Application of deep learning in isolated tooth identification.

BACKGROUND: Teeth identification has a pivotal role in the dental curriculum and provides one of the important foundations of clinical practice. Accurately identifying teeth is a vital aspect of dental education and clinical practice, but can be challenging due to the anatomical similarities between categories. In this study, we aim to explore the possibility of using a deep learning model to classify isolated tooth by a set of photographs. METHODS: A collection of 5,100 photographs from 850 isolated human tooth specimens were assembled to serve as the dataset for this study. Each tooth was carefully labeled during the data collection phase through direct observation. We developed a deep learning model that incorporates the state-of-the-art feature extractor and attention mechanism to classify each tooth based on a set of 6 photographs captured from multiple angles. To increase the validity of model evaluation, a voting-based strategy was applied to refine the test set to generate a more reliable label, and the model was evaluated under different types of classification granularities. RESULTS: This deep learning model achieved top-3 accuracies of over 90% in all classification types, with an average AUC of 0.95. The Cohen's Kappa demonstrated good agreement between model prediction and the test set. CONCLUSIONS: This deep learning model can achieve performance comparable to that of human experts and has the potential to become a valuable tool for dental education and various applications in accurately identifying isolated tooth.

E-MFNN: an emotion-multimodal fusion neural network framework for emotion recognition.

Emotional recognition is a pivotal research domain in computer and cognitive science. Recent advancements have led to various emotion recognition methods, leveraging data from diverse sources like speech, facial expressions, electroencephalogram (EEG), electrocardiogram, and eye tracking (ET). This article introduces a novel emotion recognition framework, primarily targeting the analysis of users' psychological reactions and stimuli. It is important to note that the stimuli eliciting emotional responses are as critical as the responses themselves. Hence, our approach synergizes stimulus data with physical and physiological signals, pioneering a multimodal method for emotional cognition. Our proposed framework unites stimulus source data with physiological signals, aiming to enhance the accuracy and robustness of emotion recognition through data integration. We initiated an emotional cognition experiment to gather EEG and ET data alongside recording emotional responses. Building on this, we developed the Emotion-Multimodal Fusion Neural Network (E-MFNN), optimized for multimodal data fusion to process both stimulus and physiological data. We conducted extensive comparisons between our framework's outcomes and those from existing models, also assessing various algorithmic approaches within our framework. This comparison underscores our framework's efficacy in multimodal emotion recognition. The source code is publicly available at https://figshare.com/s/8833d837871c78542b29.

Iron-catalyzed stereoselective C-H alkylation for simultaneous construction of C-N axial and C-central chirality.

The assembly of chiral molecules with multiple stereogenic elements is challenging, and, despite of indisputable advances, largely limited to toxic, cost-intensive and precious metal catalysts. In sharp contrast, we herein disclose a versatile C-H alkylation using a non-toxic, low-cost iron catalyst for the synthesis of substituted indoles with two chiral elements. The key for achieving excellent diastereo- and enantioselectivity was substitution on a chiral N-heterocyclic carbene ligand providing steric hindrance and extra represented by noncovalent interaction for the concomitant generation of C-N axial chirality and C-stereogenic center. Experimental and computational mechanistic studies have unraveled the origin of the catalytic efficacy and stereoselectivity.

The Effect of Musical Environments on Designers' Attention: Persistent Music Listening Interferes with Attention.

Research indicates that music can influence human cognitive functions. Diverse musical settings can affect alertness, orientation, and executive control of attention in various populations. Exploring the relationship between designers with highly creative thinking and music environments can provide new research perspectives for the cognitive field. A total of 94 students, consisting of 61 design majors and 33 non-design majors, completed the Attention Network Test (ANT) on a computer under three test environments: cheerful music, melancholic music, and silence. The study results indicated that the alerting network effect between the design professional group and the control group was marginally significant. However, there were no significant differences between the groups in the orienting subsystem and the executive control subsystem. Within the design professional group, the attentional network data indicated that participants showed improved performance in alerting and orienting attention in a music-free environment compared to cheerful and melancholic music environments (pa = 0.028, po = 0.008). Nevertheless, executive control attention did not show significant differences across the music environments. In conclusion, existing research confirms that designers are more susceptible to distraction from external stimuli; thus, music-free environments assist them in concentrating.

