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Deep learning (DL) algorithms used for DOTATATE PET lesion detection typically require large, well-annotated training datasets. These are difficult to obtain due to low incidence of gastroenteropancreatic neuroendocrine tumors (GEP-NETs) and the high cost of manual annotation. Furthermore, networks trained and tested with data acquired from site specific PET/CT instrumentation, acquisition and processing protocols have reduced performance when tested with offsite data. This lack of generalizability requires even larger, more diverse training datasets. The objective of this study is to investigate the feasibility of improving DL algorithm performance by better matching the background noise in training datasets to higher noise, out-of-domain testing datasets. 68Ga-DOTATATE PET/CT datasets were obtained from two scanners: Scanner1, a state-of-the-art digital PET/CT (GE DMI PET/CT; n = 83 subjects), and Scanner2, an older-generation analog PET/CT (GE STE; n = 123 subjects). Set1, the data set from Scanner1, was reconstructed with standard clinical parameters (5 min; Q.Clear) and list-mode reconstructions (VPFXS 2, 3, 4, and 5-min). Set2, data from Scanner2 representing out-of-domain clinical scans, used standard iterative reconstruction (5 min; OSEM). A deep neural network was trained with each dataset: Network1 for Scanner1 and Network2 for Scanner2. DL performance (Network1) was tested with out-of-domain test data (Set2). To evaluate the effect of training sample size, we tested DL model performance using a fraction (25%, 50% and 75%) of Set1 for training. Scanner1, list-mode 2-min reconstructed data demonstrated the most similar noise level compared that of Set2, resulting in the best performance (F1 = 0.713). This was not significantly different compared to the highest performance, upper-bound limit using in-domain training for Network2 (F1 = 0.755; p-value = 0.103). Regarding sample size, the F1 score significantly increased from 25% training data (F1 = 0.478) to 100% training data (F1 = 0.713; p < 0.001). List-mode data from modern PET scanners can be reconstructed to better match the noise properties of older scanners. Using existing data and their associated annotations dramatically reduces the cost and effort in generating these datasets and significantly improves the performance of existing DL algorithms. List-mode reconstructions can provide an efficient, low-cost method to improve DL algorithm generalizability.
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SARS-CoV-2's rapid global spread caused the declaration of COVID-19 as a pandemic in March 2020. Alongside humans, domestic dogs and cats are also susceptible to infection. However, limited reports on pet infections in Chile prompted a comprehensive study to address this knowledge gap. Between March 2021 and March 2023, the study assessed 65 pets (26 dogs and 39 cats) from 33 COVID-19+ households alongside 700 nasal swabs from animals in households with unknown COVID-19 status. Using RT-PCR, nasal, fecal, and environmental samples were analyzed for the virus. In COVID-19+ households, 6.06% tested positive for SARS-CoV-2, belonging to 3 dogs, indicating human-to-pet transmission. Pets from households with unknown COVID-19 status tested negative for the virus. We obtained 2 SARS-CoV-2 genomes from animals, that belonged to Omicron BA.4.1 variant, marking the first report of pets infected with this lineage globally. Phylogenetic analysis showed these sequences clustered with human sequences collected in Chile during the same period when the BA.4.1 variant was prevalent in the country. The prevalence of SARS-CoV-2 in Chilean pets was relatively low, likely due to the country's high human vaccination rate. Our study highlights the importance of upholding and strengthening human vaccination strategies to mitigate the risk of interspecies transmission. It underscores the critical role of the One Health approach in addressing emerging zoonotic diseases, calling for further research on infection dynamics and risk factors for a comprehensive understanding.
Assuntos
COVID-19 , Doenças do Gato , Doenças do Cão , Humanos , Animais , Gatos , Cães , Chile/epidemiologia , Doenças do Cão/epidemiologia , Filogenia , COVID-19/epidemiologia , COVID-19/veterinária , SARS-CoV-2/genética , Animais de EstimaçãoRESUMO
Advancing biomedical research in low and middle income countries (LMICs) to expand the capacity for LMICs to integrate biomedical research into their health care systems and education has been the focus of many programs in global health over the past two decades. Central to the success of these programs is effective research mentoring, characterized by academic, career and psychosocial support through culturally appropriate practices. Research mentoring is a learned skill, developed through training, mutual discussions, practice and feedback. The majority of extant training programs are designed and delivered by US partners, so the next stage in building capacity is to train facilitators within the LMIC partner institutions to contextualize and advance mentoring specifically within their cultural and institutional norms by co-developing, delivering and evaluating semi-annual research mentoring training. To this end, we describe the development, delivery and outcome evaluation of a 5-week course in the art and skill of facilitation. Care was taken to explicitly distinguish between concepts of "teaching" and "facilitation," since "teaching" is closely connected to a transmission or banking model of education, which is characterized by "top-down," hierarchical relationship. The course discussed power and positionality, themes that resonate with partners in Nigeria and Tanzania. These themes provided unique entry into deeper conversations core to advancing mentoring practice away from the traditional dyadic power structure that remains from colonization. Evaluation findings indicate significant advances in awareness of differences between teaching and facilitating, increased confidence in facilitation skills, especially in the area of structured planning and organization, as well as improved communication and interpersonal skills. All respondents felt that students in Nigeria and Tanzania would respond well to the facilitation approach conveyed during the course and they found value in participating in the course as a cohort.
