-
Environment International Jun 2021Conservation activities and natural resource management interventions have often aimed to tackle the dual challenge of improving nature conservation and human... (Review)
Review
What is the evidence documenting the effects of marine or coastal nature conservation or natural resource management activities on human well-being in South East Asia? A systematic map.
BACKGROUND
Conservation activities and natural resource management interventions have often aimed to tackle the dual challenge of improving nature conservation and human well-being. However, there is concern over the extent to which this dual goal has been achieved, and an increasing recognition of trade-offs and synergies within and between aspects of each of the goals. The amount and scope of the available evidence on the success of conservation and management interventions in both arenas has lacked documentation, for a number of reasons, including limited resources for monitoring and evaluation and the difficulty in bringing together a disparate evidence base. This systematic map focuses on the interaction between marine conservation management and the health and well-being of coastal communities in South East Asia.
METHOD
We searched bibliographic databases to find published literature, and identified grey literature through institutional and organisational website searches and key stakeholders. Eligibility criteria were applied in two stages, title and abstract and full text, with consistency checks. We extracted meta-data on the design and characteristics of each study, from which we produced an interactive database and map, and a narrative summary.
RESULTS
We assessed 42,894 records at title and abstract from the main searches. 1,331 articles were assessed at full text (30 articles were not retrievable). 287 articles (281 studies) were included in the systematic map. Most studies were peer-reviewed publications (90%), and from the Philippines and Indonesia (72%). 31% of studies were solely qualitative, 45% were solely quantitative and 24% included both qualitative and quantitative research. Only 24% (31/127) of quantitative studies included a comparator. We identified knowledge clusters where studies investigated the links between the marine conservation interventions: Site Protection, Economic or Livelihood Incentives or Alternatives, or Habitat Management, and the human health and well-being outcomes: Economic Living Standards, Governance and Empowerment, or Social Relations. In addition, qualitative research clusters were identified exploring the links between the intervention Habitat Management, and the outcome Governance and Empowerment, and between the intervention Economic or Livelihood Incentives or Alternatives, and the outcomes of Governance and Empowerment, and Social Relations. We identified major knowledge gaps in evidence for the effect of marine conservation interventions on the outcomes Freedom of Choice and Action, Security and Safety, Subjective Well-being, Health, and Culture and Spirituality. There was a lack of studies involving Education, Awareness and Activism interventions that reported any human health and well-being outcomes.
CONCLUSION
We present the first updatable, interrogable and comprehensive evidence map on this topic for South East Asia. Our work supports further, detailed investigation of knowledge clusters using systematic review and also serves to identify understudied topic areas. The lack of comparative, quantitative studies suggests that future research should include counterfactuals to strengthen the robustness of evidence base. Users of this systematic map should recognise that much evidence may be national or locally specific, and that we did not undertake an assessment of study quality. Thus, when considering implications for policy and decision-making, users should carefully consider the heterogeneity of available evidence and refer to original research articles to gain a full depth of understanding and context.
Topics: Conservation of Natural Resources; Asia, Eastern; Humans; Natural Resources; Philippines; Socioeconomic Factors
PubMed: 33713939
DOI: 10.1016/j.envint.2021.106397 -
Archives of Orthopaedic and Trauma... Nov 2022In this review paper, graft failure rates of different graft types (hamstring tendon autografts, bone-patellar tendon-bone autografts, quadriceps tendon autografts and... (Review)
Review
INTRODUCTION
In this review paper, graft failure rates of different graft types (hamstring tendon autografts, bone-patellar tendon-bone autografts, quadriceps tendon autografts and diverse allografts) that are used for surgical reconstruction of the anterior cruciate ligament are compared and statistically analysed.
METHODS
Literature search was conducted in PubMed according to Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) criteria. A total of 194 studies, which reported graft failure rates of at least one of the anterior cruciate ligament reconstruction methods mentioned above, were included in this systematic review. To be able to compare studies with different follow-up periods, a yearly graft failure rate for each reconstruction group was calculated and then investigated for significant differences by using the Kruskal-Wallis test.
RESULTS
Overall, a total of 152,548 patients treated with an anterior cruciate ligament reconstruction were included in the calculations. Comparison of graft types showed that hamstring tendon autografts had a yearly graft failure rate of 1.70%, whereas the bone-patellar tendon-bone autograft group had 1.16%, the quadriceps tendon autograft group 0.72%, and the allografts 1.76%.