Nickel-Catalyzed Atroposelective C-H Alkylation Enabled by Bimetallic Catalysis with Air-Stable Heteroatom-Substituted Secondary Phosphine Oxide Preligands.

The catalytic asymmetric construction of axially chiral C-N atropisomers remains a formidable challenge due to their low rotational barriers and is largely reliant on toxic, cost-intensive, and precious metal catalysts. In sharp contrast, we herein describe the first nickel-catalyzed atroposelective C-H alkylation for the construction of C-N axially chiral compounds with the aid of a chiral heteroatom-substituted secondary phosphine oxide (HASPO)-ligated Ni-Al bimetallic catalyst. A wide range of alkenes, including terminal and internal alkenes, were well compatible with the reaction, providing a variety of benzimidazole derivatives in high yields and enantioselectivities (up to 97:3 e.r.). The key to success was the identification of novel HASPOs as highly effective chiral preligands. Mechanistic studies revealed the catalyst mode of action, and in-depth data science analysis elucidated the key features of the responsible chiral preligands in controlling the enantioselectivity.

Neoadjuvant therapy in renal cell carcinoma with tumor thrombus: A systematic review and meta-analysis.

To evaluate the efficacy, feasibility and safety of neoadjuvant therapy (NAT) for renal cell carcinoma with tumor thrombus (RCC-TT) in terms of response, perioperative and oncological outcomes, and compare the results between neoadjuvant and non-neoadjuvant groups. Overall, 29 single-arm studies and 5 cohort studies were included. Of the 204 patients undergoing NAT, 16.2% were level I, 35.3% level II, 24.0% level III and 18.6% level IV thrombus. Most of patients underwent preoperative targeted therapy, immunotherapy-based combination therapy was applied in 5.4% patients. The total reduction rate of thrombus level was 29.4%. NAT is associated with a shorter operative time, less blood loss (p<0.05 for both). Rate of complications and oncological outcomes were similar between two groups. Overall, 32.1% (34/106) ≥ grade 3 adverse events occurred in patients undergoing NAT. Neoadjuvant therapy is safe and feasible with acceptable perioperative outcomes in RCC-TT.

Application of metal-organic frameworks-based functional composite scaffolds in tissue engineering.

With the rapid development of materials science and tissue engineering, a variety of biomaterials have been used to construct tissue engineering scaffolds. Due to the performance limitations of single materials, functional composite biomaterials have attracted great attention as tools to improve the effectiveness of biological scaffolds for tissue repair. In recent years, metal-organic frameworks (MOFs) have shown great promise for application in tissue engineering because of their high specific surface area, high porosity, high biocompatibility, appropriate environmental sensitivities and other advantages. This review introduces methods for the construction of MOFs-based functional composite scaffolds and describes the specific functions and mechanisms of MOFs in repairing damaged tissue. The latest MOFs-based functional composites and their applications in different tissues are discussed. Finally, the challenges and future prospects of using MOFs-based composites in tissue engineering are summarized. The aim of this review is to show the great potential of MOFs-based functional composite materials in the field of tissue engineering and to stimulate further innovation in this promising area.

Cerebral asymmetry in adult Macaca fascicularis as revealed by voxel-based MRI and DTI analysis.

