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[PMID]:29386436
[Au] Autor:Komada F
[Ad] Endereço:Faculty of Pharmaceutical Sciences, Himeji Dokkyo University.
[Ti] Título:[Analysis of Time-to-onset of Interstitial Lung Disease after the Administration of Small Molecule Molecularly-targeted Drugs].
[So] Source:Yakugaku Zasshi;138(2):229-235, 2018.
[Is] ISSN:1347-5231
[Cp] País de publicação:Japan
[La] Idioma:jpn
[Ab] Resumo: The aim of this study was to investigate the time-to-onset of drug-induced interstitial lung disease (DILD) following the administration of small molecule molecularly-targeted drugs via the use of the spontaneous adverse reaction reporting system of the Japanese Adverse Drug Event Report database. DILD datasets for afatinib, alectinib, bortezomib, crizotinib, dasatinib, erlotinib, everolimus, gefitinib, imatinib, lapatinib, nilotinib, osimertinib, sorafenib, sunitinib, temsirolimus, and tofacitinib were used to calculate the median onset times of DILD and the Weibull distribution parameters, and to perform the hierarchical cluster analysis. The median onset times of DILD for afatinib, bortezomib, crizotinib, erlotinib, gefitinib, and nilotinib were within one month. The median onset times of DILD for dasatinib, everolimus, lapatinib, osimertinib, and temsirolimus ranged from 1 to 2 months. The median onset times of the DILD for alectinib, imatinib, and tofacitinib ranged from 2 to 3 months. The median onset times of the DILD for sunitinib and sorafenib ranged from 8 to 9 months. Weibull distributions for these drugs when using the cluster analysis showed that there were 4 clusters. Cluster 1 described a subgroup with early to later onset DILD and early failure type profiles or a random failure type profile. Cluster 2 exhibited early failure type profiles or a random failure type profile with early onset DILD. Cluster 3 exhibited a random failure type profile or wear out failure type profiles with later onset DILD. Cluster 4 exhibited an early failure type profile or a random failure type profile with the latest onset DILD.
[Mh] Termos MeSH primário: Sistemas de Notificação de Reações Adversas a Medicamentos
Bortezomib/efeitos adversos
Carbazóis/efeitos adversos
Bases de Dados como Assunto
Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/epidemiologia
Doenças Pulmonares Intersticiais/induzido quimicamente
Piperidinas/efeitos adversos
Quinazolinas/efeitos adversos
[Mh] Termos MeSH secundário: Análise por Conglomerados
Dasatinibe/efeitos adversos
Conjuntos de Dados como Assunto
Seres Humanos
Japão/epidemiologia
Doenças Pulmonares Intersticiais/epidemiologia
Terapia de Alvo Molecular/efeitos adversos
Tamanho da Partícula
Pirazóis/efeitos adversos
Piridinas/efeitos adversos
Fatores de Tempo
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Nm] Nome de substância:
0 (CH5424802); 0 (Carbazoles); 0 (Piperidines); 0 (Pyrazoles); 0 (Pyridines); 0 (Quinazolines); 41UD74L59M (afatinib); 53AH36668S (crizotinib); 69G8BD63PP (Bortezomib); RBZ1571X5H (Dasatinib)
[Em] Mês de entrada:1802
[Cu] Atualização por classe:180228
[Lr] Data última revisão:
180228
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:180202
[St] Status:MEDLINE
[do] DOI:10.1248/yakushi.17-00194


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[PMID]:29386432
[Au] Autor:Uesawa Y
[Ad] Endereço:Department of Clinical Pharmaceutics, Meiji Pharmaceutical University.
[Ti] Título:[Adverse Effect Predictions Based on Computational Toxicology Techniques and Large-scale Databases].
[So] Source:Yakugaku Zasshi;138(2):185-190, 2018.
