AE Data Research Articles

Real-life AE data from EudraVigilance

Real-life AE data from EudraVigilance

Efficacy and Safety of Two Comparable Single Low Doses of Rasburicase Followed By Allopurinol in Adult Patients with Acute Leukemia

BACKGROUND: Hyperuricemia is a major cause of tumor lysis syndrome (TLS) related acute kidney injury. Certain hematologic malignancies (acute leukemia, high-grade lymphoma) pose a high-risk for spontaneous and chemotherapy-induced TLS. Allopurinol, a xanthine oxidase inhibitor, can inhibit formation of new uric acid (UA), but it does not eliminate the already formed UA. Alternatively, urate oxidases like rasburicase (ELITEK®, Sanofi Genzyme) can markedly and rapidly decrease UA levels through oxidation of UA to allantoin and hydrogen peroxide. In a phase III trial, rasburicase therapy more rapidly controlled UA than allopurinol in adults with hyperuricemia or at high-risk for TLS. However, rasburicase is expensive, especially when used as per the manufacturer's recommended dosage of 0.2mg/kg/day for up to 5 days. Numerous reports have shown that lower, and even single, doses are effective in lowering UA levels.OBJECTIVES: To determine the efficacy and safety of two single low doses of rasburicase (1.5mg vs. 3mg) in adult patients with acute leukemia and elevated plasma uric acid ≥ 7.5mg/dL.METHODS: Patients ≥ 18 years treated inpatient for acute leukemia with UA ≥ 7.5 mg/dL and at risk for TLS were randomized to one of two treatment arms (ClinicalTrials.gov Identifier: NCT01564277). Patients received either rasburicase 1.5mg (Arm A) or rasburicase 3mg (Arm B) intravenously over 30 minutes on day 1 in an open-label and unblinded fashion. All patients received allopurinol 300mg daily on days 1-6 (dose reduced for reduced calculated creatinine clearance). Plasma samples for UA evaluation were collected at baseline, and at approximately 4, 24, 48, 72, 96, 120, 144 hours after the Day 1 dose of rasburicase. If UA > 7.5 mg/dL at 24 or 48 hours, then additional dose of rasburicase could be administered (1.5mg for Arm A, 3mg for Arm B). Primary endpoint was the response rate of obtaining UA ≤ 7.5mg/dL within 24 hrs of rasburicase treatment. Secondary endpoints included rate of patients that maintained UA ≤ 7.5 mg/dl on days 2-6, rate of patients who required additional rasburicase doses, rate of patients experiencing significant worsening of renal function, as well as safety of low single-dose rasburicase. Patients were followed for adverse events (AE; as defined in CTCAE version 4) for up to 30 days after last dose of rasburicase or resolution of drug-related AE.RESULTS: 24 patients were enrolled on this phase 2 study (12 on each arm; Table 1). 83% of patients in both arms achieved UA response by 24 hours (Table 2). Two pts in Arm A (baseline UA: 14.2 and 17.6 mg/dL) and three pts in Arm B (baseline UA: 15.3, 10.2, 11.9 mg/dL) were given one additional rasburicase dose. Only one pt (from Arm A) had UA > 7.5 mg/dL between days 2-6. None of the patients had doubling of their baseline serum creatinine or required hemodialysis support. Average decrease in UA was lower in Arm A as compared to Arm B (5.5 vs. 6.8 mg/dL). AE data from 21 pts showed that both low doses were overall well tolerated and most toxicities were unrelated to rasburicase. No patient deaths were attributed to rasburicase. An ad-hoc analysis showed significant rasburicase specific cost benefits using either of the low doses as compared to FDA approved dosage and other studied regimens (Table 3).CONCLUSIONS: Single low doses of rasburicase (1.5mg and 3mg) plus allopurinol are well tolerated and appear to be equally efficacious in decreasing UA levels in adult patients with leukemia at high risk for TLS. If baseline UA is elevated (>12 mg/dL), a 3mg or higher dose of rasburicase might be preferable. Preliminary cost analysis profiling favors the use of the low dose rasburicase. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

A risk stratification model for toxicities in phase 1 immuno-oncology (P1-IO) trials.

