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  • 1
    Online Resource
    Online Resource
    NEOTROPICAL CARNIVORES: a data set on carnivore distribution in the Neotropics
    Wiley ; 2020
    In:  Ecology Vol. 101, No. 11 ( 2020-11)
    Details
    In: Ecology, Wiley, Vol. 101, No. 11 ( 2020-11)
    Abstract: Mammalian carnivores are considered a key group in maintaining ecological health and can indicate potential ecological integrity in landscapes where they occur. Carnivores also hold high conservation value and their habitat requirements can guide management and conservation plans. The order Carnivora has 84 species from 8 families in the Neotropical region: Canidae; Felidae; Mephitidae; Mustelidae; Otariidae; Phocidae; Procyonidae; and Ursidae. Herein, we include published and unpublished data on native terrestrial Neotropical carnivores (Canidae; Felidae; Mephitidae; Mustelidae; Procyonidae; and Ursidae). NEOTROPICAL CARNIVORES is a publicly available data set that includes 99,605 data entries from 35,511 unique georeferenced coordinates. Detection/non‐detection and quantitative data were obtained from 1818 to 2018 by researchers, governmental agencies, non‐governmental organizations, and private consultants. Data were collected using several methods including camera trapping, museum collections, roadkill, line transect, and opportunistic records. Literature (peer‐reviewed and grey literature) from Portuguese, Spanish and English were incorporated in this compilation. Most of the data set consists of detection data entries (n = 79,343; 79.7%) but also includes non‐detection data (n = 20,262; 20.3%). Of those, 43.3% also include count data (n = 43,151). The information available in NEOTROPICAL CARNIVORES will contribute to macroecological, ecological, and conservation questions in multiple spatio‐temporal perspectives. As carnivores play key roles in trophic interactions, a better understanding of their distribution and habitat requirements are essential to establish conservation management plans and safeguard the future ecological health of Neotropical ecosystems. Our data paper, combined with other large‐scale data sets, has great potential to clarify species distribution and related ecological processes within the Neotropics. There are no copyright restrictions and no restriction for using data from this data paper, as long as the data paper is cited as the source of the information used. We also request that users inform us of how they intend to use the data.
    Type of Medium: Online Resource
    ISSN: 0012-9658 , 1939-9170
    URL: Issue
    URL: Article
    DOI: 10.1002/ecy.v101.11
    DOI: 10.1002/ecy.3128
    RVK:
    WA 15000
    Language: English
    Publisher: Wiley
    Publication Date: 2020
    detail.hit.zdb_id: 1797-8
    detail.hit.zdb_id: 2010140-5
    SSG: 12
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  • 2
    Online Resource
    Online Resource
    NEOTROPICAL ALIEN MAMMALS: a data set of occurrence and abundance of alien mammals in the Neotropics
    Wiley ; 2020
    In:  Ecology Vol. 101, No. 11 ( 2020-11)
    Details
    In: Ecology, Wiley, Vol. 101, No. 11 ( 2020-11)
    Abstract: Biological invasion is one of the main threats to native biodiversity. For a species to become invasive, it must be voluntarily or involuntarily introduced by humans into a nonnative habitat. Mammals were among first taxa to be introduced worldwide for game, meat, and labor, yet the number of species introduced in the Neotropics remains unknown. In this data set, we make available occurrence and abundance data on mammal species that (1) transposed a geographical barrier and (2) were voluntarily or involuntarily introduced by humans into the Neotropics. Our data set is composed of 73,738 historical and current georeferenced records on alien mammal species of which around 96% correspond to occurrence data on 77 species belonging to eight orders and 26 families. Data cover 26 continental countries in the Neotropics, ranging from Mexico and its frontier regions (southern Florida and coastal‐central Florida in the southeast United States) to Argentina, Paraguay, Chile, and Uruguay, and the 13 countries of Caribbean islands. Our data set also includes neotropical species (e.g., Callithrix sp., Myocastor coypus , Nasua nasua) considered alien in particular areas of Neotropics. The most numerous species in terms of records are from Bos sp. ( n = 37,782), Sus scrofa ( n = 6,730), and Canis familiaris ( n = 10,084); 17 species were represented by only one record (e.g., S yncerus caffer, Cervus timorensis, Cervus unicolor, Canis latrans ). Primates have the highest number of species in the data set ( n = 20 species), partly because of uncertainties regarding taxonomic identification of the genera Callithrix, which includes the species Callithrix aurita, Callithrix flaviceps, Callithrix geoffroyi, Callithrix jacchus, Callithrix kuhlii, Callithrix penicillata , and their hybrids. This unique data set will be a valuable source of information on invasion risk assessments, biodiversity redistribution and conservation‐related research. There are no copyright restrictions. Please cite this data paper when using the data in publications. We also request that researchers and teachers inform us on how they are using the data.
