastic agents. Objectives: This study aims to investigate the TLS risk of different antineoplastic agents and provide reference information for clinical practice. Design: Real-world adverse events data in the FDA Adverse Event Reporting System (FAERS) database were used as the basis for the disproportionality analysis. Methods: We reviewed the TLS reports in the FAERS database from 2004 to 2022 to summarize an antineoplastic agent list that was reported to trigger TLS, based on which we conducted disproportionality analysis to assess the TLS risk of each antineoplastic agent. Results: In all, 164 antineoplastic agents were reported to trigger TLS. On the whole, rituximab was the most reported antineoplastic agent in TLS reports, followed by cyclophosphamide, venetoclax, doxorubicin, and etoposide, while tagraxofusp was the antineoplastic agent with the highest adverse drug reaction (ADR) signal strength in signal detection, followed by floxuridine, pentostatin, tebentafusp, and venetoclax. Integrating ADR signal detection results, 129 of 164 antineoplastic agents showed at least one positive ADR signal, and six antineoplastic agents (bevacizumab, carboplatin, cisplatin, fluorouracil, lenvatinib, and paclitaxel) have the highest total number of positive signals. Further classifying the 164 antineoplastic agents into 46 chemical subgroups to conduct ADR signal detection, nitrogen mustard analogs were the most reported antineoplastic agent subclasses, followed by clusters of differentiation 20 inhibitors, and pyrimidine analogs, while clusters of differentiation 22 inhibitors were the antineoplastic agent subclass with the highest ADR signal strength, followed by podophyllotoxin derivatives and actinomycines. Conclusion: Our study showed the TLS risk characteristics of 164 antineoplastic agents by detecting and integrating ADR signals, which may help to optimize clinical practice.

METHODS: Using data from the FDA Adverse Event Reporting System (FAERS) between the years 2004 and 2022, we reviewed TLS reports associated with antineoplastic agent exposure, summarized an antineoplastic agent list that was reported as the potential culprit-drug of TLS, and explored the TLS risk of different antineoplastic agents by disproportionality analysis. RESULTS: Our results showed that 164 antineoplastic agents, involving 64 antineoplastic agent subclasses, were reported as the potential culprit-drug of TLS in the FAERS database, in which 129 antineoplastic agents and 39 antineoplastic agent subclasses were associated with increased TLS risk to varying degrees. CONCLUSIONS: Our research expounded the differences in TLS risks of different antineoplastic agents, which helps us pay attention to the occurrence of TLS and give timely treatment when prescribing high-TLS-risk antineoplastic agents to patients.

Antineoplastic agent and the risk of tumor lysis syndrome Background: Antineoplastic agents are medicines that help treat cancer. It is one of the most outstanding achievements of human beings in medicine, which plays an increasingly important role in improving human health and prolonging the life span of cancer patients. However, adverse reactions (ADRs) associated with the use of antineoplastic agents may also cause unexpected harm to patients. Therefore, it is essential to have a comprehensive understanding of antineoplastic-related ADRs to ensure the lives of cancer patients. Tumor lysis syndrome (TLS) is a potentially life-threatening ADR that may occur during antineoplastic agent treatment. However, there is still a lack of comprehensive understanding of antineoplastic agents that may trigger TLS and their risk differences. This study aimed to comprehensively investigate the TLS risk of antineoplastic agents from the pharmacovigilance perspective, providing reference information for patients, health professionals, regulators, and others concerned with antineoplastic agent safety.

Homotypic cell-in-cell structure as a novel prognostic predictor in non-small cell lung cancer and frequently localized at the invasive front.