2648 Background: Despite an exponential increase in the number of potential targets in the immuno-oncology (IO) field, lack of risk models to predict toxicities remains a challenge in early drug development. We proposed a risk stratification strategy and investigated whether different IO classes may be associated with incremental risk of toxicities. Methods: A systematic search for IO studies from 01/2014 to 10/2020 was conducted. Among the 12053 abstracts screened, 254 reporting phase I-IO trials were selected. Type of IO treatment (IO monotherapy [mono] vs IO combination [comb]), therapeutic class (e.g. IO, molecularly targeted agents [MTA]), and dose escalation method (rule-based, model-based and model-assisted) were collected. A risk scoring model was developed after expert consensus: treatment-related deaths (1:yes, 0:no), incidence of G3/G4 treatment related adverse events (TRAE) or treatment emergent adverse events (TEAE) (0 if 1-29%,1 if ≥30-49%, 2 if ≥50%), incidence of ≥G2 cytokine release syndrome (1:yes, 0:no), incidence of ≥G2 encephalopathy (1:yes 0:no) and incidence of dose-limiting toxicity (DLT) (0:no, 1:lab, 2:clinical). Risk categories were defined by summing all points (0 = low, 1-2 = intermediate, 3+ = high) and were correlated with type of IO treatment, therapeutic class and dose escalation method. Results: Of 254 P1-IO trials reviewed, 228 (90%) were scorable, 26 were not (25 due to lack of AE data). Up to 10/26 (38%) of non-scorable studies were cell therapies. Among the 228 scorable studies, 120 (53%) scored 0, 65 (28%) scored 1-2, 43 (19%) scored 3+; 24 (11%) and 125 (55%) did not provide no. of pts with G3/G4 TRAEs or TEAEs respectively. A significant association was observed between risk categories and therapeutic class (p<0.001) (see table). Additionally, IO-MTA and IO-IO were both associated with an increased risk of toxicity as compared to IO-mono (OR=3.91 (95%CI 1.7-9.2), p=0.002) and (OR=2.79 (95%CI 1.2-6.5), p=0.02) respectively. There was no association between dose escalation method and risk of toxicity (p=0.95), but 182 (92%) used rule-based methods. Conclusions: Our results suggest that different IO classes are associated with different risks of toxicity. This risk classification strategy may guide future clinical trial design. Additionally, standards for reporting toxicities in P1-IO trials are urgently needed.[Table: see text]

Analysis of adverse events attribution and reporting in cancer clinical trials: A systematic review.

We systematically reviewed the quality of AEs reports in published oncology trials analyzing also the bias in the attribution process. We searched MEDLINE, PubMed (2000-2019) selecting randomized, double-blind, placebo-controlled, and phase 3 cancer trials using exclusively targeted therapy or immunotherapy-related drugs. The proportion of publications with complete AE reports (including both all-cause and drug-related AE data) and the AEs attribution ratio (patients with drug-related over all-cause AE) were investigated. Among 60 trials (38,174 patients) included, 40 (66.6 %) presented an incomplete report of AEs attribution. Journals with the lowest impact factor were significantly associated with deficient reports of grade 3-4 AEs (p = 0.02). Under placebo administration, the median incidence of all-grade drug-related AEs was 49 % (IQR 39-56). The median attribution ratio for all-grade AEs in the active and placebo arms was 88.9 % (IQR 79.8-93) and 53.9 % (IQR 43.4-60.9), respectively. The AEs reporting and attribution process appear to be more unreliable than expected.

Analyzing acoustic emission data to identify cracking modes in cement paste using an artificial neural network

The focus of this research is the identification of cracking mechanisms for cement paste using acoustic emission data, recorded from compression and notched four-point bending tests. A procedure is developed for analyzing the data by employing an agglomerative hierarchical clustering method, an artificial neural network, and a ray-tracing source location algorithm. An agglomerative hierarchical clustering method is utilized to cluster the AE data from a compression test using frequency-dependent features. A neural network is trained using the compression test data and applied to the AE data emitted during the four-point bending test. The clustered data from the four-point bending test is localized using a ray-tracing algorithm. Based on the occurrence and locations of the clustered events and signal feature analyses, potential cracking mechanisms are identified and assigned.

Efficacy and safety of acupuncture for trigeminal neuralgia: A protocol for systematic review and meta-analysis.