    Type of Medium: Online Resource
    ISSN: 0012-9658 , 1939-9170
    URL: Issue
    URL: Article
    DOI: 10.1002/ecy.v101.11
    DOI: 10.1002/ecy.3115
    RVK:
    WA 15000
    Language: English
    Publisher: Wiley
    Publication Date: 2020
    detail.hit.zdb_id: 1797-8
    detail.hit.zdb_id: 2010140-5
    SSG: 12
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  • 3
    Online Resource
    Online Resource
    NEOTROPICAL XENARTHRANS: a data set of occurrence of xenarthran species in the Neotropics
    Wiley ; 2019
    In:  Ecology Vol. 100, No. 7 ( 2019-07)
    Details
    In: Ecology, Wiley, Vol. 100, No. 7 ( 2019-07)
    Abstract: Xenarthrans—anteaters, sloths, and armadillos—have essential functions for ecosystem maintenance, such as insect control and nutrient cycling, playing key roles as ecosystem engineers. Because of habitat loss and fragmentation, hunting pressure, and conflicts with domestic dogs, these species have been threatened locally, regionally, or even across their full distribution ranges. The Neotropics harbor 21 species of armadillos, 10 anteaters, and 6 sloths. Our data set includes the families Chlamyphoridae (13), Dasypodidae (7), Myrmecophagidae (3), Bradypodidae (4), and Megalonychidae (2). We have no occurrence data on Dasypus pilosus (Dasypodidae). Regarding Cyclopedidae, until recently, only one species was recognized, but new genetic studies have revealed that the group is represented by seven species. In this data paper, we compiled a total of 42,528 records of 31 species, represented by occurrence and quantitative data, totaling 24,847 unique georeferenced records. The geographic range is from the southern United States, Mexico, and Caribbean countries at the northern portion of the Neotropics, to the austral distribution in Argentina, Paraguay, Chile, and Uruguay. Regarding anteaters, Myrmecophaga tridactyla has the most records ( n  = 5,941), and Cyclopes sp. have the fewest ( n  = 240). The armadillo species with the most data is Dasypus novemcinctus ( n  = 11,588), and the fewest data are recorded for Calyptophractus retusus ( n  = 33). With regard to sloth species, Bradypus variegatus has the most records ( n  = 962), and Bradypus pygmaeus has the fewest ( n  = 12). Our main objective with Neotropical Xenarthrans is to make occurrence and quantitative data available to facilitate more ecological research, particularly if we integrate the xenarthran data with other data sets of Neotropical Series that will become available very soon (i.e., Neotropical Carnivores, Neotropical Invasive Mammals, and Neotropical Hunters and Dogs). Therefore, studies on trophic cascades, hunting pressure, habitat loss, fragmentation effects, species invasion, and climate change effects will be possible with the Neotropical Xenarthrans data set. Please cite this data paper when using its data in publications. We also request that researchers and teachers inform us of how they are using these data.
