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JAMA Jan 2023In the US, nearly all medical devices progress to market under the 510(k) pathway, which uses previously authorized devices (predicates) to support new authorizations....
IMPORTANCE
In the US, nearly all medical devices progress to market under the 510(k) pathway, which uses previously authorized devices (predicates) to support new authorizations. Current regulations permit manufacturers to use devices subject to a Class I recall-the FDA's most serious designation indicating a high probability of adverse health consequences or death-as predicates for new devices. The consequences for patient safety are not known.
OBJECTIVE
To determine the risk of a future Class I recall associated with using a recalled device as a predicate device in the 510(k) pathway.
DESIGN AND SETTING
In this cross-sectional study, all 510(k) devices subject to Class I recalls from January 2017 through December 2021 (index devices) were identified from the FDA's annual recall listings. Information about predicate devices was extracted from the Devices@FDA database. Devices authorized using index devices as predicates (descendants) were identified using a regulatory intelligence platform. A matched cohort of predicates was constructed to assess the future recall risk from using a predicate device with a Class I recall.
MAIN OUTCOMES AND MEASURES
Devices were characterized by their regulatory history and recall history. Risk ratios (RRs) were calculated to compare the risk of future Class I recalls between devices descended from predicates with matched controls.
RESULTS
Of 156 index devices subject to Class I recall from 2017 through 2021, 44 (28.2%) had prior Class I recalls. Predicates were identified for 127 index devices, with 56 (44.1%) using predicates with a Class I recall. One hundred four index devices were also used as predicates to support the authorization of 265 descendant devices, with 50 index devices (48.1%) authorizing a descendant with a Class I recall. Compared with matched controls, devices authorized using predicates with Class I recalls had a higher risk of subsequent Class I recall (6.40 [95% CI, 3.59-11.40]; P<.001).
CONCLUSIONS AND RELEVANCE
Many 510(k) devices subjected to Class I recalls in the US use predicates with a known history of Class I recalls. These devices have substantially higher risk of a subsequent Class I recall. Safeguards for the 510(k) pathway are needed to prevent problematic predicate selection and ensure patient safety.
Topics: Humans; Cross-Sectional Studies; Databases, Factual; Device Approval; Medical Device Recalls; United States; United States Food and Drug Administration
PubMed: 36625810
DOI: 10.1001/jama.2022.23279 -
The Journal of Medicine Access 2022Substandard and falsified (SF) medical products are removed from circulation through a process called 'product recall' by medicines regulatory agencies. In Zambia, the...
BACKGROUND
Substandard and falsified (SF) medical products are removed from circulation through a process called 'product recall' by medicines regulatory agencies. In Zambia, the Zambia Medicines Regulatory Authority (ZAMRA) is responsible for recalling SF medical products from the Zambian market through passive and active surveillance methods. This study aimed to describe the prevalence of recalls of SF medical products and to analyse the frequently recalled therapeutic categories, dosage forms, categories of defects that led to the recalls and their sources with respect to the country of the marketing authorisation holder (MAH) or manufacturer.
METHODS
We conducted a descriptive cross-sectional review of the product recalls issued by ZAMRA between January 2018 and December 2021. A search for all medical product alerts and recalls issued by ZAMRA was carried out by reviewing the internal post-marketing surveillance database kept at ZAMRA headquarters. Data were extracted using a structured Excel database and analysed using Microsoft Excel.
RESULTS
A total of 119 alerts were received during the review period, of which 83 (69.7%) were product recalls. Oral solid dosage forms were the most recalled dosage form (53%). Furthermore, the number of recalls increased in 2020 (44.6%) and 2021 (22.9%), with the majority (20.5%) of the recalled products being substandard products classified as antiseptics and disinfectants and were attributed to the high demand during the COVID-19 pandemic. Manufacturing laboratory control issues were the reason for product recall in almost half (47.4%) of the cases. Most of the products recalled originated from India (38.6%), followed by Zambia (25.3%). Only one suspected falsified product was recalled between 2018 and 2021. A total of 66 recalls of the 83 products were initiated by ZAMRA, with only 17 voluntarily by foreign MAHs. No product recall was initiated by the local representatives of foreign manufacturers or MAH.
CONCLUSION
The majority of the pharmaceutical product recalls in Zambia were substandard products. Manufacturing laboratory control issues lead to most recalls and require investigation of the root causes, preventive action, and strict compliance with the good manufacturing practices guidelines by manufacturers.
