Epidemiological situation of acquired immunodeficiency syndrome (AIDS)-related mortality in a municipality in northeastern Brazil. A retrospective cross-sectional study

Silva, Luana Rodrigues da; Araújo, Ellen Thallita Hill; Carvalho, Moisés Lopes; Almeida, Camila Aparecida Pinheiro Landim; Oliveira, Adélia Dalva da Silva; Carvalho, Patrícia Maria Gomes de; Rodrigues, Tatyanne Silva; Campelo, Viriato

doi:10.1590/1516-3180.2017.0130100917

“…Observa-se ainda, um discreto crescimento de mortes no sexo feminino ao longo dos anos estudados, sendo o maior número de mortes registrado em 2016 (Tabela 2). (Santos, 2016;Silva et al, 2018).…”

Section: Resultsunclassified

“…Óbitos por HIV/Aids no estado do Piauí em número absoluto e porcentagem, segundo sexo -2008 a 2018. número apresentado de mortes entre homens corrobora com os dados do boletim epidemiológico de HIV/Aids, em que a razão verificada para as mortes por Aids no ano de 2018 foi de 20 óbitos entre homens para cada 10 mulheres.Além disso, nota-se um comportamento linear na taxa de óbito desde o ano de 2005 (Tabela 2). Ademais, um estudo feito porSilva et al (2018), no município de Teresina (PI) confirmou a prevalência de mortes entre o sexo masculino, verificando-se que das 1.066 mortes ocorridas por causa básica Aids entre 2003 e 2013, 743 (69,7%) ocorrem entre homens.…”

unclassified

Mortalidade por HIV-Aids no estado do Piauí entre 2008 a 2018

Mota

¹

,

Oliveira

²

2021

RSD

1

0

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O presente estudo teve como objetivo descrever a mortalidade por HIV/Aids no Estado do Piauí e sua relação com indicadores socioeconômicos (Índice de Desenvolvimento Humano e Índice de Gini) de 2008 a 2018, descrevendo o sexo, a faixa etária, ano e local da morte e a causa básica da morte de cordo com a Classificação Estatística Internacional de Doenças e Problemas Relacionados à Saúde, Décima Revisão (CID-10). Em uma abordagem quantitativa para a obtenção dos dados acerca da mortalidade, a pesquisa utilizou dados secundários disponibilizados pela Secretaria de Estado da Saúde do Estado do Piauí (SESAPI) e para a obtenção dos dados referentes ao IDH e Índice de Gini, foram utilizadas as plataformas do Instituto Brasileiro de Geográfica e Estatística (IBGE) e DATASUS/TABNET, respectivamente. De acordo com os dados obtidos, 1280 óbitos foram contabilizados no período estudado, os quais 900 (70,36%) ocorrem no sexo masculino, na faixa etária de 30 a 39 anos (33%) e principalmente por HIV resultante em doenças infecciosas e parasitárias (64%). A prevalência de mortes se deu na capital do Estado, Teresina com 664 (51,9%), sobretudo nos primeiros anos analisados. No que se refere ao IDHm e índice de Gini médio por território de desenvolvimento, observa-se uma possível relação negativa e positiva, respectivamente, com os óbitos ocorridos no Estado. Constatou-se um aumento da taxa de mortalidade no período estudado, observando uma discreta queda em 2010, o que confirma um problema de saúde pública no Estado do Piauí.

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“…Unlike basic summary statistics that consider one cause at a time, these methods consider two causes simultaneously; they were used frequently to evaluate external cause epidemiology, specifically to assess the nature of poisoning and injury related to exposure to drugs and alcohol. [80][81][82][83][84] While the nature of the coding process mandates the use of multiple causes of death for assessing injuries sustained from external causes, descriptive pairwise analysis was regularly applied to infectious diseases [85][86][87][88][89] and chronic diseases. 3,[90][91][92][93][94][95][96] More complex applications such as the assessment of mortality odds ratios were applied to assess the strength of relationships between disease on the death certificates.…”