[Is] ISSN:1347-5231
[Cp] País de publicação:Japan
[La] Idioma:jpn
[Ab] Resumo: Understanding the features of chemical structures related to the adverse effects of drugs is useful for identifying potential adverse effects of new drugs. This can be based on the limited information available from post-marketing surveillance, assessment of the potential toxicities of metabolites and illegal drugs with unclear characteristics, screening of lead compounds at the drug discovery stage, and identification of leads for the discovery of new pharmacological mechanisms. This present paper describes techniques used in computational toxicology to investigate the content of large-scale spontaneous report databases of adverse effects, and it is illustrated with examples. Furthermore, volcano plotting, a new visualization method for clarifying the relationships between drugs and adverse effects via comprehensive analyses, will be introduced. These analyses may produce a great amount of data that can be applied to drug repositioning.
[Mh] Termos MeSH primário: Sistemas de Notificação de Reações Adversas a Medicamentos
Computadores
Bases de Dados como Assunto
Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos
Toxicologia/métodos
[Mh] Termos MeSH secundário: Reposicionamento de Medicamentos
Valor Preditivo dos Testes
Vigilância de Produtos Comercializados
Relação Estrutura-Atividade
[Pt] Tipo de publicação:JOURNAL ARTICLE; REVIEW
[Em] Mês de entrada:1802
[Cu] Atualização por classe:180228
[Lr] Data última revisão:
180228
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:180202
[St] Status:MEDLINE
[do] DOI:10.1248/yakushi.17-00174-4


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[PMID]:29261782
[Au] Autor:Boonstra TW; Larsen ME; Townsend S; Christensen H
[Ad] Endereço:Black Dog Institute, University of New South Wales, Sydney, Australia.
[Ti] Título:Validation of a smartphone app to map social networks of proximity.
[So] Source:PLoS One;12(12):e0189877, 2017.
[Is] ISSN:1932-6203
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:Social network analysis is a prominent approach to investigate interpersonal relationships. Most studies use self-report data to quantify the connections between participants and construct social networks. In recent years smartphones have been used as an alternative to map networks by assessing the proximity between participants based on Bluetooth and GPS data. While most studies have handed out specially programmed smartphones to study participants, we developed an application for iOS and Android to collect Bluetooth data from participants' own smartphones. In this study, we compared the networks estimated with the smartphone app to those obtained from sociometric badges and self-report data. Participants (n = 21) installed the app on their phone and wore a sociometric badge during office hours. Proximity data was collected for 4 weeks. A contingency table revealed a significant association between proximity data (Ï• = 0.17, p<0.0001), but the marginal odds were higher for the app (8.6%) than for the badges (1.3%), indicating that dyads were more often detected by the app. We then compared the networks that were estimated using the proximity and self-report data. All three networks were significantly correlated, although the correlation with self-reported data was lower for the app (ρ = 0.25) than for badges (ρ = 0.67). The scanning rates of the app varied considerably between devices and was lower on iOS than on Android. The association between the app and the badges increased when the network was estimated between participants whose app recorded more regularly. These findings suggest that the accuracy of proximity networks can be further improved by reducing missing data and restricting the interpersonal distance at which interactions are detected.
[Mh] Termos MeSH primário: Aplicativos Móveis
Smartphone
Apoio Social
[Mh] Termos MeSH secundário: Bases de Dados como Assunto
Seres Humanos
Inquéritos e Questionários
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Em] Mês de entrada:1801
[Cu] Atualização por classe:180108
[Lr] Data última revisão:
180108
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:171221
[St] Status:MEDLINE
[do] DOI:10.1371/journal.pone.0189877


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[PMID]:29261781
[Au] Autor:Perez-Riverol Y; Kuhn M; Vizcaíno JA; Hitz MP; Audain E
[Ad] Endereço:European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom.
[Ti] Título:Accurate and fast feature selection workflow for high-dimensional omics data.
[So] Source:PLoS One;12(12):e0189875, 2017.