PubMed: 36601496
DOI: 10.1177/27550834221141767 -
GIScience & Remote Sensing 2022It is common knowledge that the level of landscape heterogeneity may affect the performance of remote sensing based land use / land cover classification. While this...
It is common knowledge that the level of landscape heterogeneity may affect the performance of remote sensing based land use / land cover classification. While this issue has been studied in depth for land cover data in general, the specific relationship between the mapping accuracy and morphological characteristics of built-up surfaces has not been analyzed in detail, an urgent need given the recent emergence of a variety of global, fine-resolution settlement datasets. Moreover, previous studies typically rely on aggregated, broad-scale landscape metrics to quantify the morphology of built-up areas, neglecting the fine-grained spatial variation and scale dependency of such metrics. Herein, we aim to fill this knowledge gap by assessing the associations between localized (focal) landscape metrics, derived from binary built-up surfaces and localized data accuracy estimates. We tested our approach for built-up surfaces from the Global Human Settlement Layer (GHSL) for Massachusetts (USA). Specifically, we examined the explanatory power of landscape metrics with respect to both commission and omission errors in the multi-temporal GHS-BUILT R2018A data product. We found that the Landscape Shape Index (LSI) calculated in focal windows exhibits, on average, the highest levels of correlation to focal accuracy measures. These relationships are scale-dependent, and become stronger with increasing level of spatial support. We found that thematic omission error, as measured by Recall, has the strongest relationship to measures of built-up surface morphology across different temporal epochs and spatial resolutions. The results of our regression analysis (R>0.9), estimating accuracy based on landscape metrics, confirmed these findings. Lastly, we tested the generalizability of our findings by regionally stratifying our regression models and applying them to a different version of the GHSL (i.e., the GHS-BUILT-S2) and a different study area. We observed varying levels of model transferability, indicating that the relationship between accuracy and landscape metrics may be sensor-specific, and is heavily localized for most accuracy metrics, but quite generalizable for the Recall measure. This indicates that there is a strong and generalizable association between morphological properties of built-up land and the degree to which it is "undermapped".
PubMed: 36593994
DOI: 10.1080/15481603.2022.2131192 -
Addictive Behaviors Apr 2023Tobacco-related content is prevalent on social media, yet many methods of measuring exposure are inadequate due to the personalized nature of online marketing. The...
INTRODUCTION
Tobacco-related content is prevalent on social media, yet many methods of measuring exposure are inadequate due to the personalized nature of online marketing. The purpose of this paper is to examine the association between exposure to pro-tobacco messages (both industry-sponsored and user-generated) and the use of tobacco products, as reported via ecological momentary assessment (EMA).
METHODS
Young adults (n = 175) were instructed to record all sightings of marketing (both in-person and online) related to tobacco for 28 days. Tobacco product use and recall of message encounters were assessed daily using app-initiated EMA.
RESULTS
Participants who reported exposure to tobacco messages were significantly more likely to report using tobacco, adjusting for gender, age, race/ethnicity, baseline use of any tobacco product, and having friends who use tobacco and e-cigarettes (p <.001). For each industry-sponsored message viewed, the odds of using tobacco or e-cigarettes in a given day increased by a factor of 1.77 (95 % CI = 1.41, 2.23). For each user-generated message viewed, the odds of using tobacco or e-cigarettes in a given day increased by a factor of 1.52 (95 % CI = 1.27, 1.83).
DISCUSSION
To our knowledge, this is the first study to specifically examine the association between exposure to user-generated messages and daily tobacco use. The findings suggests that there is a unique element to user-generated messages that distinguishes them from both traditional marketing and from simple peer influence.
Topics: Humans; Young Adult; Advertising; Nicotiana; Tobacco Products; Ecological Momentary Assessment; Electronic Nicotine Delivery Systems; Marketing; Tobacco Use
PubMed: 36592525
DOI: 10.1016/j.addbeh.2022.107601 -
Sensors (Basel, Switzerland) Nov 2022The demands for model accuracy and computing efficiency in fault warning scenarios are increasing as high-speed railway train technology continues to advance. The black...