    Type of Medium: Online Resource
    ISSN: 0012-9658 , 1939-9170
    URL: Issue
    URL: Article
    DOI: 10.1002/ecy.2019.100.issue-7
    DOI: 10.1002/ecy.2663
    RVK:
    WA 15000
    Language: English
    Publisher: Wiley
    Publication Date: 2019
    detail.hit.zdb_id: 1797-8
    detail.hit.zdb_id: 2010140-5
    SSG: 12
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  • 4
    Online Resource
    Online Resource
    Camera trap surveys of A tlantic F orest mammals: A data set for analyses considering imperfect detection (2004–2020)
    Wiley ; 2024
    In:  Ecology
    Details
    In: Ecology, Wiley
    Abstract: As armadilhas fotográficas tornaram‐se o principal método de observação de muitas espécies em grandes áreas. Os dados obtidos com armadilhas fotográficas podem ser usados para descrever os padrões e monitorar a ocupação, abundância e riqueza da vida selvagem, informação essencial para a conservação em tempos de rápidas mudanças climáticas e de cobertura do solo. A perda de habitat e a caça furtiva são responsáveis pelas perdas populacionais históricas de mamíferos no hotspot de biodiversidade da Mata Atlântica, especialmente para espécies de médio e grande porte. Aqui apresentamos um conjunto de dados de levantamentos com armadilhas fotográficas de mamíferos de médio e grande porte ( 〉 1 kg) em toda a Mata Atlântica. Compilamos dados de 5.380 armadilhas fotográficas instaladas no nível do chão em 3.046 locais, de 2004 a 2020, resultando em 43.068 registros de 58 espécies. Esses dados acrescentam aos conjuntos de dados existentes de mamíferos na Mata Atlântica por incluir as datas de operação das câmeras, que são necessárias para análises que lidam com detecção imperfeita. Também incluímos, quando disponíveis, informações sobre importantes preditores de detecção, como marca e modelo da câmera, uso de isca e obstrução do visor da câmera que pode ser medido a partir de imagens de exemplo em cada local da câmera. Além de estudos sobre os padrões e mecanismos por trás da ocupação, abundância relativa, riqueza e detecção, o conjunto de dados aqui apresentado pode ser usado para estudar os padrões de atividade diária das espécies, nível de atividade e interações espaço‐temporais entre as espécies. Além disso, os dados podem ser usados em combinação com outras fontes de dados em diversas análises com modelagem populacional integrada. Um script R está disponível para visualizar um resumo do conjunto de dados. Esperamos que este conjunto de dados seja usado para aumentar o conhecimento sobre as assembleias de mamíferos e usado para informar soluções baseadas em evidências para a conservação da Mata Atlântica. Os dados não são restritos por direitos autorais e, por favor, cite este documento ao usar os dados.
    Type of Medium: Online Resource
    ISSN: 0012-9658 , 1939-9170
    URL: Article
    DOI: 10.1002/ecy.4298
    RVK:
    WA 15000
    Language: English
    Publisher: Wiley
    Publication Date: 2024
    detail.hit.zdb_id: 1797-8
    detail.hit.zdb_id: 2010140-5
    SSG: 12
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  • 5
    Online Resource
    Online Resource
    893. Occurrence’s Prediction of Surgical Site Infection in Limb Amputation Surgery
    Oxford University Press (OUP) ; 2020
    In:  Open Forum Infectious Diseases Vol. 7, No. Supplement_1 ( 2020-12-31), p. S481-S481
    Details
    In: Open Forum Infectious Diseases, Oxford University Press (OUP), Vol. 7, No. Supplement_1 ( 2020-12-31), p. S481-S481
    Abstract: A research was conducted between July 2016 and June 2018 in five hospitals in Belo Horizonte, a city of 3,000,000 inhabitants, focused on surgical site infection (SSI) in patients undergoing limb amputation surgery procedure. The main objective is to statistically evaluate such incidences and enable a study of the prediction power of SSI through MLPs (Multilayer Perceptron), a pattern recognition algorithm. Methods Data were collected on SSI by the Hospital Infection Control Committees (CCIH) of the hospitals involved. The information was forwarded to the NOIS (Nosocomial Infection Study) Project. After data collection, three procedures were performed: a treatment of the database collected for the use of intact samples; a statistical analysis on the profile of the hospitals collected and; an assessment of the predictive power of five types of MLP (Backpropagation Standard, Momentum, Resilient Propagation, Weight Decay, and Quick Propagation) for SSI prediction. MLPs were tested with 3, 5, 7, and 10 hidden layer neurons and a database split for the resampling process (65% or 75% for testing, 35% or 25% for validation). They were compared by measuring AUC (Area Under the Curve - ranging from 0 to 1) presented for each of the configurations. Results From 969 data, only 507 were intact for analysis. Statistically: in 12.45% there was an incidence of global infection and that in 10.67% of the cases were SSI (among which, 94.6% had to be hospitalized for more than 10 days); patients were hospitalized on average 21 days (from 0 to 141 days); the average duration is 78 minutes (maximum 360 minutes); 53 deaths (a 16.98% death rate in case of SSI). A maximum prediction power of 0.688 was found. Conclusion Despite the loss rate of almost 40% of the database samples due to the presence of noise, it was obtained a relevant sampling to evaluate the profile the hospitals. For the predictive process, although some configurations reached 0.688, which makes promising the use of the automated SSI monitoring framework for patients undergoing limb amputation surgery. To optimize data collection and enable other hospitals to use the SSI prediction tool (available in www.sacihweb.com), two mobile application were developed: one for monitoring the patient in the hospital and the other for post-hospital discharge monitoring. Disclosures All Authors: No reported disclosures
