A systematic review and meta‐analysis of randomized controlled trials: Skin‐patch of Chinese herbal medicine for patients with acute gouty arthritis

Aims

To evaluate the evidence of the effectiveness and safety of Chinese herbal medicine skin‐patches for patients with acute gouty arthritis.

Background

Acute gouty arthritis is a problem that can limit the level of activity and impair the quality of life. In China, many clinical studies have demonstrated that skin‐patches of Chinese herbal medicines benefit patients with acute gouty arthritis. However, the reported clinical effects vary.

Design

A systematic review and meta‐analysis of randomized controlled trials.

Data sources

Three English databases including CENTRAL (1993 to February 2017), PubMed (1966 to February 2017) and EMBASE (1974 to February 2017) and four Chinese databases including Chinese National Knowledge Infrastructure, Chinese VIP Information, SinoMed and Wanfang (all, 1949 ‐ February 2017) were searched. Randomized controlled trials that compared skin‐patches of Chinese herbal medicine with or without conventional treatments to conventional treatments, no treatment or a placebo treatment for patients with acute gouty arthritis were included.

Review methods

We conducted a systematic review and meta‐analysis following the Cochrane process. Two authors selected the studies, extracted the data and evaluated the risk of bias of the included trials.

Results

Nineteen studies met our inclusion criteria. After synthesizing the data, the results showed that skin‐patches of CHM combined with Western medicine seemed to be more effective than Western medicine alone for pain relief in patients with acute gouty arthritis and had fewer adverse events.

Conclusion

Due to the quality of the data, larger and more rigorously designed clinical trials with proper outcome measures are necessary.     

Superlattice-like structure and enhanced ferroelectric properties of intergrowth Aurivillius oxides

Aurivillius oxides with an intergrowth structures have been receiving increasing interest because of their special structures and potential outstanding ferroelectric properties. In this work, Bi₃LaTiNbFeO₁₂–Bi₅Ti₃FeO₁₅ and Bi₃TiNbO₉–Bi₃LaTiNbFeO₁₂ compounds were successfully synthetised using a simple solid-state reaction method. X-Ray diffraction patterns and scanning transmission electron microscopy high angle annular dark field (STEM-HAADF) images confirm the 2–3 and the 3–4 intergrowth structures in Bi₃TiNbO₉–Bi₃LaTiNbFeO₁₂ and Bi₃LaTiNbFeO₁₂–Bi₅Ti₃FeO₁₅ compounds, respectively. A superlattice-like distortion in these oxides was proposed resulting from the combination of sub-lattices with different a and b parameters, which was validated by XRD refinements and Raman spectra. Polarization-electric field tests and pulsed polarization positive-up negative-down measurements demonstrate that such superlattice-like structures can effectively enhance the intrinsic ferroelectric polarization and coercive field of these oxides, especially when compared with their component oxides Bi₃TiNbO₉, Bi₃LaTiNbFeO₁₂ and Bi₅Ti₃FeO₁₅. Simultaneously, ferroelectric Curie temperatures of Bi₃TiNbO₉–Bi₃LaTiNbFeO₁₂ and Bi₃LaTiNbFeO₁₂–Bi₅Ti₃FeO₁₅ oxides are lowered because of the internal stress in the superlattice-like structure. Nevertheless, the paramagnetism of the samples is hardly influenced by their structure, while mainly related to their iron content, in which iron has a similar effective magnetic moment around 3.4–3.9.

Aurivillius oxides with an intergrowth structures have been receiving increasing interest because of their special structures and potential outstanding ferroelectric properties.     