The demands for model accuracy and computing efficiency in fault warning scenarios are increasing as high-speed railway train technology continues to advance. The black box model is difficult to interpret, making it impossible for this technology to be widely adopted in the railway industry, which has strict safety regulations. This paper proposes a fault early warning machine learning model based on feature contribution and causal inference. First, the contributions of the features are calculated through the Shapley additive explanations model. Then, causal relationships are discovered through causal inference models. Finally, data from causal and high-contribution time series are applied to the model. Ablation tests are conducted with the Naïve Bayes, Gradient Boosting Decision Tree, eXtreme Gradient Boosting, and other models in order to confirm the efficiency of the method based on early warning data regarding the on-site high-speed train traction equipment circuit board failure. The findings indicate that the strategy improves the evaluation markers, including the early warning accuracy, precision, recall, and F1 score, by an average of more than 10%. There is a 35% improvement in the computing efficiency, and the model can provide feature causal graph verification for expert product decision-making.
Topics: Bayes Theorem; Equipment Failure; Industry; Machine Learning; Records
PubMed: 36501884
DOI: 10.3390/s22239184 -
Foods (Basel, Switzerland) Dec 2022Nuts are widely consumed worldwide, mainly due to their characteristic flavor and texture, ease of consumption, and their functional properties. In addition, consumers... (Review)
Review
Nuts are widely consumed worldwide, mainly due to their characteristic flavor and texture, ease of consumption, and their functional properties. In addition, consumers increasingly demand natural or slightly processed foods with high quality. Consequently, non-thermal treatments are a viable alternative to thermal treatments used to guarantee safety and long shelf life, which produce undesirable changes that affect the sensory quality of nuts. Non-thermal treatments can achieve results similar to those of the traditional (thermal) ones in terms of food safety, while ensuring minimal loss of bioactive compounds and sensory properties, thus obtaining a product as similar as possible to the fresh one. This article focuses on a review of the main non-thermal treatments currently available for nuts (cold plasma, high pressure, irradiation, pulsed electric field, pulsed light, ultrasound and ultraviolet light) in relation to their effects on the quality and safety of nuts. All the treatments studied have shown promise with regard to the inhibition of the main microorganisms affecting nuts (e.g., , , and ). Furthermore, by optimizing the treatment, it is possible to maintain the organoleptic and functional properties of these products.
PubMed: 36496699
DOI: 10.3390/foods11233891 -
MMWR. Morbidity and Mortality Weekly... Dec 2022In July 2021, the Virginia Department of Health notified CDC of a cluster of eight invasive infections with Burkholderia stabilis, a bacterium in the Burkholderia...
In July 2021, the Virginia Department of Health notified CDC of a cluster of eight invasive infections with Burkholderia stabilis, a bacterium in the Burkholderia cepacia complex (BCC), among hospitalized patients at hospital A. Most patients had undergone ultrasound-guided procedures during their admission. Culture of MediChoice M500812 nonsterile ultrasound gel used in hospital A revealed contamination of unopened product with B. stabilis that matched the whole genome sequencing (WGS) of B. stabilis strains found among patients. CDC and hospital A, in collaboration with partner health care facilities, state and local health departments, and the Food and Drug Administration (FDA), identified 119 B. stabilis infections in 10 U.S. states, leading to the national recall of all ultrasound gel products produced by Eco-Med Pharmaceutical (Eco-Med), the manufacturer of MediChoice M500812. Additional investigation of health care facility practices revealed frequent use of nonsterile ultrasound gel to assist with visualization in preparation for or during invasive, percutaneous procedures (e.g., intravenous catheter insertion). This practice could have allowed introduction of contaminated ultrasound gel into sterile body sites when gel and associated viable bacteria were not completely removed from skin, leading to invasive infections. This outbreak highlights the importance of appropriate use of ultrasound gel within health care settings to help prevent patient infections, including the use of only sterile, single-use ultrasound gel for ultrasonography when subsequent percutaneous procedures might be performed.
Topics: Humans; Disease Outbreaks; Drug Contamination; Health Facilities; Ultrasonography; United States; Gels; Equipment Contamination; Burkholderia Infections
PubMed: 36454695
DOI: 10.15585/mmwr.mm7148a3 -
Computational Intelligence and... 2022As we all know, sports have great benefits for students. However, with more and more learning pressure, students' physical education has not been paid attention to by...