Homotypic cell-in-cell structures (hoCICs) are associated with tumor proliferation, invasion, and metastasis and is considered a promising prognostic marker in various cancers. However, the role of hoCICs in non-small cell lung cancer (NSCLC) remains unclear. Tumor tissue sections were obtained from 411 NSCLC patients. We analyzed the relationship between clinicopathological variables and the number of hoCICs. LASSO and multivariate Cox regression analysis were employed to identify prognostic factors for NSCLC. The impact of hoCICs on overall survival (OS) and disease-free survival (DFS) was assessed using the Kaplan-Meier curves and log-rank test. Prognostic models for OS and DFS were developed and validated using the C-index, time-dependent area under the curve (AUC), net reclassification improvement (NRI), integrated discrimination improvement (IDI), calibration curves and decision curve analysis (DCA). Among the cohort, 56% of patients had hoCICs while 44% did not. Notably, hoCICs were primarily found at the tumor invasion front. Male gender, smoking, squamous cell carcinoma, low differentiation, tumor size ≥ 3 cm, advanced TNM stage, lymph node metastasis, pleural invasion, vascular invasion, necrosis, P53 mutation, and high expression of Ki-67 were identified as relative risk factors for hoCICs. Furthermore, hoCICs was found to be a significant prognostic factor for both OS and DFS, with higher frequencies of hoCICs correlating with poorer outcomes. We constructed nomograms for predicting 1-, 3-, and 5-year OS and DFS based on hoCICs, and the calibration curves showed good agreement between the predicted and actual outcomes. The results of the C-index, time-dependent AUC, NRI, IDI, and DCA analyses demonstrated that incorporating hoCICs into the prognostic model significantly enhanced its predictive power and clinical applicability. HoCICs indicated independent perdictive value for OS and DFS in patients with NSCLC. Furthermore, the frequent localization of hoCICs at the tumor invasion front suggested a strong association between hoCICs and tumor invasion as well as metastasis.

Drug-induced erectile dysfunction: a real-world pharmacovigilance study using the FDA adverse event reporting system database.

BACKGROUND: The comprehensive quantitative and comparative risk data of drug-induced erectile dysfunction (ED) are still lacking, and this study aims to supplement this information. RESEARCH DESIGN AND METHODS: We reviewed all the ED reports in the FDA Adverse Event Reporting System (FAERS) database from 2004 to 2023 and summarized a potential ED culprit-drug list and its corresponding reporting frequency. The reporting odds ratio (ROR) method was used to conduct disproportionality analysis. RESULTS: A total of 20,098 ED reports were retrieved from the FAERS database, which recorded 734 different ED culprit-drugs, involving 74 drug classes. Finasteride was the drug with the highest reporting frequency, and urologicals was the drug class with the highest reporting frequency. In disproportionality analysis, 209 drugs with positive signals showed a close relationship with ED occurrence, among which finasteride was the drug with the highest signal strength. Among 209 drugs with positive signals, 27 were compound preparations, and the risk level of compound preparations was usually higher than their single active ingredient. CONCLUSIONS: Our study integrated quantitative and comparative ED risk data of 734 drugs by using the FAERS database, which can provide reference information for regulators, medical personnel, and others involved in drug management and use.

Real-time IMU-Based Kinematics in the Presence of Wireless Data Drop.

Wireless inertial motion capture holds promise for real-time human-machine interfaces and home-based rehabilitation applications. However, wireless data drop can cause significant estimation errors deteriorating performance or even making the system unusable. It is currently unclear how to estimate non-periodic kinematics with wearable inertial measurement units (IMUs) in the presence of wireless data drop (packet loss). We thus propose a novel inference encoder-decoder network model for real-time kinematics during dynamic movement. Twenty-four healthy subjects performed yoga, golf, swimming, dance, and badminton movement activities while wearing IMUs and 10-90% of each IMU's data were randomly removed to determine the effects of data drop on estimation accuracy with and without the proposed model. Results demonstrated a reduction in RMSE of 45.2% to 51.5% in the upper limb kinematic estimation of the proposed model compared to the No Prediction strategy, and a reduction of 19.1% to 31.3% of the proposed model compared with an baseline LSTM model. In addition, the proposed model has significantly less error (p<0.05) than the No Prediction strategy and the baseline LSTM model for 10%, 20%, 30%, 40%, 50%, 60%, 70%, and 80% data drop. These results could enable wearable, wireless IMU dynamic motion analysis and assessment with reduced kinematic estimation error in the presence of varying amounts of wireless data drop and thus could further facilitate human-machine interaction and home-based medical assessment and treatment.

Automated, IMU-based spine angle estimation and IMU location identification for telerehabilitation.