Investigating cerebral asymmetries in non-human primates would facilitate to understand the evolutional traits of the human brain specialization related to language and other high-level cognition. However, brain asymmetrical studies of monkeys produced controversial results. Here, we investigated the cerebral asymmetries using a combination of the optimized voxel-based morphometry (VBM) and tract-based spatial statistics (TBSS) protocols in monkeys. The study-specific MRI and DTI-based templates were created in 66 adult Macaca fascicularis, and the asymmetrical index of grey and white matter was subsequently examined. The VBM analysis detected the well-known frontal and occipital petalias and confirmed the presence of leftward asymmetry in the ventral frontal cortex. A marked leftward asymmetry of anterior superior temporal gyrus but not posterior portion were found. We also identified grey matter asymmetries in some regions that were not previously reported including rightward anterior cingulate, insular cortex and thalamus, and leftward caudate. In contrast, the results of TBSS analysis for the first time revealed the robust leftwards asymmetries of corpus callosum (splenium and body), internal/external capsule, and white matter in middle temporal gyrus, adjacent thalamus and amygdala whereas the rightwards in uncinate fasciculus, posterior thalamic radiation and cerebral peduncle. These findings provide robust evidence of grey and white matter asymmetries in the brain of monkeys, which may extend the understanding of brain evolution in cerebral specialization.

Correlation Between N-Demethyl Imatinib Trough Concentration and Serious Adverse Reactions in Patients with Gastrointestinal Stromal Tumors: A Retrospective Cohort Study.

BACKGROUND: Imatinib is the first-line treatment for gastrointestinal stromal tumors; however, the clinical prognosis and adverse reactions of patients vary owing to individualized discrepancies in plasma exposure. METHODS: To determine the safe interval for steady-state plasma trough concentrations (C min ) of imatinib and its active metabolite, N-demethyl imatinib (NDI), 328 plasma samples from 273 patients treated with imatinib were retrospectively analyzed. Imatinib C min and NDI C min were tested, and adverse reactions were recorded. The association between imatinib C min , NDI C min , and serious adverse reactions was evaluated. RESULTS: The C min range of imatinib was 209.5-4950.0 ng/mL, with the mean value and SD of 1491.8 ± 731.4 ng/mL. The C min range of NDI was 80.0-2390.0 ng/mL with the mean value and SD of 610.8 ± 281.5 ng/mL. NDI C min was positively correlated with imatinib C min , whereas the ratio of NDI C min to imatinib C min (NDI C min /imatinib C min ) was negatively correlated with imatinib C min . Univariate logistic regression analysis demonstrated that the treatment objective, daily dose, imatinib C min , NDI C min , and imatinib C min + NDI C min were significantly associated with serious adverse reactions. Multivariate logistic regression analysis showed that NDI C min was an independent risk factor for serious adverse reactions, with a threshold of 665 ng/mL. CONCLUSIONS: NDI C min was an independent risk factor for serious adverse reactions, with a threshold of 665 ng/mL. Monitoring NDI C min was beneficial for the rational application of imatinib and individualized treatment of patients with gastrointestinal stromal tumors.

Plaque characteristics associated with failure of primary balloon angioplasty for intracranial atherosclerotic stenosis: a retrospective study.

BACKGROUND: Primary balloon angioplasty (PBA) is an alternative treatment approach for intracranial atherosclerotic stenosis (ICAS); however, its efficacy may be compromised by arterial dissection or early elastic recoil after balloon dilation. This study aimed to explore the association between plaque characteristics on high-resolution magnetic resonance vessel wall imaging (HR-VWI) and failure of PBA for ICAS. METHODS: We conducted a retrospective analysis of 113 patients with ICAS who underwent HR-VWI before endovascular treatment. Based on the presence of arterial dissection or early elastic recoil post-balloon dilation, patients were classified into the failed PBA (FPBA) group or the successful PBA (SPBA) group. Clinical and baseline HR-VWI characteristics were compared between the two groups. Multivariable analysis was used to investigate plaque features associated with the failure of PBA. RESULTS: The FPBA and SPBA groups comprised 74 and 39 patients, respectively. Plaque eccentricity (83.78% vs 46.15%, P<0.001), negative remodeling (90.54% vs 48.72%, P<0.001), remodeling index (median 0.73 vs 0.90, P=0.001), and intraplaque hemorrhage (31.08% vs 5.13%, P=0.002) differed significantly between the FPBA and SPBA groups. Multivariable analysis indicated that higher frequency of plaque eccentricity (OR 14.03, 95% CI 3.42 to 57.62, P<0.001) and negative remodeling (OR 6.11, 95% CI 1.22 to 30.71, P=0.028) were independently associated with failure of PBA. CONCLUSION: Our findings showed that failure of PBA was associated with plaque eccentricity and negative remodeling. Analysis of plaque characteristics on baseline HR-VWI holds potential value for identifying arterial dissection or early elastic recoil after angioplasty in patients with ICAS.