Background:Trigeminal neuralgia (TN) is a disease accompanied by severe facial pain, which seriously affects the daily life of patients. Acupuncture is widely used by Traditional Chinese Medicine doctors to treat various painful diseases. Acupuncture combined with the treatment of trigeminal neuralgia can increase the analgesic effect and reduce side effects. However, there is still a lack of more quality multi-center clinical controlled trials and comprehensive meta-analysis, and a lack of more comprehensive and stronger evidence-based medical evidence.Methods:The 2 reviewers used the same search strategy to search CNKI, PubMed, Web of Science, Cochrane Library, Scopus, EBSCO, and the search date is until July 19, 2020. Two people read the retrieved literatures independently, and then delete duplications. Then, use the “risk of bias” tool in Cochrane Handbook 5.2 to score. Only documents with a score greater than 5 can be included. Make a table of literature characteristics, extract baseline patient data, research methods and possible risks of bias in the literature, interventions in treatment and control groups, outcome evaluation indicators (BNI, VAS, ER and AE), and research funding support. Use Review Manager 5.3.5 for meta-analysis, use Stata 15 for regression analysis to find the source of heterogeneity, and then perform subgroup analysis to resolve the heterogeneity based on the corresponding source.Results:The analysis of BNI, VAS, ER and AE data can provide high-quality evidence for high-quality synthesis and/or descriptive analysis of the effectiveness and safety of acupuncture treatment of various causes of urinary retention.Conclusion:This study can provide more comprehensive and strong evidence to prove whether acupuncture is effective and safe in the treatment of TN patients.Registration:The research has been registered and approved on the PROSPERO website. The registration number is CRD42019119606.

Experimental study on damage evolution characteristics of segment structure of shield tunnel with cracks based on acoustic emission information

Cracks are constantly observed in segments due to adverse geological conditions and loads during shield construction. However, crack propagation can have a negative impact on the stress deformation of the segment structures in the long run. Revealing the characteristics of energy release during crack propagation can effectively reflect the damage evolution process. Based on an investigation of segment cracks in a subway tunnel project, this paper conducts an in-depth analysis of AE data of segments through similar model tests, and explores the influence of cracks of different lengths, quantities and positions on the damage evolution of segments of shield tunnels. The results show that cracks reduce the overall stiffness of the structure when compared with that of a segment ring with no prepared cracks, and the elastic bearing range increases slightly, while the plastic bearing range decreases obviously. With the increase of the length and number of prepared cracks, the number of ladders of AE events decreases and the height of ladders increases, and the number of AE events of segments increases continuously at the critical point of instability. The damage of segments appears earlier, and the development process of the damage and is relatively gentle if cracks are located at the arch waist. By contrast, the damage of segments is more serious if cracks are located at the arch roof and arch bottom. The results provide theoretical basis for design optimization, disease analysis and evaluation of shield tunnel.

The Possibility of Applying Acoustic Emission and Dynamometric Methods for Monitoring the Turning Process.

Ensuring optimal turning conditions has a huge impact on the quality and properties of the machined surface. The condition of the cutting tool is one of the factors to achieve this goal. In order to control its wear during the turning process, monitoring was used. In this study, the acoustic emission method and measure of cutting forces during turning were used for monitoring that process. The research was carried out on a universal lathe center (CU500MRD type) using a Kistler dynamometer with assembled removable insert CCET09T302R-MF by DIJET Industrial CO., LTD. A dynamometer allows to measure forces Fx (radial force), Fy (feed force) and Fz (cutting force). The turning process was performed on a shaft with 60 mm diameter made of 304L stainless steel. The AE research was carried at Physical Acoustics Corporation with the kit that includes: recorder USB AE Node, preamplifier, AE-sensor VS 150M and computer with dedicated software used for recording and analyzing AE data. The aim of this paper is to compare selected diagnostic methods: acoustic emission and cutting forces measurement for monitoring wear of cutting tool edge. Analysis of the research results showed that both selected methods of monitoring the turning process allowed the determination of the beginning of the tool damage process.

Application of Acoustic Emission Technique (AET) to the Study of Adhesive Wear of two Aluminium Alloys 2024 and 2024-T4

The adhesive wear resistance of (2024&2024-T4) aluminium alloy under dry and lubricated conditions has been investigated by using the weighing method and the Acoustic Emission Technique (AET). Pin–on-plate reciprocating wear apparatus was used. The AET has capability of predicting an impending failure much ahead of time of its occurrence. The AE measurements are made with the help of a tape recorder system into isolated chamber from external noises. The results show that 2024-T4 alloy has higher wear resistance with three distinct stages of wear rate in comparison with 2024 alloy under the working conditions. The AE data analysis showed a clear evident that the Events Rate and Peak Amplitude value display a clear-cut distinction between the wear rate stages in dry and lubricated conditions of both alloys giving a good agreement with the weighing method results.