[Is] ISSN:1932-6203
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:We are moving into the age of 'Big Data' in biomedical research and bioinformatics. This trend could be encapsulated in this simple formula: D = S * F, where the volume of data generated (D) increases in both dimensions: the number of samples (S) and the number of sample features (F). Frequently, a typical omics classification includes redundant and irrelevant features (e.g. genes or proteins) that can result in long computation times; decrease of the model performance and the selection of suboptimal features (genes and proteins) after the classification/regression step. Multiple algorithms and reviews has been published to describe all the existing methods for feature selection, their strengths and weakness. However, the selection of the correct FS algorithm and strategy constitutes an enormous challenge. Despite the number and diversity of algorithms available, the proper choice of an approach for facing a specific problem often falls in a 'grey zone'. In this study, we select a subset of FS methods to develop an efficient workflow and an R package for bioinformatics machine learning problems. We cover relevant issues concerning FS, ranging from domain's problems to algorithm solutions and computational tools. Finally, we use seven different proteomics and gene expression datasets to evaluate the workflow and guide the FS process.
[Mh] Termos MeSH primário: Algoritmos
Bases de Dados como Assunto
Genômica/métodos
Fluxo de Trabalho
[Mh] Termos MeSH secundário: Seres Humanos
Análise Multivariada
Análise de Componente Principal
Máquina de Vetores de Suporte
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Em] Mês de entrada:1801
[Cu] Atualização por classe:180108
[Lr] Data última revisão:
180108
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:171221
[St] Status:MEDLINE
[do] DOI:10.1371/journal.pone.0189875


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[PMID]:29176802
[Au] Autor:Andrés-Blanco AM; Álvarez D; Crespo A; Arroyo CA; Cerezo-Hernández A; Gutiérrez-Tobal GC; Hornero R; Del Campo F
[Ad] Endereço:Pneumology Service, Río Hortega University Hospital, Valladolid, Spain.
[Ti] Título:Assessment of automated analysis of portable oximetry as a screening test for moderate-to-severe sleep apnea in patients with chronic obstructive pulmonary disease.
[So] Source:PLoS One;12(11):e0188094, 2017.
[Is] ISSN:1932-6203
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:BACKGROUND: The coexistence of obstructive sleep apnea syndrome (OSAS) and chronic obstructive pulmonary disease (COPD) leads to increased morbidity and mortality. The development of home-based screening tests is essential to expedite diagnosis. Nevertheless, there is still very limited evidence on the effectiveness of portable monitoring to diagnose OSAS in patients with pulmonary comorbidities. OBJECTIVE: To assess the influence of suffering from COPD in the performance of an oximetry-based screening test for moderate-to-severe OSAS, both in the hospital and at home. METHODS: A total of 407 patients showing moderate-to-high clinical suspicion of OSAS were involved in the study. All subjects underwent (i) supervised portable oximetry simultaneously to in-hospital polysomnography (PSG) and (ii) unsupervised portable oximetry at home. A regression-based multilayer perceptron (MLP) artificial neural network (ANN) was trained to estimate the apnea-hypopnea index (AHI) from portable oximetry recordings. Two independent validation datasets were analyzed: COPD versus non-COPD. RESULTS: The portable oximetry-based MLP ANN reached similar intra-class correlation coefficient (ICC) values between the estimated AHI and the actual AHI for the non-COPD and the COPD groups either in the hospital (non-COPD: 0.937, 0.909-0.956 CI95%; COPD: 0.936, 0.899-0.960 CI95%) and at home (non-COPD: 0.731, 0.631-0.808 CI95%; COPD: 0.788, 0.678-0.864 CI95%). Regarding the area under the receiver operating characteristics curve (AUC), no statistically significant differences (p >0.01) between COPD and non-COPD groups were found in both settings, particularly for severe OSAS (AHI ≥30 events/h): 0.97 (0.92-0.99 CI95%) non-COPD vs. 0.98 (0.92-1.0 CI95%) COPD in the hospital, and 0.87 (0.79-0.92 CI95%) non-COPD vs. 0.86 (0.75-0.93 CI95%) COPD at home. CONCLUSION: The agreement and the diagnostic performance of the estimated AHI from automated analysis of portable oximetry were similar regardless of the presence of COPD both in-lab and at-home. Particularly, portable oximetry could be used as an abbreviated screening test for moderate-to-severe OSAS in patients with COPD.
