Vancomycin Dependent Pancytopenia- a rare side effect: A Case Report

Kemeç, Zeki; Kahya, Yusuf; Atay, Arif; Demır, Mustafa; Gürel, Ali

doi:10.5455/ijmrcr.vancomycin-dependent-pancytopenia

Cited by 4 publications

(4 citation statements)

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“…From Table 9 we see that the side effects diarrhea, dyspepsia, and musculoskeletal discomfort associated with the drug amlodipine which have been reported in [57], [58,59], and [60], respectively, were detected in our experiment. Similarly, the side effects paraesthesia [67] and leukopenia [61,68] associated with the drug vancomycin were also detected in our experiment. Moreover, Table 10 shows that the side effects somnolence [62][p. 1211], anorexia [64], and convulsion [65] associated with the drug cisplatin were found in our experiment.…”

Section: Discussionsupporting

confidence: 85%

“…Tables 6 –7 exemplified the results. Table 6 shows that the side effects, viz, paraesthesia and leukopenia associated with vancomycin, an antibiotic, have high probability which has been reported in [48], and [49, 55], respectively. Besides, the side effect angioedema associated with the drug glimperide is rarely seen, which has been reported in [50] was detected in our experiments.…”

Section: Discussionmentioning

confidence: 99%

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Predicting Adverse Drug Effects: A Heterogeneous Graph Convolution Network with a Multi-layer Perceptron Approach

Chen

Shih

Chien

et al. 2022

Preprint

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We exploit a heterogeneous graph convolution network (GCN) combined with a multi-layer perceptron (MLP), which is denoted by GCNMLP, to explore potential side effects of drugs. By inferring the relationship among similar drugs, our approach in silico methods shortens the time consumption in uncovering the side effects unobserved in routine drug prescriptions. In addition, it highlights the relevance in exploring the mechanism of well-documented drugs. Our results predict drug side effects with area under precision-recall (AUPR) curve AUPR = 0.941, substantially outperforming the non-negative matrix factorization (NMF) method with AUPR=0.600. Moreover, new side effects are obtained using the GCNMLP.

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Section: Discussionsupporting

confidence: 85%

Section: Discussionmentioning

confidence: 99%

Predicting Adverse Drug Effects: A Heterogeneous Graph Convolution Network with a Multi-layer Perceptron Approach

Chen

Shih

Chien

et al. 2022

Preprint

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“…Table 9 shows that the side effects of diarrhea, dyspepsia, and musculoskeletal discomfort associated with the drug Amlodipine, which have been reported in [ 55 – 58 ], respectively, were detected in our experiment. Similarly, the side effects paraesthesia [ 59 ] and leukopenia [ 60 , 61 ] associated with the drug Vancomycin were also detected in our experiment. Moreover, Table 10 shows that the side effects of somnolence [ 62 ] [p. 1211], anorexia [ 63 ], and convulsion [ 64 ] associated with Cisplatin were found in our experiment.…”

Section: Discussionsupporting

confidence: 83%

Predicting adverse drug effects: A heterogeneous graph convolution network with a multi-layer perceptron approach

Chen

Shih²,

Chien³

et al. 2022

PLoS ONE

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We apply a heterogeneous graph convolution network (GCN) combined with a multi-layer perceptron (MLP) denoted by GCNMLP to explore the potential side effects of drugs. Here the SIDER, OFFSIDERS, and FAERS are used as the datasets. We integrate the drug information with similar characteristics from the datasets of known drugs and side effect networks. The heterogeneous graph networks explore the potential side effects of drugs by inferring the relationship between similar drugs and related side effects. This novel in silico method will shorten the time spent in uncovering the unseen side effects within routine drug prescriptions while highlighting the relevance of exploring drug mechanisms from well-documented drugs. In our experiments, we inquire about the drugs Vancomycin, Amlodipine, Cisplatin, and Glimepiride from a trained model, where the parameters are acquired from the dataset SIDER after training. Our results show that the performance of the GCNMLP on these three datasets is superior to the non-negative matrix factorization method (NMF) and some well-known machine learning methods with respect to various evaluation scales. Moreover, new side effects of drugs can be obtained using the GCNMLP.

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“…Vancomycin is prohibited from being used in livestock and poultry farming in China [11] and is also infrequently used for treating humans owing to the many potential sideeffects [12][13][14]. Therefore, vancomycin is rarely detected in the aquatic environment.…”

Section: Introductionmentioning

confidence: 99%

Fate and Proliferation of Vancomycin Resistance Genes in Two Typical Pharmaceutical Wastewater Treatment Plants

Guo,

Zhang,

et al. 2023

Water

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The emergence of vancomycin-resistant Enterococcus (VRE) and vancomycin resistance genes (VRGs) complicates the application of vancomycin, which is a last-line agent for human infectious diseases, and pharmaceutical wastewater treatment plants (PWWTPs) are widely thought to be important sources of corresponding antibiotic resistance genes (ARGs). In this study, two VRGs (vanA and vanB) were evaluated in two PWWTPs using quantitative polymerase chain reaction (qPCR) analysis to characterize the occurrence and fate of VRGs. The VRG concentration tended to decrease throughout all processing stages, while anaerobic treatment promoted the propagation of antibiotic-resistant bacteria and led to an increase in VRG abundance. Finally, the absolute concentrations of vanA and vanB exceeded 104 copies/mL in the effluents, and a significant amount of VRGs was transferred to sludge at 1.68 × 1017 copies/d. Redundancy analysis demonstrated that the relative abundance of ARGs was significantly correlated with the concentrations of vancomycin and COD. Furthermore, the relative abundance of vanA was increased in wastewater with multiple antibiotics, while the relative abundance of vanB only increased in the presence of vancomycin. This observation implied different intrinsic resistance mechanisms for different VRG subtypes. Overall, in this report, we describe the first comprehensive study on the fate and behavior of VRGs with different physicochemical or biochemical treatments and different antibiotic selection pressures in PWWTPs; this report provides important references for the environmental spread of VRGs.

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Vancomycin Dependent Pancytopenia- a rare side effect: A Case Report

Cited by 4 publications

References 0 publications

Predicting Adverse Drug Effects: A Heterogeneous Graph Convolution Network with a Multi-layer Perceptron Approach

Predicting Adverse Drug Effects: A Heterogeneous Graph Convolution Network with a Multi-layer Perceptron Approach

Predicting adverse drug effects: A heterogeneous graph convolution network with a multi-layer perceptron approach

Fate and Proliferation of Vancomycin Resistance Genes in Two Typical Pharmaceutical Wastewater Treatment Plants

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