BACKGROUND: Telerehabilitation is a promising avenue for improving patient outcomes and expanding accessibility. However, there is currently no spine-related assessment for telerehabilitation that covers multiple exercises. METHODS: We propose a wearable system with two inertial measurement units (IMUs) to identify IMU locations and estimate spine angles for ten commonly prescribed spinal degeneration rehabilitation exercises (supine chin tuck head lift rotation, dead bug unilateral isometric hold, pilates saw, catcow full spine, wall angel, quadruped neck flexion/extension, adductor open book, side plank hip dip, bird dog hip spinal flexion, and windmill single leg). Twelve healthy subjects performed these spine-related exercises, and wearable IMU data were collected for spine angle estimation and IMU location identification. RESULTS: Results demonstrated average mean absolute spinal angle estimation errors of 2.59 ∘ and average classification accuracy of 92.97%. The proposed system effectively identified IMU locations and assessed spine-related rehabilitation exercises while demonstrating robustness to individual differences and exercise variations. CONCLUSION: This inexpensive, convenient, and user-friendly approach to spine degeneration rehabilitation could potentially be implemented at home or provide remote assessment, offering a promising avenue to enhance patient outcomes and improve accessibility for spine-related rehabilitation. TRIAL REGISTRATION:  No. E2021013P in Shanghai Jiao Tong University.

Ferroptosis and hepatocellular carcinoma: the emerging role of lncRNAs.

Hepatocellular carcinoma is the most common form of primary liver cancer and poses a significant challenge to the medical community because of its high mortality rate. In recent years, ferroptosis, a unique form of cell death, has garnered widespread attention. Ferroptosis, which is characterized by iron-dependent lipid peroxidation and mitochondrial alterations, is closely associated with the pathological processes of various diseases, including hepatocellular carcinoma. Long non-coding RNAs (lncRNAs), are a type of functional RNA, and play crucial regulatory roles in a variety of biological processes. In this manuscript, we review the regulatory roles of lncRNAs in the key aspects of ferroptosis, and summarize the research progress on ferroptosis-related lncRNAs in hepatocellular carcinoma.

Radiotherapy activates picolinium prodrugs in tumours.

Radiotherapy-induced prodrug activation provides an ideal solution to reduce the systemic toxicity of chemotherapy in cancer therapy, but the scope of the radiation-activated protecting groups is limited. Here we present that the well-established photoinduced electron transfer chemistry may pave the way for developing versatile radiation-removable protecting groups. Using a functional reporter assay, N-alkyl-4-picolinium (NAP) was identified as a caging group that efficiently responds to radiation by releasing a client molecule. When evaluated in a competition experiment, the NAP moiety is more efficient than other radiation-removable protecting groups discovered so far. Leveraging this property, we developed a NAP-derived carbamate linker that releases fluorophores and toxins on radiation, which we incorporated into antibody-drug conjugates (ADCs). These designed ADCs were active in living cells and tumour-bearing mice, highlighting the potential to use such a radiation-removable protecting group for the development of next-generation ADCs with improved stability and therapeutic effects.

Graph-Driven Simultaneous and Proportional Estimation of Wrist Angle and Grasp Force via High-Density EMG.

Myoelectric prostheses are generally unable to accurately control the position and force simultaneously, prohibiting natural and intuitive human-machine interaction. This issue is attributed to the limitations of myoelectric interfaces in effectively decoding multi-degree-of-freedom (multi-DoF) kinematic and kinetic information. We thus propose a novel multi-task, spatial-temporal model driven by graphical high-density electromyography (HD-EMG) for simultaneous and proportional control of wrist angle and grasp force. Twelve subjects were recruited to perform three multi-DoF movements, including wrist pronation/supination, wrist flexion/extension, and wrist abduction/adduction while varying grasp force. Experimental results demonstrated that the proposed model outperformed five baseline models, with the normalized root mean square error of 13.2% and 9.7% and the correlation coefficient of 89.6% and 91.9% for wrist angle and grasp force estimation, respectively. In addition, the proposed model still maintained comparable accuracy even with a significant reduction in the number of HD-EMG electrodes. To the best of our knowledge, this is the first study to achieve simultaneous and proportional wrist angle and grasp force control via HD-EMG and has the potential to empower prostheses users to perform a broader range of tasks with greater precision and control, ultimately enhancing their independence and quality of life.

3D Knee and Hip Angle Estimation With Reduced Wearable IMUs via Transfer Learning During Yoga, Golf, Swimming, Badminton, and Dance.