CONCLUSION
The findings of this meta-data study indicate that reconstructing the anterior cruciate ligament using quadriceps tendon autografts, hamstring tendon autografts, patellar tendon autografts or allografts does not show significant differences in terms of graft failure rates.
Topics: Anterior Cruciate Ligament; Anterior Cruciate Ligament Injuries; Anterior Cruciate Ligament Reconstruction; Autografts; Bone-Patellar Tendon-Bone Grafting; Hamstring Tendons; Humans; Transplantation, Autologous
PubMed: 34536121
DOI: 10.1007/s00402-021-04147-w -
PLoS Neglected Tropical Diseases Jun 2016Schistosomiasis control mainly relies on preventive chemotherapy with praziquantel (PZQ) distributed through mass drug administration. With a target of 260 million... (Review)
Review
The Schistosomiasis Clinical Trials Landscape: A Systematic Review of Antischistosomal Treatment Efficacy Studies and a Case for Sharing Individual Participant-Level Data (IPD).
BACKGROUND
Schistosomiasis control mainly relies on preventive chemotherapy with praziquantel (PZQ) distributed through mass drug administration. With a target of 260 million treatments yearly, reliably assessing and monitoring efficacy is all-important. Recommendations for treatment and control of schistosomiasis are supported by systematic reviews and meta-analyses of aggregated data, which however also point to limitations due to heterogeneity in trial design, analyses and reporting. Some such limitations could be corrected through access to individual participant-level data (IPD), which facilitates standardised analyses.
METHODOLOGY
A systematic literature review was conducted to identify antischistosomal drug efficacy studies performed since 2000; including electronic searches of the Cochrane Infectious Diseases Group specialised register and the Cochrane Library, PubMed, CENTRAL and Embase; complemented with a manual search for articles listed in past reviews. Antischistosomal treatment studies with assessment of outcome within 60 days post-treatment were eligible. Meta-data, i.e. study-level characteristics (Schistosoma species, number of patients, drug administered, country, etc.) and efficacy parameters were extracted from published documents to evaluate the scope of an individual-level data sharing platform.
PRINCIPAL FINDINGS
Out of 914 documents screened, 90 studies from 26 countries were included, enrolling 20,517 participants infected with Schistosoma spp. and treated with different PZQ regimens or other drugs. Methodologies varied in terms of diagnostic approaches (number of samples and test repeats), time of outcome assessment, and outcome measure (cure rate or egg reduction rate, as an arithmetic or geometric mean), making direct comparison of published data difficult.
CONCLUSIONS
This review describes the landscape of schistosomiasis clinical research. The volume of data and the methodological and reporting heterogeneity identified all indicate that there is scope for an individual participant-level database, to allow for standardised analyses.
Topics: Anthelmintics; Data Interpretation, Statistical; Humans; Randomized Controlled Trials as Topic; Schistosomiasis
PubMed: 27347678
DOI: 10.1371/journal.pntd.0004784 -
Journal of Medical Internet Research Jul 2021Recent years have been witnessing a substantial improvement in the accuracy of skin cancer classification using convolutional neural networks (CNNs). CNNs perform on par... (Review)
Review
BACKGROUND
Recent years have been witnessing a substantial improvement in the accuracy of skin cancer classification using convolutional neural networks (CNNs). CNNs perform on par with or better than dermatologists with respect to the classification tasks of single images. However, in clinical practice, dermatologists also use other patient data beyond the visual aspects present in a digitized image, further increasing their diagnostic accuracy. Several pilot studies have recently investigated the effects of integrating different subtypes of patient data into CNN-based skin cancer classifiers.
OBJECTIVE
This systematic review focuses on the current research investigating the impact of merging information from image features and patient data on the performance of CNN-based skin cancer image classification. This study aims to explore the potential in this field of research by evaluating the types of patient data used, the ways in which the nonimage data are encoded and merged with the image features, and the impact of the integration on the classifier performance.
METHODS
Google Scholar, PubMed, MEDLINE, and ScienceDirect were screened for peer-reviewed studies published in English that dealt with the integration of patient data within a CNN-based skin cancer classification. The search terms skin cancer classification, convolutional neural network(s), deep learning, lesions, melanoma, metadata, clinical information, and patient data were combined.
RESULTS
A total of 11 publications fulfilled the inclusion criteria. All of them reported an overall improvement in different skin lesion classification tasks with patient data integration. The most commonly used patient data were age, sex, and lesion location. The patient data were mostly one-hot encoded. There were differences in the complexity that the encoded patient data were processed with regarding deep learning methods before and after fusing them with the image features for a combined classifier.