A probabilistic model of acoustic emissions generated during compression test of cementitious materials for crack mode classification

This article presents a study on crack mode classification in cementitious materials under uniaxial compression usinggaussian mixture modeling (GMM) of acoustic emissions approach. To implement a retrofitting method to an in-serviceconcrete structure, a prior knowledge about the type of crack developed in the concrete structure is useful. Because,occurrence of AE events during fracture process in solids is random, a probabilsitc method has been required to classify theAE sources related to different types of cracks. In this study, a monotonically increasing unconfined uniaxial compressiveload has been applied on different cylindrical specimens of plain cement concrete cast with maximum coarse aggregate sizeof 20 mm, 12.5 mm and cement mortar to study crack classification. It has been observed that the slope of the line separatingthe AE data clusters belonging to tensile and shear cracks is more steep for the concrete specimen containing 20 mm maximumcoarse aggregate when compared to the concrete specimen containing 12.5 mm maximum coarse aggregate and cementmortar. This indicated that as the coarse aggregate size in concrete increased, the generated AE events related to shearcracking decreased. Also, the AE based b-value has reached minimum at the peak load. At the time of failure, AE related toshear cracking has increased sharply.

Predicting Protein Complex Structure from Surface-Induced Dissociation Mass Spectrometry Data.

Recently, mass spectrometry (MS) has become a viable method for elucidation of protein structure. Surface-induced dissociation (SID), colliding multiply charged protein complexes or other ions with a surface, has been paired with native MS to provide useful structural information such as connectivity and topology for many different protein complexes. We recently showed that SID gives information not only on connectivity and topology but also on relative interface strengths. However, SID has not yet been coupled with computational structure prediction methods that could use the sparse information from SID to improve the prediction of quaternary structures, i.e., how protein subunits interact with each other to form complexes. Protein–protein docking, a computational method to predict the quaternary structure of protein complexes, can be used in combination with subunit structures from X-ray crystallography and NMR in situations where it is difficult to obtain an experimental structure of an entire complex. While de novo structure prediction can be successful, many studies have shown that inclusion of experimental data can greatly increase prediction accuracy. In this study, we show that the appearance energy (AE, defined as 10% fragmentation) extracted from SID can be used in combination with Rosetta to successfully evaluate protein–protein docking poses. We developed an improved model to predict measured SID AEs and incorporated this model into a scoring function that combines the RosettaDock scoring function with a novel SID scoring term, which quantifies agreement between experiments and structures generated from RosettaDock. As a proof of principle, we tested the effectiveness of these restraints on 57 systems using ideal SID AE data (AE determined from crystal structures using the predictive model). When theoretical AEs were used, the RMSD of the selected structure improved or stayed the same in 95% of cases. When experimental SID data were incorporated on a different set of systems, the method predicted near-native structures (less than 2 Å root-mean-square deviation, RMSD, from native) for 6/9 tested cases, while unrestrained RosettaDock (without SID data) only predicted 3/9 such cases. Score versus RMSD funnel profiles were also improved when SID data were included. Additionally, we developed a confidence measure to evaluate predicted model quality in the absence of a crystal structure.

Experimental investigation of progressive cracking processes in granite under uniaxial loading using digital imaging and AE techniques

For a full understanding of the cracking processes in granite, uniaxial compression tests are conducted on prismatic specimens with pre-existing flaws, and digital imaging and AE techniques are applied to monitor real-time rupture behaviors. The digital image correlation (DIC) method is used to detect the process zone nucleation characteristics in granite. A novel approach for representing AE data in terms of the inter-event time (IET) function F(τ) is employed to analyze fracture-related AE event rate characteristics. Based on the coupled analyses of the acousto-optic-mechanical characteristics, the complete cracking processes of granite are classified into six levels, which are distinguishable by five characteristic stresses. Process zone nucleation, which represents the clustering of micro-cracks, is incorporated into the classification for the first time. Process zone nucleation is visualized as a white patch and is either linear or diffuse. By DIC analysis, the maximum principal strain field reliably predicts a linear white patch, and the maximum shear strain field implies a diffuse white patch. The evolutionary rules of the IET function F(τ) strongly support the new classification of cracking levels in granite. For the identification of stress thresholds and cracking levels, a combined acousto-optic-mechanical methodology is established, in which the role of the IET function F(τ) is highlighted.