[Mh] Termos MeSH primário: Programas de Rastreamento
Oximetria/métodos
Doença Pulmonar Obstrutiva Crônica/complicações
Doença Pulmonar Obstrutiva Crônica/diagnóstico
Síndromes da Apneia do Sono/complicações
Síndromes da Apneia do Sono/diagnóstico
[Mh] Termos MeSH secundário: Automação
Bases de Dados como Assunto
Demografia
Feminino
Seres Humanos
Masculino
Meia-Idade
Redes Neurais (Computação)
Polissonografia
Curva ROC
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Em] Mês de entrada:1712
[Cu] Atualização por classe:171219
[Lr] Data última revisão:
171219
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:171128
[St] Status:MEDLINE
[do] DOI:10.1371/journal.pone.0188094


  6 / 8665 MEDLINE  
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[PMID]:29069555
[Au] Autor:Blumcke I; Spreafico R; Haaker G; Coras R; Kobow K; Bien CG; Pfäfflin M; Elger C; Widman G; Schramm J; Becker A; Braun KP; Leijten F; Baayen JC; Aronica E; Chassoux F; Hamer H; Stefan H; Rössler K; Thom M; Walker MC; Sisodiya SM; Duncan JS; McEvoy AW; Pieper T; Holthausen H; Kudernatsch M; Meencke HJ; Kahane P; Schulze-Bonhage A; Zentner J; Heiland DH; Urbach H; Steinhoff BJ; Bast T; Tassi L; Lo Russo G; Özkara C; Oz B; Krsek P; Vogelgesang S; Runge U; Lerche H; Weber Y; Honavar M; Pimentel J; Arzimanoglou A; Ulate-Campos A; Noachtar S; Hartl E; EEBB Consortium
[Ad] Endereço:From the Departments of Neuropathology (I.B., G.H., R.C., K.K.) and Neurosurgery (K.R.) and the Epilepsy Center (H. Hamer, H.S.), University Hospital Erlangen, Erlangen, the Epilepsy Center Bethel, Krankenhaus Mara, Bielefeld (C.G.B., M.P.), the Departments of Epileptology (C.E., G.W.) and Neuropath
[Ti] Título:Histopathological Findings in Brain Tissue Obtained during Epilepsy Surgery.
[So] Source:N Engl J Med;377(17):1648-1656, 2017 10 26.
[Is] ISSN:1533-4406
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:BACKGROUND: Detailed neuropathological information on the structural brain lesions underlying seizures is valuable for understanding drug-resistant focal epilepsy. METHODS: We report the diagnoses made on the basis of resected brain specimens from 9523 patients who underwent epilepsy surgery for drug-resistant seizures in 36 centers from 12 European countries over 25 years. Histopathological diagnoses were determined through examination of the specimens in local hospitals (41%) or at the German Neuropathology Reference Center for Epilepsy Surgery (59%). RESULTS: The onset of seizures occurred before 18 years of age in 75.9% of patients overall, and 72.5% of the patients underwent surgery as adults. The mean duration of epilepsy before surgical resection was 20.1 years among adults and 5.3 years among children. The temporal lobe was involved in 71.9% of operations. There were 36 histopathological diagnoses in seven major disease categories. The most common categories were hippocampal sclerosis, found in 36.4% of the patients (88.7% of cases were in adults), tumors (mainly ganglioglioma) in 23.6%, and malformations of cortical development in 19.8% (focal cortical dysplasia was the most common type, 52.7% of cases of which were in children). No histopathological diagnosis could be established for 7.7% of the patients. CONCLUSIONS: In patients with drug-resistant focal epilepsy requiring surgery, hippocampal sclerosis was the most common histopathological diagnosis among adults, and focal cortical dysplasia was the most common diagnosis among children. Tumors were the second most common lesion in both groups. (Funded by the European Union and others.).