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This study was done to assess the age-specific incidence of admission for acute myocardial infarction in Antigua and Barbuda from 1990 to 2001. A retrospective review of Intensive Care Unit admissions for possible acute myocardial infarction was performed. Data obtained included age, gender, country of residence, electrocardiogram, creatine kinase results and intensive care unit outcome. There were, 250 admissions, 194 (78%) having data available for review. Acute myocardial infarction was found in 107/194 (55.2%) patients, age 59.9 +/- 13.7 years, 28% female, 70% from Antigua and Barbuda, 90/107 (85%) were between 35 and 75 years old. The incidence would be 7.5 per year or 9.7 per year if the confirmation rate documented was similar for all admissions. With a yearly population of 9555 men age 35 to 75 years in Antigua and Barbuda, with men accounting for 72% of acute myocardial infarctions, the incidence rate was 0.57 (confirmed) to 0.73 (all admissions) per year per 1000 men. For women, the yearly population was 10822 age 35 to 75 years, and the incidence rate was 0.19 to 0.24 per year per 1000 women. The mortality rate was 12/107 (11.2%), with women being older (67 vs 57 years, p = 0.001) and dying more often (17% vs 9%) compared with men. The mortality rate in the Intensive Care Unit was 0.07 per year for men, 0.04 per year for women per 1000 aged 35 to 75 years. In the United States of America (USA), the admission rate is 4.1 for men and 1.8 for women per year per 1000 aged 35 to 75 years; the mortality rate is 1.0 for men and 0.5 for women per year per 1000 aged 35 to 75 years. Rates of admission to the Intensive Care Unit for acute myocardial infarction in Antigua and Barbuda are 20%, and mortality rates are 10% of those reported in the USA.
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Adulto , Idoso , Idoso de 80 Anos ou mais , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Hospitalização/estatística & dados numéricos , Infarto do Miocárdio/epidemiologia , Unidades de Terapia Intensiva/estatística & dados numéricos , Antígua e Barbuda/epidemiologia , Doença da Artéria Coronariana/epidemiologia , Doença Aguda , Doenças Cardiovasculares , Estudos Retrospectivos , Fatores Etários , Fatores de Risco , Incidência , Prevalência , Unidades de Terapia IntensivaRESUMO
Between January 1990 and May 1995, 117 patients were admitted to the Intentsive Care at Holberton Hospital, Antigua, for chest pain due to suspected acute myocardial infarction. 39 (45 percent) of 86 patients whose records were available for retrospective review had confirmed (27 patients) or probable (12 patients) acute myocardial infarction. Risk factors identified among the patients included hypertension, diabetes, tobacco smoking, hypercholesterolaemia and obesity. On admission, 82 percent were Killip class I and 18 percent were Killip class II. Medications in the Intensive Care Unit included nitrates, aspirin, calcium and channel blockers, beta-adrenergic blockers, heparin and angiotensin converting enzyme inhibitors (21 percent). No thrombolytic agents were available. THe average hospital stay was 10 days and the in-hospital mortality rate was 13 percent. These data indicate that early mortality from acute myocardial infarction can be reduced in developing countries by early admission to an Intensive Care Unit and use of drugs known to be effective in its treatment.(AU)
Assuntos
Adulto , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Infarto do Miocárdio/mortalidade , Mortalidade Hospitalar , Antígua e Barbuda/epidemiologia , Unidades de Terapia Intensiva , Dor no Peito/etiologia , Dor no Peito/terapiaRESUMO
Between January 1990 and May 1995, 117 patients were admitted to the Intentsive Care at Holberton Hospital, Antigua, for chest pain due to suspected acute myocardial infarction. 39 (45 percent) of 86 patients whose records were available for retrospective review had confirmed (27 patients) or probable (12 patients) acute myocardial infarction. Risk factors identified among the patients included hypertension, diabetes, tobacco smoking, hypercholesterolaemia and obesity. On admission, 82 percent were Killip class I and 18 percent were Killip class II. Medications in the Intensive Care Unit included nitrates, aspirin, calcium and channel blockers, beta-adrenergic blockers, heparin and angiotensin converting enzyme inhibitors (21 percent). No thrombolytic agents were available. THe average hospital stay was 10 days and the in-hospital mortality rate was 13 percent. These data indicate that early mortality from acute myocardial infarction can be reduced in developing countries by early admission to an Intensive Care Unit and use of drugs known to be effective in its treatment.