Thromboelastography (TEG) in normal pregnancy and its diagnostic efficacy in patients with gestational hypertension,gestational diabetes mellitus,or preeclampsia

BackgroundThromboelastography (TEG) provides global assessment of hemostatic function and has been recommended to monitor potential coagulopathies during pregnancy in which hypercoagulable state is favored. In present study, we established the reference intervals (RIs) of the TEG parameters (R, K, MA, and α‐angle) with Chinese pregnant women of third trimester. In addition, we examined the diagnostic efficacies of the TEG parameters in the patients diagnosed of gestational hypertension (GH), gestational diabetes mellitus (GDM), or preeclampsia (PE).MethodsWith specified including and excluding criteria, non‐pregnant controls, healthy pregnant women, and pregnant women with GH, GDM, or PE had their venous blood drawn at Beijing Obstetrics and Gynecology Hospital, followed by TEG tests performed in the clinical laboratory.ResultsThe RIs determined with the healthy pregnant women (in third trimester) for R, K, MA, and α‐angle were 4.0‐7.7, 1.2‐3.2, 51.9‐70.1, and 41.4‐74.4, respectively. When compared with the healthy pregnancy group, the K value was significantly decreased in GH patients but increased in PE patients; MA was significantly lower in the PE group. In the receiver operating characteristic curve (ROC) analyses, K value was able to efficiently distinguish normal pregnancy from the GH patients, with an AUC of 0.86 which is far better than those of R (AUC = 0.57) and MA (AUC = 0.56). For the PE patients, the AUC of MA (0.69) was significantly greater than that of R (0.50).ConclusionsThromboelastography may provide more accurate experimental basis for monitoring coagulation functions especially in pregnant women with complications of GH and PE.     

Preoperative Aspiration Culture for Preoperative Diagnosis of Infection in Total Hip or Knee Arthroplasty

This meta-analysis evaluated preoperative aspiration culture for diagnosing prosthetic joint infection (PJI) in total hip arthroplasty (THA) and total knee arthroplasty (TKA). The pooled sensitivity and specificity were 0.72 (95% confidence interval, 0.65 to 0.78) and 0.95 (0.93 to 0.97), respectively. Subgroup analyses revealed nonsignificant worse diagnostic performance for THA than for TKA (sensitivity, 0.70 versus 0.78; specificity, 0.94 versus 0.96). Preoperative aspiration culture has moderate to high sensitivity and very high specificity for diagnosing PJI.     

A sensor for needle puncture force measurement during interventional radiological procedures

Computer-based simulation for interventional radiology training has attracted increasing attention in recent years because of its potential to train remotely from patients and to provide objective assessment of proficiency. Yet developing a high fidelity simulator with realistic tactile feedback requires accurate knowledge of forces exerted on medical devices during interventional radiology procedures. This paper presents the development and validation of a force sensor for the measurement of axial forces generated during needle, and combined cannula/trocar, puncture procedures in patients. In order to assess the performance of this sensor, in vitro measurements were obtained using needle penetration of porcine liver, kidney and muscle. The results were compared with forces measured by means of a tensile tester.Calibration results showed that the force sensor has high sensitivity and linearity. Comparison of the force profiles obtained from the sensor and the tensile tester shows that good agreement was achieved in the in vitro studies for all the tissues tested.Preliminary clinical force measurements during arterial puncture and liver biopsy procedures have been performed in patients. An example of force recording for each procedure type is presented.     

Distinct neural ensemble response statistics are associated with recognition and discrimination of natural sound textures

The perception of sound textures, a class of natural sounds defined by statistical sound structure such as fire, wind, and rain, has been proposed to arise through the integration of time-averaged summary statistics. Where and how the auditory system might encode these summary statistics to create internal representations of these stationary sounds, however, is unknown. Here, using natural textures and synthetic variants with reduced statistics, we show that summary statistics modulate the correlations between frequency organized neuron ensembles in the awake rabbit inferior colliculus (IC). These neural ensemble correlation statistics capture high-order sound structure and allow for accurate neural decoding in a single trial recognition task with evidence accumulation times approaching 1 s. In contrast, the average activity across the neural ensemble (neural spectrum) provides a fast (tens of milliseconds) and salient signal that contributes primarily to texture discrimination. Intriguingly, perceptual studies in human listeners reveal analogous trends: the sound spectrum is integrated quickly and serves as a salient discrimination cue while high-order sound statistics are integrated slowly and contribute substantially more toward recognition. The findings suggest statistical sound cues such as the sound spectrum and correlation structure are represented by distinct response statistics in auditory midbrain ensembles, and that these neural response statistics may have dissociable roles and time scales for the recognition and discrimination of natural sounds.