Risk factors for incident venous thromboembolism in patients with renal tumor and inferior vena cava tumor thrombus: a retrospective case-control study.

BACKGROUND: Venous thromboembolism (VTE) is a principal cause of mortality and adverse oncologic outcomes in patients with renal tumor and inferior vena cava tumor thrombus (RT-IVCTT). However, the preoperative thrombotic risk factors in these patients remain not fully characterized. OBJECTIVES: To identify preoperative thrombotic risk factors in patients with RT-IVCTT. PATIENTS/METHODS: Two hundred fifty-seven consecutive postsurgical patients with RT-IVCTT aged 18-86 years were enrolled between January 2008 and September 2022. Clinicopathological variables were retrospectively reviewed. A multivariate logistic regression model was performed. Preoperative hemoglobin, neutrophils, and serum albumin levels were analyzed as both continuous and categorical variables. RESULTS: VTE was identified in 63 patients (24.5%). On both continuously and categorically coded variables, advanced IVC thrombus (OR 3.2, 95% CI: 1.4-7.0; OR 2.7, 95% CI: 1.2-6.1), renal sinus fat invasion (OR 3.4, 95% CI: 1.6-7.0; OR 3.7, 95% CI: 1.8-7.7), IVC wall invasion (OR 3.6, 95% CI: 1.6-7.9; OR 4.3, 95% CI: 1.9-10.0), IVC blockage status of greater than 75% (OR 5.2, 95% CI: 1.7-15.8; OR 6.1, 95% CI: 1.9-19.7), and higher neutrophils (OR 1.3, 95% CI: 1.0-1.7; OR 2.4, 95% CI: 1.1-5.4) were significantly associated with increased VTE risk in patients with RT-IVCTT. Except hemoglobin, categorically coded serum albumin (OR 0.36, 95% CI: 0.17-0.75) was validated as an independent risk factor for VTE. CONCLUSIONS: This study provided an insight of risk factors contributing to preoperative VTE in patients with RT-IVCTT, which may be beneficial for optimizing strategies to manage VTE in clinical practice.

Loss of SARM1 ameliorates secondary thalamic neurodegeneration after cerebral infarction.

Ischemic stroke causes secondary neurodegeneration in the thalamus ipsilateral to the infarction site and impedes neurological recovery. Axonal degeneration of thalamocortical fibers and autophagy overactivation are involved in thalamic neurodegeneration after ischemic stroke. However, the molecular mechanisms underlying thalamic neurodegeneration remain unclear. Sterile /Armadillo/Toll-Interleukin receptor homology domain protein (SARM1) can induce Wallerian degeneration. Herein, we aimed to investigate the role of SARM1 in thalamic neurodegeneration and autophagy activation after photothrombotic infarction. Neurological deficits measured using modified neurological severity scores and adhesive-removal test were ameliorated in Sarm1-/- mice after photothrombotic infarction. Compared with wild-type mice, Sarm1-/- mice exhibited unaltered infarct volume; however, there were markedly reduced neuronal death and gliosis in the ipsilateral thalamus. In parallel, autophagy activation was attenuated in the thalamus of Sarm1-/- mice after cerebral infarction. Thalamic Sarm1 re-expression in Sarm1-/- mice increased thalamic neurodegeneration and promoted autophagy activation. Auotophagic inhibitor 3-methyladenine partially alleviated thalamic damage induced by SARM1. Moreover, autophagic initiation through rapamycin treatment aggravated post-stroke neuronal death and gliosis in Sarm1-/- mice. Taken together, SARM1 contributes to secondary thalamic neurodegeneration after cerebral infarction, at least partly through autophagy inhibition. SARM1 deficiency is a potential therapeutic strategy for secondary thalamic neurodegeneration and functional deficits after stroke.