[Mh] Termos MeSH primário: Neoplasias Encefálicas/patologia
Encéfalo/patologia
Epilepsia/patologia
Hipocampo/patologia
Malformações do Desenvolvimento Cortical/patologia
[Mh] Termos MeSH secundário: Adulto
Fatores Etários
Idade de Início
Neoplasias Encefálicas/complicações
Criança
Bases de Dados como Assunto
Epilepsia/etiologia
Epilepsia/cirurgia
Europa (Continente)
Feminino
Seres Humanos
Masculino
Malformações do Desenvolvimento Cortical/complicações
Lobo Temporal/patologia
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Em] Mês de entrada:1711
[Cu] Atualização por classe:171107
[Lr] Data última revisão:
171107
[Sb] Subgrupo de revista:AIM; IM
[Da] Data de entrada para processamento:171026
[St] Status:MEDLINE
[do] DOI:10.1056/NEJMoa1703784


  7 / 8665 MEDLINE  
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[PMID]:28880923
[Au] Autor:Zdravevski E; Risteska Stojkoska B; Standl M; Schulz H
[Ad] Endereço:Faculty of Computer Science and Engineering, Saints Cyril and Methodius University, Skopje, Macedonia.
[Ti] Título:Automatic machine-learning based identification of jogging periods from accelerometer measurements of adolescents under field conditions.
[So] Source:PLoS One;12(9):e0184216, 2017.
[Is] ISSN:1932-6203
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:BACKGROUND: Assessment of health benefits associated with physical activity depend on the activity duration, intensity and frequency, therefore their correct identification is very valuable and important in epidemiological and clinical studies. The aims of this study are: to develop an algorithm for automatic identification of intended jogging periods; and to assess whether the identification performance is improved when using two accelerometers at the hip and ankle, compared to when using only one at either position. METHODS: The study used diarized jogging periods and the corresponding accelerometer data from thirty-nine, 15-year-old adolescents, collected under field conditions, as part of the GINIplus study. The data was obtained from two accelerometers placed at the hip and ankle. Automated feature engineering technique was performed to extract features from the raw accelerometer readings and to select a subset of the most significant features. Four machine learning algorithms were used for classification: Logistic regression, Support Vector Machines, Random Forest and Extremely Randomized Trees. Classification was performed using only data from the hip accelerometer, using only data from ankle accelerometer and using data from both accelerometers. RESULTS: The reported jogging periods were verified by visual inspection and used as golden standard. After the feature selection and tuning of the classification algorithms, all options provided a classification accuracy of at least 0.99, independent of the applied segmentation strategy with sliding windows of either 60s or 180s. The best matching ratio, i.e. the length of correctly identified jogging periods related to the total time including the missed ones, was up to 0.875. It could be additionally improved up to 0.967 by application of post-classification rules, which considered the duration of breaks and jogging periods. There was no obvious benefit of using two accelerometers, rather almost the same performance could be achieved from either accelerometer position. CONCLUSIONS: Machine learning techniques can be used for automatic activity recognition, as they provide very accurate activity recognition, significantly more accurate than when keeping a diary. Identification of jogging periods in adolescents can be performed using only one accelerometer. Performance-wise there is no significant benefit from using accelerometers on both locations.
[Mh] Termos MeSH primário: Acelerometria/instrumentação
Corrida Moderada/fisiologia
Aprendizado de Máquina
[Mh] Termos MeSH secundário: Adolescente
Algoritmos
Automação
Bases de Dados como Assunto
Seres Humanos
Modelos Teóricos
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Em] Mês de entrada:1710
[Cu] Atualização por classe:171016
[Lr] Data última revisão:
171016
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170908
[St] Status:MEDLINE
[do] DOI:10.1371/journal.pone.0184216


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[PMID]:28873436
[Au] Autor:Bass C; Helkkula P; De Paola V; Clopath C; Bharath AA
[Ad] Endereço:Centre for Neurotechnology, South Kensington Campus, Imperial College London, London, United Kingdom.
[Ti] Título:Detection of axonal synapses in 3D two-photon images.