Wearable lower-limb joint angle estimation using a reduced inertial measurement unit (IMU) sensor set could enable quick, economical sports injury risk assessment and motion capture; however the vast majority of existing research requires a full IMU set attached to every related body segment and is implemented in only a single movement, typically walking. We thus implemented 3-dimensional knee and hip angle estimation with a reduced IMU sensor set during yoga, golf, swimming (simulated lower body swimming in a seated posture), badminton, and dance movements. Additionally, current deep-learning models undergo an accuracy drop when tested with new and unseen activities, which necessitates collecting large amounts of data for the new activity. However, collecting large datasets for every new activity is time-consuming and expensive. Thus, a transfer learning (TL) approach with long short-term memory neural networks was proposed to enhance the model's generalization ability towards new activities while minimizing the need for a large new-activity dataset. This approach could transfer the generic knowledge acquired from training the model in the source-activity domain to the target-activity domain. The maximum improvement in estimation accuracy (RMSE) achieved by TL is 23.6 degrees for knee flexion/extension and 22.2 degrees for hip flexion/extension compared to without TL. These results extend the application of motion capture with reduced sensor configurations to a broader range of activities relevant to injury prevention and sports training. Moreover, they enhance the capacity of data-driven models in scenarios where acquiring a substantial amount of training data is challenging.

Drug-Induced Acute Pancreatitis: A Real-World Pharmacovigilance Study Using the FDA Adverse Event Reporting System Database.

Timely identification and discontinuation of culprit-drug is the cornerstone of clinical management of drug-induced acute pancreatitis (AP), but the comprehensive landscape of AP culprit-drugs is still lacking. To provide the current overview of AP culprit-drugs to guide clinical practice, we reviewed the adverse event (AE) reports associated with AP in the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) database from 2004 to 2022, and summarized a potential AP culprit-drug list and its corresponding AE report quantity proportion. The disproportionality analysis was used to detect adverse drug reaction (ADR) signals for each drug in the drug list, and the ADR signal distribution was integrated to show the risk characteristic of drugs according to the ADR signal detection results. In the FAERS database, a total of 62,206 AE reports were AP-related, in which 1,175 drugs were reported as culprit-drug. On the whole, metformin was the drug with the greatest number of AE reports, followed by quetiapine, liraglutide, exenatide, and sitagliptin. Drugs used in diabetes was the drug class with the greatest number of AE reports, followed by immunosuppressants, psycholeptics, drugs for acid-related disorders, and analgesics. In disproportionality analysis, 595 drugs showed potential AP risk, whereas 580 drugs did not show any positive ADR signal. According to the positive-negative distribution of the ADR signal for drug classes, the drug class with the greatest number of positive drugs was antineoplastic agents. In this study, we provided the current comprehensive landscape of AP culprit-drugs from the pharmacovigilance perspective, which can provide reference information for clinical practice.

Nucleation Domains in Biomineralization: Biomolecular Sequence and Conformational Features.

Biomolecules play a vital role in the regulation of biomineralization. However, the characteristics of practical nucleation domains are still sketchy. Herein, the effects of the representative biomolecular sequence and conformations on calcium phosphate (Ca-P) nucleation and mineralization are investigated. The results of computer simulations and experiments prove that the line in the arrangement of dual acidic/essential amino acids with a single interval (Bc (Basic) -N (Neutral) -Bc-N-Ac (Acidic)- NN-Ac-N) is most conducive to the nucleation. 2α-helix conformation can best induce Ca-P ion cluster formation and nucleation. "Ac- × × × -Bc" sequences with α-helix are found to be the features of efficient nucleation domains, in which process, molecular recognition plays a non-negligible role. It further indicates that the sequence determines the potential of nucleation/mineralization of biomolecules, and conformation determines the ability of that during functional execution. The findings will guide the synthesis of biomimetic mineralized materials with improved performance for bone repair.

IMU Shoulder Angle Estimation: Effects of Sensor-to-Segment Misalignment and Sensor Orientation Error.

Accurate shoulder joint angle estimation is crucial for analyzing joint kinematics and kinetics across a spectrum of movement applications including in athletic performance evaluation, injury prevention, and rehabilitation. However, accurate IMU-based shoulder angle estimation is challenging and the specific influence of key error factors on shoulder angle estimation is unclear. We thus propose an analytical model based on quaternions and rotation vectors that decouples and quantifies the effects of two key error factors, namely sensor-to-segment misalignment and sensor orientation estimation error, on shoulder joint rotation error. To validate this model, we conducted experiments involving twenty-five subjects who performed five activities: yoga, golf, swimming, dance, and badminton. Results showed that improving sensor-to-segment misalignment along the segment's extension/flexion dimension had the most significant impact in reducing the magnitude of shoulder joint rotation error. Specifically, a 1° improvement in thorax and upper arm calibration resulted in a reduction of 0.40° and 0.57° in error magnitude. In comparison, improving IMU heading estimation was only roughly half as effective (0.23° per 1°). This study clarifies the relationship between shoulder angle estimation error and its contributing factors, and identifies effective strategies for improving these error factors. These findings have significant implications for enhancing the accuracy of IMU-based shoulder angle estimation, thereby facilitating advancements in IMU-based upper limb rehabilitation, human-machine interaction, and athletic performance evaluation.