CONCLUSIONS
This study indicates the potential benefits of integrating patient data into CNN-based diagnostic algorithms. However, how exactly the individual patient data enhance classification performance, especially in the case of multiclass classification problems, is still unclear. Moreover, a substantial fraction of patient data used by dermatologists remains to be analyzed in the context of CNN-based skin cancer classification. Further exploratory analyses in this promising field may optimize patient data integration into CNN-based skin cancer diagnostics for patients' benefits.
Topics: Dermoscopy; Humans; Melanoma; Neural Networks, Computer; Skin Neoplasms
PubMed: 34255646
DOI: 10.2196/20708 -
The effects of population management on wild ungulates: A systematic map of evidence for UK species.PloS One 2022Over recent decades, the abundance and geographic ranges of wild ungulate species have expanded in many parts of Europe, including the UK. Populations are managed to... (Meta-Analysis)
Meta-Analysis
INTRODUCTION
Over recent decades, the abundance and geographic ranges of wild ungulate species have expanded in many parts of Europe, including the UK. Populations are managed to mitigate their ecological impacts using interventions, such as shooting, fencing and administering contraception. Predicting how target species will respond to interventions is critical for developing sustainable, effective and efficient management strategies. However, the quantity and quality of evidence of the effects of interventions on ungulate species is unclear. To address this, we systematically mapped research on the effects of population management on wild ungulate species resident in the UK.
METHODS
We searched four bibliographic databases, Google Scholar and nine organisational websites using search terms tested with a library of 30 relevant articles. Worldwide published peer-reviewed articles were considered, supplemented by 'grey' literature from UK-based sources. Three reviewers identified and screened articles for eligibility at title, abstract and full-text levels, based on predefined criteria. Data and metadata were extracted and summarised in a narrative synthesis supported by structured graphical matrices.
RESULTS
A total of 123 articles were included in the systematic map. Lethal interventions were better represented (85%, n = 105) than non-lethal interventions (25%, n = 25). Outcomes related to demography and behaviour were reported in 95% of articles (n = 117), whereas effects on health, physiology and morphology were studied in only 11% of articles (n = 14). Well-studied species included wild pigs (n = 58), red deer (n = 28) and roe deer (n = 23).
CONCLUSIONS
Evidence for the effects of population management on wild ungulate species is growing but currently limited and unevenly distributed across intervention types, outcomes and species. Priorities for primary research include: species responses to non-lethal interventions, the side-effects of shooting and studies on sika deer and Chinese muntjac. Shooting is the only intervention for which sufficient evidence exists for systematic review or meta-analysis.
Topics: Animals; Deer; Europe; United Kingdom
PubMed: 35687554
DOI: 10.1371/journal.pone.0267385 -
Frontiers in Cellular and Infection... 2022Cryptosporidiosis is a zoonotic disease caused by Cryptosporidium infection with the main symptom of diarrhea. The present study performed a metaanalysis to determine... (Meta-Analysis)
Meta-Analysis
INTODUCTION
Cryptosporidiosis is a zoonotic disease caused by Cryptosporidium infection with the main symptom of diarrhea. The present study performed a metaanalysis to determine the global prevalence of Cryptosporidium in Equus animals.
METHODS
Data collection was carried out using Chinese National Knowledge Infrastructure (CNKI), VIP Chinese journal database (VIP), WanFang Data, PubMed, and ScienceDirect databases, with 35 articles published before 2021 being included in this systematic analysis. This study analyzed the research data through subgroup analysis and univariate regression analysis to reveal the factors leading to high prevalence. We applied a random effects model (REM) to the metadata.
RESULTS
The total prevalence rate of Cryptosporidium in Equus was estimated to be 7.59% from the selected articles. The prevalence of Cryptosporidium in female Equus was 2.60%. The prevalence of Cryptosporidium in Equus under 1-year-old was 11.06%, which was higher than that of Equus over 1-year-old (2.52%). In the experimental method groups, the positive rate detected by microscopy was the highest (10.52%). The highest Cryptosporidium prevalence was found in scale breeding Equus (7.86%). The horses had the lowest Cryptosporidium prevalence (7.32%) among host groups. C. muris was the most frequently detected genotype in the samples (53.55%). In the groups of geographical factors, the prevalence rate of Cryptosporidium in Equus was higher in regions with low altitude (6.88%), rainy (15.63%), humid (22.69%), and tropical climates (16.46%).