Section: Discussionmentioning

confidence: 99%

Analysis of multiple causes of death: a review of methods and practices

Bishop

¹

,

Balogun

²

,

Eynstone-Hinkins

³

et al. 2022

Preprint

1

0

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Background Research and reporting of mortality indicators typically focus on a single underlying cause of death selected from multiple causes recorded on a death certificate. The need to incorporate the multiple causes in mortality statistics - reflecting increasing multimorbidity and complex causation patterns - is recognised internationally. This review aims to identify and appraise relevant multiple cause analytical methods and practices. Methods We searched Medline, PubMed, Scopus and Web of Science from inception to December 2020 without language restrictions, supplemented by consultation with international experts. Eligible articles included those analysing multiple causes of death from death certificates. The process identified 4,080 articles; after screening, 434 full texts were reviewed. Results Most reviewed articles (77%, n=332) were published since 2001. The majority examined mortality by 'any-mention' of a cause of death (87%, n=377) and assessed pairwise combinations of causes (56%, n=245). Recently emerging (since 2001) were applications of methods to group deaths based on common cause patterns using, for example, cluster analysis (2%, n=9), and the application of multiple cause weights to re-evaluate mortality burden (1%, n=5). Multiple cause methods applied to specific research objectives are described for recently emerging approaches. Conclusion This review confirms rapidly increasing international interest in the analysis of multiple causes of death and provides the most comprehensive overview of methods and practices to date. Available multiple cause methods are diverse but suit a range of research objectives, that with greater data availability and technology could be further developed and applied across a range of settings.

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“…Acquired immune deficiency syndrome (AIDS) caused by human immunodeficiency virus (HIV) is a global health crisis [1]. HIV invades T lymphocytes (CD4+) cells of the human immune system, leading to a variety of opportunistic infections and death [2,3]. Hepatitis B (HB), a chronic disease characterized by hepatitis B virus (HBV) infection for more than 6 months and varying degrees of inflammatory necrosis/fibrosis of the liver, also poses a global health threat [4].…”

Section: Introductionmentioning

confidence: 99%

A Noninvasive Prediction Model for Hepatitis B Virus Disease in Patients with HIV: Based on the Population of Jiangsu, China

Yin

¹

,

Xue

²

,

Shi

³

et al. 2021

BioMed Research International

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Objective. To establish a machine learning model for identifying patients coinfected with hepatitis B virus (HBV) and human immunodeficiency virus (HIV) through two sexual transmission routes in Jiangsu, China. Methods. A total of 14197 HIV cases transmitted by homosexual and heterosexual routes were recruited. After data processing, 12469 cases (HIV and HBV, 1033; HIV, 11436) were left for further analysis, including 7849 cases with homosexual transmission and 4620 cases with heterosexual transmission. Univariate logistic regression was used to select variables with significant P value and odds ratio for multivariable analysis. In homosexual transmission and heterosexual transmission groups, 10 and 6 variables were selected, respectively. For identifying HIV individuals coinfected with HBV, a machine learning model was constructed with four algorithms, including Decision Tree, Random Forest, AdaBoost with decision tree (AdaBoost), and extreme gradient boosting decision tree (XGBoost). The detective value of each variable was calculated using the optimal machine learning algorithm. Results. AdaBoost algorithm showed the highest efficiency in both transmission groups (homosexual transmission group: accuracy = 0.928 , precision = 0.915 , recall = 0.944 , F − 1 = 0.930 , and AUC = 0.96 ; heterosexual transmission group: accuracy = 0.892 , precision = 0.881 , recall = 0.905 , F − 1 = 0.893 , and AUC = 0.98 ). Calculated by AdaBoost algorithm, the detective value of PLA was the highest in homosexual transmission group, followed by CR, AST, HB, ALT, TBIL, leucocyte, age, marital status, and treatment condition; in the heterosexual transmission group, the detective value of PLA was the highest (consistent with the condition in the homosexual group), followed by ALT, AST, TBIL, leucocyte, and symptom severity. Conclusions. The univariate logistics regression combined with the AdaBoost algorithm could accurately screen the risk factors of HBV in HIV coinfection without invasive testing. Further studies are needed to evaluate the utility and feasibility of this model in various settings.

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Epidemiological situation of acquired immunodeficiency syndrome (AIDS)-related mortality in a municipality in northeastern Brazil. A retrospective cross-sectional study

Cited by 8 publications

References 17 publications

Mortalidade por HIV-Aids no estado do Piauí entre 2008 a 2018

Mortalidade por HIV-Aids no estado do Piauí entre 2008 a 2018

Analysis of multiple causes of death: a review of methods and practices

A Noninvasive Prediction Model for Hepatitis B Virus Disease in Patients with HIV: Based on the Population of Jiangsu, China

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