Pharmacokinetic Interaction Between Imatinib and Metformin in Rats.

BACKGROUND AND OBJECTIVE: Imatinib is primarily transported into the liver by organic cation transporter 1 (OCT1), organic anion transporting polypeptide 1B3 (OATP1B3), and novel organic cation transporter 2 (OCTN2), which is the first step in the metabolic and elimination of imatinib. Patients taking imatinib may concurrently take metformin, a substrate for OCT1. Drug-drug interactions (DDI) may occur between imatinib and metformin, affecting the clinical efficacy of imatinib. This experiment aimed to investigate the pharmacokinetic effects of metformin on imatinib and its active metabolism of N-desmethyl imatinib in rats. METHODS: Twenty healthy Sprague-Dawley rats were selected and randomly divided into control and experimental groups (10 rats per group). The control group was orally administered imatinib (30 mg/kg) for 14 days, and the experimental group was orally co-administered imatinib (30 mg/kg) and metformin (200 mg/kg) for 14 days. The plasma concentrations of imatinib and N-desmethyl imatinib in rats were determined by ultra-performance liquid chromatography-mass spectrometry. Pharmacokinetic parameters were calculated by DAS2.0 software. RESULTS: After single-dose co-administration of imatinib and metformin on day 1, the AUC0-24 (area under the plasma concentration-time curve) and Cmax (maximum concentration) of imatinib and the MRT (mean residence time) and Cmax of N-desmethyl imatinib in the experimental group were significantly decreased compared with the control group (P < 0.05). After multiple-dose co-administration of imatinib and metformin for 14 days, the AUC0-24 and Cmax of both imatinib and N-desmethyl imatinib were significantly decreased in the experimental group (P < 0.05). CONCLUSION: With both single and multiple co-administration doses, metformin significantly changed the pharmacokinetic parameters of imatinib and N-desmethyl imatinib. The results suggest that care should be taken when metformin and imatinib are co-administered.

Boosting quantification accuracy of chemical exchange saturation transfer MRI with a spatial-spectral redundancy-based denoising method.

Chemical exchange saturation transfer (CEST) is a versatile technique that enables noninvasive detections of endogenous metabolites present in low concentrations in living tissue. However, CEST imaging suffers from an inherently low signal-to-noise ratio (SNR) due to the decreased water signal caused by the transfer of saturated spins. This limitation challenges the accuracy and reliability of quantification in CEST imaging. In this study, a novel spatial-spectral denoising method, called BOOST (suBspace denoising with nOnlocal lOw-rank constraint and Spectral local-smooThness regularization), was proposed to enhance the SNR of CEST images and boost quantification accuracy. More precisely, our method initially decomposes the noisy CEST images into a low-dimensional subspace by leveraging the global spectral low-rank prior. Subsequently, a spatial nonlocal self-similarity prior is applied to the subspace-based images. Simultaneously, the spectral local-smoothness property of Z-spectra is incorporated by imposing a weighted spectral total variation constraint. The efficiency and robustness of BOOST were validated in various scenarios, including numerical simulations and preclinical and clinical conditions, spanning magnetic field strengths from 3.0 to 11.7 T. The results demonstrated that BOOST outperforms state-of-the-art algorithms in terms of noise elimination. As a cost-effective and widely available post-processing method, BOOST can be easily integrated into existing CEST protocols, consequently promoting accuracy and reliability in detecting subtle CEST effects.