[So] Source:PLoS One;12(9):e0183309, 2017.
[Is] ISSN:1932-6203
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:Studies of structural plasticity in the brain often require the detection and analysis of axonal synapses (boutons). To date, bouton detection has been largely manual or semi-automated, relying on a step that traces the axons before detection the boutons. If tracing the axon fails, the accuracy of bouton detection is compromised. In this paper, we propose a new algorithm that does not require tracing the axon to detect axonal boutons in 3D two-photon images taken from the mouse cortex. To find the most appropriate techniques for this task, we compared several well-known algorithms for interest point detection and feature descriptor generation. The final algorithm proposed has the following main steps: (1) a Laplacian of Gaussian (LoG) based feature enhancement module to accentuate the appearance of boutons; (2) a Speeded Up Robust Features (SURF) interest point detector to find candidate locations for feature extraction; (3) non-maximum suppression to eliminate candidates that were detected more than once in the same local region; (4) generation of feature descriptors based on Gabor filters; (5) a Support Vector Machine (SVM) classifier, trained on features from labelled data, and was used to distinguish between bouton and non-bouton candidates. We found that our method achieved a Recall of 95%, Precision of 76%, and F1 score of 84% within a new dataset that we make available for accessing bouton detection. On average, Recall and F1 score were significantly better than the current state-of-the-art method, while Precision was not significantly different. In conclusion, in this article we demonstrate that our approach, which is independent of axon tracing, can detect boutons to a high level of accuracy, and improves on the detection performance of existing approaches. The data and code (with an easy to use GUI) used in this article are available from open source repositories.
[Mh] Termos MeSH primário: Axônios/fisiologia
Imagem Tridimensional
Microscopia de Fluorescência por Excitação Multifotônica/métodos
Sinapses/fisiologia
[Mh] Termos MeSH secundário: Algoritmos
Animais
Bases de Dados como Assunto
Masculino
Camundongos Endogâmicos C57BL
Terminações Pré-Sinápticas/fisiologia
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Em] Mês de entrada:1710
[Cu] Atualização por classe:171016
[Lr] Data última revisão:
171016
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170906
[St] Status:MEDLINE
[do] DOI:10.1371/journal.pone.0183309


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[PMID]:28873413
[Au] Autor:Salt C; Morris PJ; German AJ; Wilson D; Lund EM; Cole TJ; Butterwick RF
[Ad] Endereço:WALTHAM Centre for Pet Nutrition, Mars Petcare, Waltham on the Wolds, Leicestershire, United Kingdom.
[Ti] Título:Growth standard charts for monitoring bodyweight in dogs of different sizes.
[So] Source:PLoS One;12(9):e0182064, 2017.
[Is] ISSN:1932-6203
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:Limited information is available on what constitutes optimal growth in dogs. The primary aim of this study was to develop evidence-based growth standards for dogs, using retrospective analysis of bodyweight and age data from >6 million young dogs attending a large corporate network of primary care veterinary hospitals across the USA. Electronic medical records were used to generate bodyweight data from immature client-owned dogs, that were healthy and had remained in ideal body condition throughout the first 3 years of life. Growth centile curves were constructed using Generalised Additive Models for Location, Shape and Scale. Curves were displayed graphically as centile charts covering the age range 12 weeks to 2 years. Over 100 growth charts were modelled, specific to different combinations of breed, sex and neuter status. Neutering before 37 weeks was associated with a slight upward shift in growth trajectory, whilst neutering after 37 weeks was associated with a slight downward shift in growth trajectory. However, these shifts were small in comparison to inter-individual variability amongst dogs, suggesting that separate curves for neutered dogs were not needed. Five bodyweight categories were created to cover breeds up to 40kg, using both visual assessment and hierarchical cluster analysis of breed-specific growth curves. For 20/24 of the individual breed centile curves, agreement with curves for the corresponding bodyweight categories was good. For the remaining 4 breed curves, occasional deviation across centile lines was observed, but overall agreement was acceptable. This suggested that growth could be described using size categories rather than requiring curves for specific breeds. In the current study, a series of evidence-based growth standards have been developed to facilitate charting of bodyweight in healthy dogs. Additional studies are required to validate these standards and create a clinical tool for growth monitoring in pet dogs.