    Type of Medium: Online Resource
    ISSN: 2328-8957
    URL: Article
    DOI: 10.1093/ofid/ofaa439.1081
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2020
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  • 6
    Online Resource
    Online Resource
    Baseline characteristics and evolution of Brazilian patients with atypical hemolytic uremic syndrome: first report of the Brazilian aHUS Registry
    Oxford University Press (OUP) ; 2022
    In:  Clinical Kidney Journal Vol. 15, No. 8 ( 2022-07-23), p. 1601-1611
    Details
    In: Clinical Kidney Journal, Oxford University Press (OUP), Vol. 15, No. 8 ( 2022-07-23), p. 1601-1611
    Abstract: Atypical hemolytic uremic syndrome (aHUS) is an ultra-rare disease. Therefore, studies involving large samples are scarce, making registries powerful tools to evaluate cases. We present herein the first analysis of the Brazilian aHUS Registry (BRaHUS). Methods Analysis of clinical, laboratory, genetic and treatment data from patients inserted in the BRaHUS, from 2017 to 2020, as an initiative of the Rare Diseases Committee of the Brazilian Society of Nephrology. Results The cohort consisted of 75 patients (40 adults and 35 pediatric). There was a predominance of women (56%), median age at diagnosis of 20.7 years and a positive family history in 8% of cases. Renal involvement was observed in all cases and 37% had low C3 levels. In the  & lt;2 years of age group, males were predominant. Children presented lower levels of hemoglobin (P = .01) and platelets (P = .003), and higher levels of lactate dehydrogenase (LDH) (P = .004) than adults. Genetic analysis performed in 44% of patients revealed pathogenic variants in 66.6% of them, mainly in CFH and the CFHR1-3 deletion. Plasmapheresis was performed more often in adults (P = .005) and 97.3% of patients were treated with eculizumab and its earlier administration was associated with dialysis-free after 3 months (P = .08). Conclusions The cohort of BRaHUS was predominantly composed of female young adults, with renal involvement in all cases. Pediatric patients had lower hemoglobin and platelet levels and higher LDH levels than adults, and the most common genetic variants were identified in CFH and the CFHR1-3 deletion with no preference of age, a peculiar pattern of Brazilian patients.
    Type of Medium: Online Resource
    ISSN: 2048-8505 , 2048-8513
    URL: Article
    DOI: 10.1093/ckj/sfac097
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2022
    detail.hit.zdb_id: 2656786-6
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  • 7
    Online Resource
    Online Resource
    901. Risk Prediction for Surgical Site Infection in Patients Subject to Knee Arthroplasty Surgery
    Oxford University Press (OUP) ; 2020
    In:  Open Forum Infectious Diseases Vol. 7, No. Supplement_1 ( 2020-12-31), p. S484-S485
    Details
    In: Open Forum Infectious Diseases, Oxford University Press (OUP), Vol. 7, No. Supplement_1 ( 2020-12-31), p. S484-S485
    Abstract: This research represents an experiment on surgical site infection (SSI) in patients undergoing knee arthroplasty surgery procedures in hospitals in Belo Horizonte, between July 2016 and June 2018. The objective is to statistically evaluate such incidences and enable a study of the prediction power of SSI of pattern recognition algorithms, in this case the Multilayer Perceptron (MLP). Methods Data were collected on SSI in five hospitals. The Hospital Infection Control Committees (CCIH) of the hospitals involved collected all data used in the analysis during their routine SSI surveillance procedures and sent the information to the Nosocomial Infection Study Project (NOIS). Three procedures were performed: a treatment of the database collected for use of intact samples; a statistical analysis on the profile of the hospitals collected and; an assessment of the predictive power of five types of MLP (Backpropagation Standard, Momentum, Resilient Propagation, Weight Decay, and Quick Propagation) for SSI prediction. MLPs were tested with 3, 5, 7, and 10 hidden layer neurons and a database split for the resampling process (65% and 75% for testing, 35% and 25% for validation). They were compared by measuring AUC (Area Under the Curve - ranging from 0 to 1) presented for each of the configurations. Results From the 1438 data collected, 390 records