Impact of Visceral Fat Area on Intraoperative Complexity and Surgical Approach Decision for Robot-Assisted Partial Nephrectomy: A Comparative Analysis with BMI.

BACKGROUND Optimizing surgical approaches for robot-assisted partial nephrectomy (RAPN) is vital for better patient outcomes. This retrospective study aimed to examine how visceral fat area (VFA) and body mass index (BMI) correlate with intraoperative complexities, thereby guiding the selection of surgical techniques for RAPN. MATERIAL AND METHODS The study analyzed the medical records of 213 Chinese patients diagnosed with a range of benign and malignant renal neoplasms and treated with RAPN in 2020. Visceral fat area was quantified using computed tomography (CT) scans taken at the umbilical level. Various perioperative indicators, such as demographic details, clinicopathological parameters, operation time, estimated blood loss (EBL), warm ischemic time (WIT), and intraoperative complications, were assessed. RESULTS For the retroperitoneal approach, patients with either visceral obesity or general obesity had longer operation times (P<0.001 and P=0.004) and had a tendency for higher EBL (P=0.003 and P=0.001) compared to non-obese patients. In the transperitoneal approach, those with visceral obesity had significantly longer operation times (P=0.008) than their non-viscerally obese counterparts; however, general obesity showed no impact on operation time (P=0.251). Estimated blood loss was higher for patients with visceral obesity (P=0.004), but no significant difference was noted among those with general obesity (P=0.980). CONCLUSIONS VFA appears to offer predictive advantages over BMI in assessing intraoperative complexities for transperitoneal RAPN. When used in conjunction with BMI, it could serve as a valuable tool in selecting the most appropriate surgical approach for RAPN.

Enantioconvergent Palladium-Catalyzed Alkylation of Tertiary Allylic C-H Bonds.

Enantioconvergent catalysis enables the conversion of racemic molecules into a single enantiomer in perfect yield and is considered an ideal approach for asymmetric synthesis. Despite remarkable advances in this field, enantioconvergent transformations of inert tertiary C-H bonds remain largely unexplored due to the high bond dissociation energy and the surrounding steric repulsion that pose unparalleled constraints on bond cleavage and formation. Here, we report an enantioconvergent Pd-catalyzed alkylation of racemic tertiary allylic C-H bonds of α-alkenes, providing a unique approach to access a broad range of enantioenriched γ,δ-unsaturated carbonyl compounds featuring quaternary carbon stereocenters. Mechanistic studies reveal that a stereoablative event occurs through the rate-limiting cleavage of tertiary allylic C-H bonds to generate σ-allyl-Pd species, and the achieved E/Z-selectivity of σ-allyl-Pd species effectively regulates the diastereoselectivity via a nucleophile coordination-enabled SN 2'-allylation pathway.

Learned spatiotemporal correlation priors for CEST image denoising using incorporated global-spectral convolution neural network.

PURPOSE: To develop a deep learning-based method, dubbed Denoising CEST Network (DECENT), to fully exploit the spatiotemporal correlation prior to CEST image denoising. METHODS: DECENT is composed of two parallel pathways with different convolution kernel sizes aiming to extract the global and spectral features embedded in CEST images. Each pathway consists of a modified U-Net with residual Encoder-Decoder network and 3D convolution. Fusion pathway with 1 × 1 × 1 convolution kernel is utilized to concatenate two parallel pathways, and the output of DECENT is noise-reduced CEST images. The performance of DECENT was validated in numerical simulations, egg white phantom experiments, and ischemic mouse brain and human skeletal muscle experiments in comparison with existing state-of-the-art denoising methods. RESULTS: Rician noise was added to CEST images to mimic a low SNR situation for numerical simulation, egg white phantom experiment, and mouse brain experiments, while human skeletal muscle experiments were of inherently low SNR. From the denoising results evaluated by peak SNR (PSNR) and structural similarity index (SSIM), the proposed deep learning-based denoising method (DECENT) can achieve better performance compared to existing CEST denoising methods such as NLmCED, MLSVD, and BM4D, avoiding complicated parameter tuning or time-consuming iterative processes. CONCLUSIONS: DECENT can well exploit the prior spatiotemporal correlation knowledge of CEST images and restore the noise-free images from their noisy observations, outperforming state-of-the-art denoising methods.