DISCUSSION
The search strategy use of five databases might have caused the omission of some researches. This metaanalysis systematically presented the global prevalence and potential risk factors of Cryptosporidium infection in Equus. The farmers should strengthen the management of young and female Equus animals, improve water filtration systems, reduce stocking densities, and harmless treatment of livestock manure.
Topics: Female; Animals; Horses; Cryptosporidiosis; Cryptosporidium; Prevalence; Risk Factors; Zoonoses
PubMed: 36506009
DOI: 10.3389/fcimb.2022.1072385 -
JMIR MHealth and UHealth Jun 2020Comprehensive exams such as the Dean-Woodcock Neuropsychological Assessment System, the Global Deterioration Scale, and the Boston Diagnostic Aphasia Examination are the...
BACKGROUND
Comprehensive exams such as the Dean-Woodcock Neuropsychological Assessment System, the Global Deterioration Scale, and the Boston Diagnostic Aphasia Examination are the gold standard for doctors and clinicians in the preliminary assessment and monitoring of neurocognitive function in conditions such as neurodegenerative diseases and acquired brain injuries (ABIs). In recent years, there has been an increased focus on implementing these exams on mobile devices to benefit from their configurable built-in sensors, in addition to scoring, interpretation, and storage capabilities. As smartphones become more accepted in health care among both users and clinicians, the ability to use device information (eg, device position, screen interactions, and app usage) for subject monitoring also increases. Sensor-based assessments (eg, functional gait using a mobile device's accelerometer and/or gyroscope or collection of speech samples using recordings from the device's microphone) include the potential for enhanced information for diagnoses of neurological conditions; mapping the development of these conditions over time; and monitoring efficient, evidence-based rehabilitation programs.
OBJECTIVE
This paper provides an overview of neurocognitive conditions and relevant functions of interest, analysis of recent results using smartphone and/or tablet built-in sensor information for the assessment of these different neurocognitive conditions, and how human-device interactions and the assessment and monitoring of these neurocognitive functions can be enhanced for both the patient and health care provider.
METHODS
This survey presents a review of current mobile technological capabilities to enhance the assessment of various neurocognitive conditions, including both neurodegenerative diseases and ABIs. It explores how device features can be configured for assessments as well as the enhanced capability and data monitoring that will arise due to the addition of these features. It also recognizes the challenges that will be apparent with the transfer of these current assessments to mobile devices.
RESULTS
Built-in sensor information on mobile devices is found to provide information that can enhance neurocognitive assessment and monitoring across all functional categories. Configurations of positional sensors (eg, accelerometer, gyroscope, and GPS), media sensors (eg, microphone and camera), inherent sensors (eg, device timer), and participatory user-device interactions (eg, screen interactions, metadata input, app usage, and device lock and unlock) are all helpful for assessing these functions for the purposes of training, monitoring, diagnosis, or rehabilitation.
CONCLUSIONS
This survey discusses some of the many opportunities and challenges of implementing configured built-in sensors on mobile devices to enhance assessments and monitoring of neurocognitive functions as well as disease progression across neurodegenerative and acquired neurological conditions.
Topics: Computers, Handheld; Delivery of Health Care; Humans; Smartphone; Surveys and Questionnaires
PubMed: 32442150
DOI: 10.2196/15517 -
Journal of Ambient Intelligence and... 2023The success of deep learning over the traditional machine learning techniques in handling artificial intelligence application tasks such as image processing, computer...
UNLABELLED
The success of deep learning over the traditional machine learning techniques in handling artificial intelligence application tasks such as image processing, computer vision, object detection, speech recognition, medical imaging and so on, has made deep learning the buzz word that dominates Artificial Intelligence applications. From the last decade, the applications of deep learning in physiological signals such as electrocardiogram (ECG) have attracted a good number of research. However, previous surveys have not been able to provide a systematic comprehensive review including biometric ECG based systems of the applications of deep learning in ECG with respect to domain of applications. To address this gap, we conducted a systematic literature review on the applications of deep learning in ECG including biometric ECG based systems. The study analyzed systematically, 150 primary studies with evidence of the application of deep learning in ECG. The study shows that the applications of deep learning in ECG have been applied in different domains. We presented a new taxonomy of the domains of application of the deep learning in ECG. The paper also presented discussions on biometric ECG based systems and meta-data analysis of the studies based on the domain, area, task, deep learning models, dataset sources and preprocessing methods. Challenges and potential research opportunities were highlighted to enable novel research. We believe that this study will be useful to both new researchers and expert researchers who are seeking to add knowledge to the already existing body of knowledge in ECG signal processing using deep learning algorithm.