were usable and it was verified: the average age of the patients who underwent this surgical procedure was 70 (ranging from 29 to 92), average surgery time was 171 minutes (between 50 and 480), 47% presented a hospital contamination, 1% SSI and no deaths. During the MLP experiments, due to the low number of SSI cases, the prediction rate for this specific surgery was 0.5. Conclusion Despite the large noise index of the database, it was possible to have a relevant sampling to evaluate the profile of hospitals in Belo Horizonte. However, for the predictive process, despite some results equal to 0.5, the database demands more samples of SSI cases, as only 1% of positive samples generated an unbalance of the database. To optimize data collection and enable other hospitals to use the SSI prediction tool (available in www.sacihweb.com), two mobile application were developed: one for monitoring the patient in the hospital and the other for monitoring after hospital discharge. Disclosures All Authors: No reported disclosures
    Type of Medium: Online Resource
    ISSN: 2328-8957
    URL: Article
    DOI: 10.1093/ofid/ofaa439.1089
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2020
    detail.hit.zdb_id: 2757767-3
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  • 8
    Online Resource
    Online Resource
    810. Cardiac Pacemaker Implantation Surgery: Automated Prediction of Surgical Site Infection
    Oxford University Press (OUP) ; 2021
    In:  Open Forum Infectious Diseases Vol. 8, No. Supplement_1 ( 2021-12-04), p. S499-S499
    Details
    In: Open Forum Infectious Diseases, Oxford University Press (OUP), Vol. 8, No. Supplement_1 ( 2021-12-04), p. S499-S499
    Abstract: A research focused on surgical site infection (SSI) was performed in patients undergoing cardiac pacemaker implantation surgery. The main objective is to statistically evaluate such incidences and enable a study of the prediction power of SSI through pattern recognition algorithms, in this case the Multilayer Perceptron (MLP). Methods Data were collected from five hospitals in the city of Belo Horizonte (more than 3,000,000 inhabitants), between July 2016 and June 2018, on SSI by the Hospital Infection Control Committees (CCIH) of the hospitals involved in the search. All data used in the analysis during their routine SSI surveillance procedures were collected. So, three procedures were performed: a treatment of the collected database for use of intact samples; a statistical analysis on the profile of the hospitals collected and; an assessment of the predictive power of five types of MLP (Backpropagation Standard, Momentum, Resilient Propagation, Weight Decay, and Quick Propagation) for SSI prediction. MLPs were tested with 3, 5, 7, and 10 hidden layer neurons and a database split for the resampling process (65% and 75% for testing, 35% and 25% for validation). They were compared by measuring AUC (Area Under the Curve - from 0 to 1) presented for each of the configurations. Results From 1394, 572 records were: 21% of deaths and 2.4% patients had SSI; from the confirmed SSI cases, approximately 64.3% had sites classified as “clean”; length of hospital stay ranged from 0 to 175 days (from 1 to 70 days); the average age is 67 years. The prediction power of SSI, the experiments achieved from 0.409 to 0.722. Conclusion Despite the considerable loss rate of more than 65% of the database samples due to the presence of noise, it was possible to have a relevant sampling for the profile evaluation of Belo Horizonte hospitals. Moreover, for the predictive process, although some configurations reached 0.722. To optimize data collection and enable other hospitals to use the SSI prediction tool (available in www.nois.org.br ), two mobile application were developed: one for monitoring the patient in the hospital and the other for monitoring after hospital discharge. Disclosures All Authors: No reported disclosures
    Type of Medium: Online Resource
    ISSN: 2328-8957
    URL: Article
    DOI: 10.1093/ofid/ofab466.1006
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
    detail.hit.zdb_id: 2757767-3
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  • 9
    Online Resource
    Online Resource
    895. Prediction of Occurrence for Surgical Site Infection in Infected Surgeries
    Oxford University Press (OUP) ; 2020
    In:  Open Forum Infectious Diseases Vol. 7, No. Supplement_1 ( 2020-12-31), p. S482-S482
    Details
    In: Open Forum Infectious Diseases, Oxford University Press (OUP), Vol. 7, No. Supplement_1 ( 2020-12-31), p. S482-S482