Adverse events of miniscalpel-needle treatment in Korea: A systematic review

IntroductionThe miniscalpel-needle (MSN) acupuncture combines acupuncture and microinvasive surgery and is used extensively in China and Korea for the management of several painful conditions. Given the potential for this technique to cause damage to nerves and blood vessels, the aim of this systematic review was to investigate adverse events’ (AEs) characteristics associated with MSN treatment in Korea, and summarize the reporting of safety procedural guidelines. MethodsNine electronic databases were searched. Clinical studies reporting MSN treatment associated AEs in Korea were selected by two independent authors. Severity and causality of each AEs was assessed. Safety precautions and infection prevention measures of each study were summarized. ResultsOf the 45 relevant studies included in this review, 15 reported adverse events. The quality of AE data was generally poor. Most AEs associated with MSN treatment reported mild symptoms (local pain having certain causality and grade 1 severity with highly heterogeneous incidence), while few reported moderate-to- severe and systemic AEs (headache, dizziness, or tiredness, having probable/likely causality and grade 2 or 3 severity). The checklist drafts of safety precautions and infection preventions consisting of 10 and 11 sub-items, respectively, were established. ConclusionsDue to the high heterogeneity and poor quality of AE data, the definite characteristics of the AEs were undetermined. The heterogeneity may have occurred from differences in the strictness of AE report and safety procedural guidelines. To improve this, we summarized the drafts of safety procedural guidelines. Our findings could be used in further studies to establish MSN treatment safety.

Abstract WP412: Use of Interactive Cluster Heatmaps and Text Analytics in the Escape-na1 Phase 3 Clinical Trial for Pharmacovigilance of Adverse Events and Site Performance

Introduction: Stroke trial subjects sustain numerous adverse events (AE’s) which may be related to the disease under study or to the therapeutic intervention. In studies involving pharmacovigilance of multiple AE’s, ongoing oversight of AEs by investigators and trial sponsors is critical to ensure the safety and well being of trial subjects. Static cluster heatmaps are used extensively in the field of gene expression studies and text analytics are used widely to monitor text on social media sites such as Twitter. Here we present novel dynamic tools using static cluster heatmaps and text analytics to aid with the visualization of AEs and of clinical site performance in AE reporting in the ESCAPE-NA-1 trial (Clinicaltrials.gov NCT 02930018). Methodology: In an interactive cluster heatmap display, the frequency of AEs is color coded in cells, with the rows corresponding to either sites or patients and columns correspond to unique AEs. Clustering is visualized on a heatmap by addition of row and column dendrograms. Quantification of AEs in the clinical trial is performed through text analytics and the results are visualized using a word cloud. Difference of AE across sites is visualized using a comparison cloud, a cloud that compares frequencies across sites. A cluster heatmap and word cloud are made interactive by formatting into HTML. Results: The main results obtained from interactive AE cluster heatmaps are patient ,site and AE clusters (Figure 1). The results obtained from text analytics are word clouds that convey overall AEs frequency and AEs frequency across sites (Figure 1). Due to active status of the trial, we will share the methodology of constructing interactive AE cluster heatmaps and word clouds and broad visual results without providing specifics of sites or AEs. Conclusion: Interactive cluster heatmaps and word clouds constructed via text analytics are a novel way of visualizing complex multidimensional AE data from clinical trials.

Fracture Paths and Acoustic Emission Characteristics of Layered Brazilian Disc Specimens with Different Monolayer Thickness

The Brazil disk test is carried out for thin layered rock with different thickness by numerical simulation method, with the load and AE data of samples analyzed.The following are some findings: (1) When the thickness of a single layer of layered rock increases, its tensile strength does not simply increase. Instead, they roughly show a U-shaped relationship. (2) Layered rock’s load-displacement curve is multimodal. (3) Shear rupture occurs at the upper and lower ends of the disk, tensil and mixed rupture occurs more frequently in the middle of the disk. (4) There are three stages of of interacting cracks’ coalescence: initial crack and the secondary fracture generate, then they interact and extend, lastly coalesce.