SUPPLEMENTARY INFORMATION
The online version contains supplementary material available at 10.1007/s12652-022-03868-z.
PubMed: 35821879
DOI: 10.1007/s12652-022-03868-z -
Journal of Translational Medicine Jul 2019Drug development is currently hampered by high attrition rates; many developed treatments fail during clinical testing. Part of the attrition may be due to low...
BACKGROUND
Drug development is currently hampered by high attrition rates; many developed treatments fail during clinical testing. Part of the attrition may be due to low animal-to-human translational success rates; so-called "translational failure". As far as we know, no systematic overview of published translational success rates exists.
SYSTEMATIC SCOPING REVIEW
The following research question was examined: "What is the observed range of the animal-to-human translational success (and failure) rates within the currently available empirical evidence?". We searched PubMed and Embase on 16 October 2017. We included reviews and all other types of "umbrella"-studies of meta-data quantitatively comparing the translational results of studies including at least two species with one being human. We supplemented our database searches with additional strategies. All abstracts and full-text papers were screened by two independent reviewers. Our scoping review comprises 121 references, with various units of measurement: compound or intervention (k = 104), study/experiment (k = 10), and symptom or event (k = 7). Diagnostic statistics corresponded with binary and continuous definitions of successful translation. Binary definitions comprise percentages below twofold error, percentages accurately predicted, and predictive values. Quantitative definitions comprise correlation/regression (r) and meta-analyses (percentage overlap of 95% confidence intervals). Translational success rates ranged from 0 to 100%.
CONCLUSION
The wide range of translational success rates observed in our study might indicate that translational success is unpredictable; i.e. it might be unclear upfront if the results of primary animal studies will contribute to translational knowledge. However, the risk of bias of the included studies was high, and much of the included evidence is old, while newer models have become available. Therefore, the reliability of the cumulative evidence from current papers on this topic is insufficient. Further in-depth "umbrella"-studies of translational success rates are still warranted. These are needed to evaluate the probabilistic evidence for predictivity of animal studies for the human situation more reliably, and to determine which factors affect this process.
Topics: Animals; Humans; Periodicals as Topic; Publication Bias; Risk; Translational Research, Biomedical
PubMed: 31307492
DOI: 10.1186/s12967-019-1976-2 -
Stroke Research and Treatment 2021This review aimed at figuring out the risk factors of uncontrolled hypertension in stroke. (Review)
Review
OBJECTIVE
This review aimed at figuring out the risk factors of uncontrolled hypertension in stroke.
METHOD
This study systematically analyzed the hypertension risk factors available in the ProQuest, EBSCO, and PubMed databases published between 2010 and December 2019. The risk factors' pooled odds ratio (POR) included in this research was calculated using both fixed and random-effect models. The meta-data analysis was processed using the Review Manager 5.3 (Rev Man 5.3).
RESULT
Of 1868 articles, seven studies were included in this review searched using specific keywords. Based on the analysis results, there were 7 risk factors of uncontrolled hypertension in stroke: medication nonadherence (POR = 2.23 [95% CI 1.71-2.89], = 0.342; = 6.7%), use of antihypertensive drugs (POR = 1.13 [95% CI 1.19-1.59, = 0.001; = 90.9%), stage of hypertension (POR = 1.14 [95% CI 1.02-1.27], = <0.001; = 97.1%), diabetes mellitus (POR = 0.71 [95% CI 0.52-0.99], = <0.001; = 96.5%), atrial fibrillation (POR = 1.74 [95% CI 1.48-2.04)], = <0.001; = 93.1%), triglycerides (POR = 1.47 [95% CI 1.23-1.75], = 0.879; = 0%), and age (POR = 1.03 [95% CI 0.89-1.18], = <0.001; = 97.5%]. There were no bias publications among studies. Medication nonadherence and triglycerides had homogeneous variations, while the others had heterogeneous variations.
CONCLUSION
Medication nonadherence, triglycerides, stage of hypertension, atrial fibrillation, and use of antihypertensive drugs significantly affect the uncontrolled hypertension in stroke.
PubMed: 33680423
DOI: 10.1155/2021/6683256