CD4+ T-cell subsets in autoimmune hepatitis: A review.

Autoimmune hepatitis (AIH) is a chronic autoimmune liver disease that can lead to hepatocyte destruction, inflammation, liver fibrosis, cirrhosis, and liver failure. The diagnosis of AIH requires the identification of lymphoblast cell interface hepatitis and serum biochemical abnormalities, as well as the exclusion of related diseases. According to different specific autoantibodies, AIH can be divided into AIH-1 and AIH-2. The first-line treatment for AIH is a corticosteroid and azathioprine regimen, and patients with liver failure require liver transplantation. However, the long-term use of corticosteroids has obvious side effects, and patients are prone to relapse after drug withdrawal. Autoimmune diseases are characterized by an imbalance in immune tolerance of self-antigens, activation of autoreactive T cells, overactivity of B cells, and increased production of autoantibodies. CD4+ T cells are key players in adaptive immunity and can secrete cytokines, activate B cells to produce antibodies, and influence the cytotoxicity of CD8+ T cells. According to their characteristics, CD4+ T cells can be divided into different subsets. In this review, we discuss the changes in T helper (Th)1, Th2, Th17, Th9, Th22, regulatory T cell, T follicular helper, and T peripheral helper cells and their related factors in AIH and discuss the therapeutic potential of targeting CD4+ T-cell subsets in AIH.

Efficient Osteogenic Activity of PEEK Surfaces Achieved by Femtosecond Laser-Hydroxylation.

Poly(etheretherketone) (PEEK) is regarded as an attractive orthopedic material because of its good biocompatibility and mechanical properties similar to natural bone. The efficient activation methods for the surfaces of PEEK matrix materials have become a hot research topic. In this study, a method using a femtosecond laser (FSL) followed by hydroxylation was developed to achieve efficient bioactivity. It produces microstructures, amorphous carbon, and grafted -OH groups on the PEEK surface to enhance hydrophilicity and surface energy. Both experimental and simulation results show that our modification leads to a superior ability to induce apatite deposition on the PEEK surface. The results also demonstrate that efficient grafting of C-OH through FSL-hydroxylation can effectively enhance cell proliferation and osteogenic differentiation compared to other modifications, thus improving osteogenic activity. Overall, FSL hydroxylation treatment is proved to be a simple, efficient, and environmentally friendly modification method for PEEK activation. It could expand the applications of PEEK in orthopedics, as well as promote the surface modification and structural design of other polymeric biomaterials to enhance bioactivity.

Real-World Data in Pharmacovigilance Database Provides a New Perspective for Understanding the Risk of Clostridium difficile Infection Associated with Antibacterial Drug Exposure.

Antibacterial drug exposure (ADE) is a well-known potential risk factor for Clostridium difficile infection (CDI), but it remains controversial which certain antibacterial drugs are associated with the highest risk of CDI occurrence. To summarize CDI risk associated with ADE, we reviewed the CDI reports related to ADE in the FDA Adverse Event Reporting System database and conducted disproportionality analysis to detect adverse reaction (ADR) signals of CDI for antibacterial drugs. A total of 8063 CDI reports associated with ADE were identified, which involved 73 antibacterial drugs. Metronidazole was the drug with the greatest number of reports, followed by vancomycin, ciprofloxacin, clindamycin and amoxicillin. In disproportionality analysis, metronidazole had the highest positive ADR signal strength, followed by vancomycin, cefpodoxime, ertapenem and clindamycin. Among the 73 antibacterial drugs, 58 showed at least one positive ADR signal, and ceftriaxone was the drug with the highest total number of positive signals. Our study provided a real-world overview of CDI risk for AED from a pharmacovigilance perspective and showed risk characteristics for different antibacterial drugs by integrating its positive-negative signal distribution. Meanwhile, our study showed that the CDI risk of metronidazole and vancomycin may be underestimated, and it deserves further attention and investigation.