    Abstract: A survey was carried out in five hospitals, between July 2016 and June 2018, on surgical site infection (SSI) in patients undergoing infected surgery procedures, in the city of Belo Horizonte (3,000,000 inhabitants). The general objective is to statistically evaluate such incidences and enable an analysis of the SSI predictive power, through MLP (Multilayer Perceptron) pattern recognition algorithms. Methods Through the Hospital Infection Control Committees (CCIH) of the hospitals, a data collection on SSI was carried out. Such data is used in the analysis during your routine SSI surveillance procedures. So, three procedures were performed: a treatment of the collected database for use of intact samples; a statistical analysis on the profile of the collected hospitals and; an assessment of the predictive power of five types of MLPs (Backpropagation Standard, Momentum, Resilient Propagation, Weight Decay and Quick Propagation) for SSI prediction. The MLPs were tested with 3, 5, 7 and 10 neurons in the hidden layer and with a division of the database for the resampling process (65% or 75% for testing, 35% or 25% for validation). They were compared by measuring the AUC (Area Under the Curve - ranging from 0 to 1) presented for each of the configurations. Results From 1770 records, 810 were intact for analysis. It was found that: the average age is 53 years old (from 0 to 98 years old); the surgeries had an average time of approximately 140 minutes; the average hospital stay is 19 days, the death rate reached 10.86% and the SSI rate was 6.04%. A maximum prediction power of 0.729 was found. Conclusion There was a loss of 54% of the database samples due to the presence of noise. However, it was possible to have a relevant sample to assess the profile of these five hospitals. The predictive process, presented some configurations with results that reached 0.729, which promises the use of the structure for the monitoring of automated SSI for patients submitted to infected surgeries. To optimize data collection, enable other hospitals to use the prediction tool and minimize noise from the database, two mobile application were developed: one for monitoring the patient in the hospital and another for monitoring after hospital discharge. The SSI prediction analysis tool is available at www.nois.org.br. Disclosures All Authors: No reported disclosures
    Type of Medium: Online Resource
    ISSN: 2328-8957
    URL: Article
    DOI: 10.1093/ofid/ofaa439.1083
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2020
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  • 10
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    880. Artificial Neural Networks to Predict Surgical Site Infection in Aorta Artery Aneurysm Correction
    Oxford University Press (OUP) ; 2020
    In:  Open Forum Infectious Diseases Vol. 7, No. Supplement_1 ( 2020-12-31), p. S476-S477
    Details
    In: Open Forum Infectious Diseases, Oxford University Press (OUP), Vol. 7, No. Supplement_1 ( 2020-12-31), p. S476-S477
    Abstract: A survey was conducted in three hospitals, between July 2016 and June 2018, about surgical site infection (SSI) in patients undergoing surgeries to correct aortic artery aneurysms in the city of Belo Horizonte, with more than 3,000,000 of inhabitants. The general objective is to statistically evaluate such incidences and enable an analysis of the predictive power of SSI, through MLP (Multilayer Perceptron) pattern recognition algorithms. Methods Through the Hospital Infection Control Committees (CCIH) of the hospitals involved in the research, data collection on SSI was carried out. Such data is used in the analysis during your routine SSI surveillance procedures. Thus, three procedures were performed: a treatment of the database collected for use of intact samples; a statistical analysis on the profile of the collected hospitals and; an assessment of the predictive power of five types of MLPs (Backpropagation Standard, Momentum, Resilient Propagation, Weight Decay and Quick Propagation) for SSI prediction. The MLPs were tested with 3, 5, 7 and 10 neurons in the hidden layer and with a division of the database for the resampling process (65% or 75% for testing, 35% or 25% for validation). They were compared by measuring the AUC (Area Under the Curve - ranging from 0 to 1) for each of the configurations. Results From 600 records, 575 were complete for analysis. It was found that: the average age is 68 years (from 24 to 98 years); the average hospital stay is 9 days (with a maximum of 127 days), the death rate reached 6.43% and the SSI rate 2.78%. A maximum prediction power of 0.75 was found. Conclusion There was a loss of 4% of the database samples due to the presence of noise. It was possible to evaluate the profile of the three hospitals. The predictive process presented configurations with results that reached 0.75, which promises the use of the structure for the monitoring of automated SSI for patients undergoing surgery to correct aortic artery aneurysms. To optimize data collection, enable other hospitals to use the prediction tool and minimize noise from the database, two mobile application were developed: one for monitoring the patient in the hospital and another for monitoring after hospital discharge. The SSI prediction analysis tool is available at www.nois.org.br. Disclosures All Authors: No reported disclosures
    Type of Medium: Online Resource
    ISSN: 2328-8957
    URL: Article
    DOI: 10.1093/ofid/ofaa439.1068
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2020
    detail.hit.zdb_id: 2757767-3
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