As we all know, sports have great benefits for students. However, with more and more learning pressure, students' physical education has not been paid attention to by teachers and parents, so the analysis and prediction of physical education performance have become significant work. This paper proposes a new method (factorization deep product neural network) for PE course score prediction. The experimental results show that, compared with the existing performance prediction methods (LR, SVM, FM, and the DNN), the proposed method achieves the best prediction effect on the sports education dataset. Compared with the traditional optimal methods, the accuracy and AUC of DNN are both improved by 2%. In addition, there is also a significant improvement in accuracy, recall, and F1. In addition, this study found that considering two or more features at the same time has a certain influence on the prediction results of students' grades. The proposed feature combination method can learn feature combinations automatically, consider the influence of first-order features, second-order features, and high-order features in the meantime, and acquire the relationship information between each feature and performance. Compared with single-feature learning, the proposed method in this paper can enhance prediction accuracy significantly. Moreover, several dimensionality reduction methods are used in this paper, and we found that the PCA model for data processing outperformed all the benchmark models.
Topics: Humans; Students; Physical Functional Performance; Neural Networks, Computer; Learning; Sports
PubMed: 36444308
DOI: 10.1155/2022/4221254 -
Sensors (Basel, Switzerland) Nov 2022Sensing and remembering features in visual scenes are conditioned by visual attention and methods to guide it. This should be relevant in terms of product placement,... (Randomized Controlled Trial)
Randomized Controlled Trial
Sensing and remembering features in visual scenes are conditioned by visual attention and methods to guide it. This should be relevant in terms of product placement, which has become an important part of incorporating brands into different mass media formats with a commercial purpose. The approach can be challenging in 360° video, where an omnidirectional view enables consumers to choose different viewing perspectives, which may result in overlooking the brands. Accordingly, attention guidance methods should be applied. This study is the first to explore diegetic guidance methods as the only appropriate guiding method for an unobtrusive and unconscious nature of product placement. To test the effectiveness of three different diegetic guiding methods, a between-subject design was employed, where the participants were assigned randomly to one of four videos with the same scene but different guiding methods. The findings show and explain the discrepancy with studies on guiding attention in other contexts, as there were no significant differences between the guiding cues according to brand recall and brand recognition. The results also indicate a significant influence of brand familiarity on brand recall in 360° video. The article concludes by providing limitations, future research directions, and recommendations for audiovisual policy.
Topics: Humans; Recognition, Psychology; Mental Recall; Cues
PubMed: 36433406
DOI: 10.3390/s22228809 -
Epidemiology and Infection Nov 2022From 2016-2019, dry bulb onions were the suspected cause of three multistate outbreaks in the United States. We investigated a large multistate outbreak of Newport...
From 2016-2019, dry bulb onions were the suspected cause of three multistate outbreaks in the United States. We investigated a large multistate outbreak of Newport infections that caused illnesses in both the United States and Canada in 2020. Epidemiologic, laboratory and traceback investigations were conducted to determine the source of the infections, and data were shared among U.S. and Canadian public health officials. We identified 1127 U.S. illnesses from 48 states with illness onset dates ranging from 19 June to 11 September 2020. Sixty-six per cent of ill people reported consuming red onions in the week before illness onset. Thirty-five illness sub-clusters were identified during the investigation and seventy-four per cent of sub-clusters served red onions to customers during the exposure period. Traceback for the source of onions in illness sub-clusters identified a common onion grower in Bakersfield, CA as the source of red onions, and onions were recalled at this time. Although other strains of Newport were identified in environmental samples collected at the Bakersfield, CA grower, extensive environmental and product testing did not yield the outbreak strain. This was the third largest U.S. foodborne outbreak in the last 30 years. It is the first U.S. multistate outbreak with a confirmed link to dry bulb onions, and it was nearly 10-fold larger than prior outbreaks with a suspected link to onions. This outbreak is notable for its size and scope, as well as the international data sharing that led to implication of red onions as the primary cause of the outbreak. Although an environmental assessment at the grower identified several factors that likely contributed to the outbreak, no main reason was identified. The expedient identification of the outbreak vehicle and response of multiple public health agencies allowed for recall and removal of product from the marketplace, and rapid messaging to both the public and industry on actions to protect consumers; these features contributed to a decrease in cases and expeditious conclusion of the outbreak.
Topics: Humans; Canada; Disease Outbreaks; Onions; Salmonella; Salmonella enterica; Salmonella Infections; United States; Food Contamination
PubMed: 36382397
DOI: 10.1017/S0950268822001571