Data-driven design of new chiral carboxylic acid for construction of indoles with C-central and C-N axial chirality via cobalt catalysis.

Challenging enantio- and diastereoselective cobalt-catalyzed C-H alkylation has been realized by an innovative data-driven knowledge transfer strategy. Harnessing the statistics of a related transformation as the knowledge source, the designed machine learning (ML) model took advantage of delta learning and enabled accurate and extrapolative enantioselectivity predictions. Powered by the knowledge transfer model, the virtual screening of a broad scope of 360 chiral carboxylic acids led to the discovery of a new catalyst featuring an intriguing furyl moiety. Further experiments verified that the predicted chiral carboxylic acid can achieve excellent stereochemical control for the target C-H alkylation, which supported the expedient synthesis for a large library of substituted indoles with C-central and C-N axial chirality. The reported machine learning approach provides a powerful data engine to accelerate the discovery of molecular catalysis by harnessing the hidden value of the available structure-performance statistics.

Close-Shell Reductive Elimination versus Open-Shell Radical Coupling for Site-Selective Ruthenium-Catalyzed C-H Activations by Computation and Experiments.

Ruthenium-catalyzed σ-bond activation-assisted meta-C-H functionalization has emerged as a useful tool to forge distal C-C bonds. However, given the limited number of mechanistic studies, a clear understanding of the origin of the site-selectivity and the complete reaction pattern is not available. Here, we present systematic computational studies on ruthenium-catalyzed C-H functionalization with primary, secondary, tertiary alkyl bromides and aryl bromides. The C-H scission and the C-C formation were carefully examined. Monocyclometalated ruthenium(II) complexes were identified as the active species, which then underwent inner-sphere single electron transfer (ISET) to activate the organic bromides. The site-selectivity results from the competition between the close-shell reductive elimination and the open-shell radical coupling. Based on this mechanistic understanding, a multilinear regression model was built to predict the site-selectivity, which was further validated by experiments.

Norvancomycin plasma concentration monitoring in hemodialysis patients with end stage kidney disease: A retrospective cohort study.

Blood concentration monitoring plays an important role in the rational use of norvancomycin. However, the reference interval for the norvancomycin plasma concentration in the treatment of infections in hemodialysis patients with end stage kidney disease is undefined. To determine the safe and effective interval for the norvancomycin plasma trough concentration, 39 patients treated with hemodialysis and norvancomycin were analyzed retrospectively. The norvancomycin plasma concentration before hemodialysis was tested as the trough concentration. The associations of the norvancomycin trough concentration with efficacy and adverse reactions were evaluated. No norvancomycin concentration above 20 µg/mL was detected. The trough concentration, but not the dose, had a significant effect on the anti-infectious efficacy. Compared with the low norvancomycin trough concentration group (<9.30 µg/mL), the high concentration group (9.30-20.0 µg/mL) had improved efficacy (OR = 15.45, p < 0.01) with similar side effects (OR = 0.5417, p = 0.4069). It is beneficial to maintain the norvancomycin trough concentration at 9.30-20.0 µg/mL to achieve a good anti-infectious effect in hemodialysis patients with end stage kidney disease. Plasma concentration monitoring provides a data basis for the individual treatment of infections with norvancomycin in hemodialysis patients.