Real-Time Ground Reaction Force and Knee Extension Moment Estimation During Drop Landings Via Modular LSTM Modeling and Wearable IMUs.

This work investigates real-time estimation of vertical ground reaction force (vGRF) and external knee extension moment (KEM) during single- and double-leg drop landings via wearable inertial measurement units (IMUs) and machine learning. A real-time, modular LSTM model with four sub-deep neural networks was developed to estimate vGRF and KEM. Sixteen subjects wore eight IMUs on the chest, waist, right and left thighs, shanks, and feet and performed drop landing trials. Ground embedded force plates and an optical motion capture system were used for model training and evaluation. During single-leg drop landings, accuracy for the vGRF and KEM estimation was R2 = 0.88 ± 0.12 and R2 = 0.84 ± 0.14, respectively, and during double-leg drop landings, accuracy for the vGRF and KEM estimation was R2 = 0.85 ± 0.11 and R2 = 0.84 ± 0.12, respectively. The best vGRF and KEM estimations of the model with the optimal LSTM unit number (130) require eight IMUs placed on the eight selected locations during single-leg drop landings. During double-leg drop landings, the best estimation on a leg only needs five IMUs placed on the chest, waist, and the leg's shank, thigh, and foot. The proposed modular LSTM-based model with optimally-configurable wearable IMUs can accurately estimate vGRF and KEM in real-time with relatively low computational cost during single- and double-leg drop landing tasks. This investigation could potentially enable in-field, non-contact anterior cruciate ligament injury risk screening and intervention training programs.

Severe cutaneous adverse reactions to drugs: A real-world pharmacovigilance study using the FDA Adverse Event Reporting System database.

Background: Sound drug safety information is important to optimize patient management, but the widely recognized comprehensive landscape of culprit-drugs that cause severe cutaneous adverse reactions (SCARs) is currently lacking. Objective: The main aim of the study is to provide a comprehensive landscape of culprit-drugs for SCARs to guide clinical practice. Methods: We analyzed reports associated with SCARs in the FDA Adverse Event Reporting System database between 1 January 2004 and 31 December 2021 and compiled a list of drugs with potentially serious skin toxicity. According to this list, we summarized the reporting proportions of different drugs and drug classes and conducted disproportionality analysis for all the drugs. In addition, the risk characteristic of SCARs due to different drugs and drug classes was summarized by the positive-negative distribution based on the results of the disproportionality analysis. Results: A total of 77,789 reports in the FDA Adverse Event Reporting System database were considered SCAR-related, of which lamotrigine (6.2%) was the most reported single drug followed by acetaminophen (5.8%) and allopurinol (5.8%) and antibacterials (20.6%) was the most reported drug class followed by antiepileptics (16.7%) and antineoplastics (11.3%). A total of 1,219 drugs were reported as culprit-drugs causing SCARs in those reports, and the largest number of drugs belonged to antineoplastics. In disproportionality analysis, 776 drugs showed at least one positive pharmacovigilance signal. Drugs with the most positive signals were lamotrigine, acetaminophen, furosemide, and sulfamethoxazole/trimethoprim. Conclusion: Our study provided a real-world overview of SCARs to drugs, and the investigation of SCAR positive-negative distribution across different drugs revealed its risk characteristics, which may help optimize patient management.

The impact of pharmacist early active consultation (PEAC) on multidrug resistance organism treatment outcomes: A prospective historically controlled study.

Background and aim: Infectious disease (ID) consultation can improve multidrug-resistant organism (MDRO) treatment outcomes. However, the impact of clinical pharmacists' ID consultation on MDRO therapy, especially early initiation, has not been reported. In this study, we try to explore the impact of the pharmacist early active consultation (PEAC) on MDRO patient management. Methods: We conducted a prospective historical controlled study based on PEAC in MDRO patients. The retrospective control group was patients hospitalized 18 months before the PEAC initiation, and the prospective PEAC group was patients hospitalized 18 months after the PEAC initiation. Primary endpoint was 30-day all-cause mortality. Secondary outcomes were MDRO clinical outcome, duration of antibiotic use, length of stay, antibiotic consumption and antibiotic costs. Further subgroup analysis of secondary outcomes was performed by the condition at admission, MDRO pathogenicity and MDRO clinical outcome. Results: 188 MDRO patients were included. After adjusting for potential predictors, PEAC reduced the 30-day all-cause mortality by 70% (HR 0.30, 95% CI 0.09-0.96, p = 0.042). PEAC group had clinical improvement than control group (89.47% vs. 65.59%, p < 0.001), especially in patients with non-severe clinical conditions at admission (98.41% vs. 70.18%, p < 0.001). However, no significant differences were found between groups in length of stay, antibiotics consumption, and antibiotics costs. Conclusion: Early active pharmacy ID consultation can reduce 30-day all-cause mortality and improve clinical outcomes in MDRO patients.