[Mh] Termos MeSH primário: Tamanho Corporal
Peso Corporal
Cães/crescimento & desenvolvimento
Gráficos de Crescimento
[Mh] Termos MeSH secundário: Animais
Cruzamento
Análise por Conglomerados
Bases de Dados como Assunto
Crescimento e Desenvolvimento
Modelos Teóricos
[Pt] Tipo de publicação:JOURNAL ARTICLE; OBSERVATIONAL STUDY
[Em] Mês de entrada:1710
[Cu] Atualização por classe:171016
[Lr] Data última revisão:
171016
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170906
[St] Status:MEDLINE
[do] DOI:10.1371/journal.pone.0182064


  10 / 8665 MEDLINE  
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[PMID]:28814539
[Au] Autor:Sherman SL; Kidd SA; Riley C; Berry-Kravis E; Andrews HF; Miller RM; Lincoln S; Swanson M; Kaufmann WE; Brown WT
[Ad] Endereço:Department of Human Genetics, Emory University School of Medicine, Atlanta, Georgia; ssherma@emory.edu.
[Ti] Título:FORWARD: A Registry and Longitudinal Clinical Database to Study Fragile X Syndrome.
[So] Source:Pediatrics;139(Suppl 3):S183-S193, 2017 Jun.
[Is] ISSN:1098-4275
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:BACKGROUND AND OBJECTIVE: Advances in the care of patients with fragile X syndrome (FXS) have been hampered by lack of data. This deficiency has produced fragmentary knowledge regarding the natural history of this condition, healthcare needs, and the effects of the disease on caregivers. To remedy this deficiency, the Fragile X Clinic and Research Consortium was established to facilitate research. Through a collective effort, the Fragile X Clinic and Research Consortium developed the Fragile X Online Registry With Accessible Research Database (FORWARD) to facilitate multisite data collection. This report describes FORWARD and the way it can be used to improve health and quality of life of FXS patients and their relatives and caregivers. METHODS: FORWARD collects demographic information on individuals with FXS and their family members (affected and unaffected) through a 1-time registry form. The longitudinal database collects clinician- and parent-reported data on individuals diagnosed with FXS, focused on those who are 0 to 24 years of age, although individuals of any age can participate. RESULTS: The registry includes >2300 registrants (data collected September 7, 2009 to August 31, 2014). The longitudinal database includes data on 713 individuals diagnosed with FXS (data collected September 7, 2012 to August 31, 2014). Longitudinal data continue to be collected on enrolled patients along with baseline data on new patients. CONCLUSIONS: FORWARD represents the largest resource of clinical and demographic data for the FXS population in the United States. These data can be used to advance our understanding of FXS: the impact of cooccurring conditions, the impact on the day-to-day lives of individuals living with FXS and their families, and short-term and long-term outcomes.
[Mh] Termos MeSH primário: Bases de Dados como Assunto
Síndrome do Cromossomo X Frágil/diagnóstico
Síndrome do Cromossomo X Frágil/genética
Sistema de Registros
[Mh] Termos MeSH secundário: Atividades Cotidianas/psicologia
Adolescente
Adulto
Cuidadores/psicologia
Criança
Pré-Escolar
Feminino
Síndrome do Cromossomo X Frágil/psicologia
Síndrome do Cromossomo X Frágil/terapia
Seres Humanos
Lactente
Recém-Nascido
Estudos Longitudinais
Masculino
Estados Unidos
Adulto Jovem
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Em] Mês de entrada:1708
[Cu] Atualização por classe:171001
[Lr] Data última revisão:
171001
[Sb] Subgrupo de revista:AIM; IM
[Da] Data de entrada para processamento:170818
[St] Status:MEDLINE
[do] DOI:10.1542/peds.2016-1159E



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