Peculiar Properties of Phase Transitions in Na0.5Bi0.5TiO3-xBaTiO3 (0<x<6) Lead-free Relaxor Ferroelectrics Seen Via Acoustic Emission

Na0.5Bi0.5TiO3-xBaTiO3 (0<x<6) relaxor ferroelectrics crystals were investigated by means of dielectric and acoustic emission methods. Dielectric curves exhibit the slightly visible small maxima near the depolarization temperatures, Td, and the wide maxima at the temperatures of Tm, whereas the acoustic emission exhibits the sharp bursts, corresponding to Td, Tlm, which is known to be a temperature exhibiting a strong frequency dispersion, TRE, which is known to be a temperature above which a frequency dispersion vanishes, and the Tm and the Tp manifesting a transition to the paraelectric phase. Based on the AE data it was established that all these characteristic temperatures shift down as x increases, but with different slopes. A mechanism of such the differences is discussed.

Acoustic Emission Technique Applied in Textiles Mechanical Characterization

The common textile architecture/geometry are woven, braided, knitted, stitch boded, and Z-pinned. Fibres in textile form exhibit good out-of-plane properties and good fatigue and impact resistance, additionally, they have better dimensional stability and conformability. Besides the nature of the textile, the architecture has a great role in the mechanical behaviour and mechanisms of damage in textiles, therefore damage mechanisms and mechanical performance in structural applications textiles have been a major concern. Mechanical damage occurs to a large extent during the service lifetime consequently it is vital to understand the material mechanical behaviour by identifying its mechanisms of failure such as onset of damage, crack generation and propagation. In this work, textiles of different architecture were used to manufacture epoxy based composites in order to study failure events under tensile load by using acoustic emission technique which is a powerful characterization tool due to its link between AE data and fracture mechanics, which makes this relation a very useful from the engineering point of view.

Improving of Acoustic Emission Signal Detection for Fatigue Fracture Monitoring

Identifying growing cracks in running machinery and industrial facilities is challenging, particularly at the nucleation stage in “hard-to-reach” places and in harsh environment. The method of acoustic emission is a popular non-destructive means for inspecting and monitoring the behavior of loaded materials and active internal defects. One of the key problems which impedes a wider application of the AE technique is associated with detectability of low amplitude signals hidden on a background of laboratory or industrial noise. A recently proposed continuous threshold-less mode of AE data acquisition offers an advantage in analyzing AE random time series on different time scales, thus providing information otherwise inaccessible by a conventional threshold-based acquisition mode. The evaluation criteria concerning the activity of internal defects depend strongly on the AE detectability in the selected time interval. In the present work we compare performance of two signal detection algorithms: conventional amplitude threshold discrimination and innovative «phase picker» based on a wavelet transform. In observing the characteristic accumulation of AE signals over long periods of hundreds time and opposite in a single loading cycle can provide a difference at signal estimation.

Advanced signal analysis of acoustic emission data to discrimination of different corrosion forms

Aim of the present work is to give an analytical approach suitable to distinguish three different corrosion forms through the use of acoustic emission technique. Corrosion attacks have been obtained on three different types of martensitic stainless steel in a FeCl3 solution, using conditions set by the ASTM G48 standard. These martensitic stainless steel used were characterised by different mechanical, microstructural and electrochemical properties, which lead to the development of specific corrosion forms, albeit the steels were tested in the same environmental conditions. A multivariate statistical analysis approach, based on principal component analysis (PCA) and self-organising map (SOM), has been adopted to evaluate AE data and to obtain highlight damage-sensitive features. Specific clusters of variables related to specific corrosion phenomena have been identified, promoting this analysis approach as a potential procedure for discriminating onset of a specific corrosion mechanism.

Acoustic Emission Monitoring and Failure Precursors of Sandstone Samples under Various Loading and Unloading Paths

To explore the failure precursors of hard rock, a series of triaxial loading and unloading experiments were carried out on sandstone sample using the acoustic emission systems. The extreme-point symmetric mode decomposition method (ESMD method) was used to denoise and reconstruct the AE data. The AE quiet period in Scheme I becomes much more obvious with the confining pressure increasing, which can be regarded as the precursor information of the sample failure under conventional triaxial compression. Unlike Scheme I, there are no obvious precursory characteristics before failure in Schemes II and III, and the count rate reaches the maximum at the peak point. When the stress ratio ranges from 0.8 to 1.0, the fractal values of acoustic emission can be used to investigate the failure precursors of samples at a lower confining pressure. When the time ratio is greater than 0.8 under higher confining pressures, the fractal values of sandstone samples under unloading paths are rapidly reduced, which can be used to predict rock failure at higher confining pressures.