Drug-induced QT prolongation and torsade de pointes: a real-world pharmacovigilance study using the FDA Adverse Event Reporting System database.

Introduction: Drug-induced QT prolongation and (or) Torsade de Pointes (TdP) is a well-known serious adverse reaction (ADR) for some drugs, but the widely recognized comprehensive landscape of culprit-drug of QT prolongation and TdP is currently lacking. Aim: To identify the top drugs reported in association with QT prolongation and TdP and provide information for clinical practice. Method: We reviewed the reports related to QT prolongation and TdP in the FDA Adverse Event Reporting System (FAERS) database from January 1, 2004 to December 31, 2022, and summarized a potential causative drug list accordingly. Based on this drug list, the most frequently reported causative drugs and drug classes of QT prolongation and TdP were counted, and the disproportionality analysis for all the drugs was conducted to in detect ADR signal. Furthermore, according to the positive-negative distribution of ADR signal, we integrated the risk characteristic of QT prolongation and TdP in different drugs and drug class. Results: A total of 42,713 reports in FAERS database were considered to be associated with QT prolongation and TdP from 2004 to 2022, in which 1,088 drugs were reported as potential culprit-drugs, and the largest number of drugs belonged to antineoplastics. On the whole, furosemide was the most frequently reported drugs followed by acetylsalicylic acid, quetiapine, citalopram, metoprolol. In terms of drug classes, psycholeptics was the most frequently reported drug classes followed by psychoanaleptics, analgesics, beta blocking agents, drugs for acid related disorders. In disproportionality analysis, 612 drugs showed at least one positive ADR signals, while citalopram, ondansetron, escitalopram, loperamide, and promethazine were the drug with the maximum number of positive ADR signals. However, the positive-negative distribution of ADR signals between different drug classes showed great differences, representing the overall risk difference of different drug classes. Conclusion: Our study provided a real-world overview of QT prolongation and TdP to drugs, and the presentation of the potential culprit-drug list, the proportion of reports, the detection results of ADR signals, and the distribution characteristics of ADR signals may help understand the safety profile of drugs and optimize clinical practice.

Asparaginase-related diabetic ketoacidosis: Analysis of the FDA Adverse Event Reporting System (FAERS) data and literature review.

WHAT IS KNOWN AND OBJECTIVE: Diabetic ketoacidosis (DKA) may occur during asparaginase use. However, limited by the study population, the association between asparaginase and DKA has not been elucidated. The purpose of this study was to determine the potential association between asparaginase and DKA and analyse related clinical characteristics and possible risk factor. METHODS: Disproportionality analysis with the reporting odd ratio (ROR) was used to detect the adverse reaction signals of asparaginase-associated DKA in Food and Drug Administration Adverse Event Reporting System (FAERS). A literature review was conducted to further analyse clinical characteristics, possible risk factor and something noteworthy in asparaginase-associated DKA. RESULTS AND DISCUSSION: A total of 12 reports of DKA associated with l-asparaginase (l-asp) and 6 reports associated with pegaspargase (PEG-asp) were extracted in FAERS, more than 50% of the cases were classified as serious adverse events. DKA was a positive signal of l-asp (ROR = 2.397, 95% CI 1.360-4.226), while not closely related to the use of PEG-asp (ROR = 1.602, 95% CI 0.719-3.570). Searched in PubMed, Embase and Web of Science, a total of eight patients were collected. The patients were mainly adolescent patients, aged between 11 and 25 years old with a median age of 16 years. Drug dosage form distribution is unbalanced, 7 patients received l-asp and only 1 received PEG-asp. WHAT IS NEW AND CONCLUSIONS: The ROR of KDA caused by l-asp was statistically significant, but there was not a statistical association for DKA caused by PEG-asp. Asparaginase dosage form may affect the occurrence of DKA, but further research is needed.