What makes a sound natural, and what are the neural codes that support recognition and discrimination of real-world natural sounds? Although it is known that the early auditory system decomposes sounds along fundamental acoustic dimensions such as intensity and frequency, the higher-level neural computations that mediate natural sound recognition are poorly understood. This general lack of understanding is in part attributed to the structural complexity of natural sounds, which is difficult to study with traditional auditory test stimuli, such as tones, noise, or modulated sequences. Such stimuli can reveal details of the neural representation for relatively low-level acoustic cues, yet they don’t capture the rich and diverse statistical structure of natural sounds. Thus, they cannot reveal many of the computations associated with higher-level sound properties that facilitate auditory tasks such as natural sound recognition or discrimination. A class of stationary natural sounds termed textures, such as the random sounds emanating from a running stream, a crowded restaurant, or a chorus of birds, have been proposed as alternative natural stimuli which allow for manipulating high-level acoustic structure (1). Texture sounds are composed of spatially and temporally distributed acoustic elements that are collectively perceived as a single source and are defined by their statistical features. Identification of these natural sounds has been proposed to be mediated through the integration of time-averaged summary statistics, which account for high-level structures such as the sparsity and time-frequency correlation structure found in many natural sounds (1–3). Using a generative model of the auditory system to measure summary statistics from natural texture sounds, it is possible to synthesize highly realistic synthetic auditory textures (1). This suggests that high-order statistical cues are perceptually salient and that the brain might extract these statistical features to build internal representations of sounds.Although neural activity throughout the auditory pathway is sensitive to a variety of statistical cues such as the sound contrast, modulation power spectrum, and correlation structure (4–12), how sound summary statistics contribute toward basic auditory tasks such as recognition and discrimination of sounds is poorly understood. Furthermore, it is unclear where along the auditory pathway summary statistics are represented and how they are reflected in neural activity. The inferior colliculus (IC) is one candidate midlevel structure for representing such summary statistics. As the principal midbrain auditory nucleus, the IC receives highly convergent brainstem inputs with varied sound selectivities. Neurons in the IC are selective over most of the perceptually relevant range of sound modulations and neural activity is strongly driven by multiple high-order sound statistics (4–7, 10). In previous work, we showed the correlation statistics of natural sounds are highly informative about stimulus identity and they appear to be represented in the correlation statistics of auditory midbrain neuron ensembles (4). Correlations between neurons have also been proposed as mechanisms for pitch identification (13) and sound localization (14). This broadly supports the hypotheses that high-order sound statistics are reflected in the response statistics of neural ensembles and that these neural response statistics could potentially subserve basic auditory tasks.Here using natural and synthetic texture sounds, we test the hypothesis that statistical structure in natural texture sounds modulates the response statistics of neural ensembles in the IC of unanesthetized rabbits, and that distinct neural response statistics have the potential to contribute toward sound recognition and discrimination behaviors. By comparing the performance of neural decoders with human texture perception, we find that place rate representation of sounds (neural spectrum) accumulates evidence about the sounds on relatively fast time scales (tens of milliseconds) exhibiting decoding trends that mirror those seen for human texture discrimination. High-order statistical sound cues, by comparison, are reflected in the correlation statistics of neural ensembles, which require substantially longer evidence accumulation times (>500 ms) and follow trends that mirror those measured for human texture recognition. Collectively, the findings suggest that spectrum cues and accompanying place rate representation (neural spectrum) may contribute surprisingly little toward the recognition of auditory textures. Instead, high-order statistical sound structure is reflected in the distributed patterns of correlated activity across IC neural ensembles and such neural response structure has the potential to contribute toward the recognition of natural auditory textures.