Spelling suggestions: "subject:"diabetes inn pregnancy"" "subject:"diabetes inn regnancy""
111 |
Diabetes mellitus gestacional : perfis glicêmicos e desfechos da gestaçãoAndrade, Laís Trevisan de January 2017 (has links)
Introdução e objetivos – A finalidade prioritária no tratamento do diabetes mellitus gestacional (DMG) é alcançar níveis de glicemia materna tão próximos da normalidade quanto possível, a fim de reduzir os efeitos adversos associados à hiperglicemia na gestação. A auto verificação da glicemia capilar (perfil glicêmico) é o método mais usado para a monitorização do controle metabólico na gestação complicada por diabetes. Nosso objetivo foi analisar as associações entre os perfis glicêmicos maternos com os principais desfechos da gestação numa população de mulheres com DMG acompanhadas em ambulatório de pré-natal especializado em hospital universitário no sul do Brasil, Hospital de Clínicas de Porto Alegre (HCPA). Desenho e metodotologia – conduzimos um estudo de coorte prospectiva de gestantes referidas da rede de atenção primária de saúde pública para tratamento do DMG no HCPA, acompanhadas do diagnóstico ao parto. Pesquisamos associações entre os resultados dos perfis glicêmicos com o peso de nascimento e com o risco de recém-nascidos grandes para idade gestacional e de desfechos adversos perinatais. Resultados – acompanhamos 440 mulheres com DMG. A média do índice de massa corporal (IMC) foi 33.3kg/m2. 351 bebês (79.8%) mostraram peso adequado à idade gestacional no nascimento. As médias de glicemia nos perfis pré e pósprandiais aumentaram com o avanço na categoria de peso nascimento. Três ou mais perfis glicêmicos anormais foram o fator de risco mais robusto para o nascimento de bebês grandes (OR 3.15 1.51-6.55) e para o desenvolvimento de desfechos adversos perinatais (OR 2.28 1.59-3.29). O ganho de peso materno durante o tratamento associou-se ao risco de recém-nascido grande para idade gestacional, assim como o IMC pré-gestacional, esse último também fator de risco independente para eventos perinatais adversos. Conclusão – perfis glicêmicos anormais em mais de 2 ocasiões foram o fator de risco mais relacionado ao nascimento de um bebê grande para a idade gestacional e para o desenvolvimento de complicações neonatais. Efeito benéfico do tratamento do DMG, guiado pelos perfis glicêmicos, foi a maioria de recém-nascidos com peso adequado à idade gestacional nessa coorte, apesar da incidência de desfechos perinatais adversos não ter sido diferente entre as categorias de peso fetal de nascimento. / Background and objective – a priority target in the treatment of gestational diabetes mellitus (GDM) is attaining maternal glucose levels as close as possible to euglycemia, in order to decrease the adverse outcomes linked to hyperglycemia. Self-performed capillary glucose (glycemic profile) is the most widely used method for metabolic monitoring in pregnancy complicated by diabetes. We intended to analyze the associations of maternal glycemic profile to main pregnancy outcomes in a population of GDM women treated in a specialized prenatal clinic at a university hospital in South Brazil, Hospital de Clínicas de Porto Alegre (HCPA). Research design and methodology – we conducted a prospective cohort study of pregnant women, referred from public primary health care for treatment of GDM at HCPA, between 2008 and 2015. We searched associations of glycemic profiles to birth weight, large for gestational age newborn and adverse neonatal outcomes. Results – we followed 440 GDM women from diagnosis to delivery. Mean prepregnancy body mass index (BMI) was 33.3kg/m2; 351 babies (79.8%) had appropriate birth weight for gestational age. Mean glucose in pre-prandial and postprandial profiles increased with raising birth weight category. Three or more abnormal glycemic profiles showed the strongest association to a large baby (OR 3.15 1.51-6.55) and to a composite of adverse neonatal outcomes (OR 2.28 1.59- 3.29). Gestational weight gain in the course of treatment was associated to large babies, as pre-pregnancy BMI, the latter also an independent risk factor for adverse neonatal outcome. Conclusion – abnormal maternal glycemic profiles in more than two occasions were the stronger risk factor for delivering a large baby and for developing neonatal complications. A beneficial effect of GDM treatment, guided by glycemic profiles, was that most of our newborns had birth weight appropriate for gestational age, although incidence of adverse neonatal outcomes had been no different across birth weight categories.
|
112 |
Human immunodeficiency virus and diabetes mellitus : a missed link to improve pregnancy outcome in EthiopiaDememew, Zewdu Gashu 11 1900 (has links)
Introduction: Evidences indicate that human immuno-deficiency virus (HIV) and diabetes (DM) impact pregnancy outcomes but no experience on the integrated service delivery of HIV, DM and pregnancy care. This study explored the domains and levels of integration among DM, HIV and pregnancy care to prepare a service delivery model in Ethiopia.
Methods: A sequential exploratory mixed method and the integration theoretical framework guided the study. An exploratory qualitative phase used focused group discussion, in-depth interview and observation to explore the level of integration and to refine a questionnaire for the quantitative phase. The data were transcribed and coded for theme-based analysis. The descriptive quantitative phase described HIV, DM and pregnancy care services, and determined the burden of DM among HIV patients and the prevalence of pregnancy and pregnancy outcomes. Data was analysed using Epi-info. The findings were triangulated, discussed and interpreted.
Results: Seven themes were generated: joint plan, shared budget, monitoring system, structural location, the need of policy guide, the practice of integrated service delivery and suggested integration approaches. A coordinated HIV and pregnancy care services were noted. There was a linkage between diabetes and HIV, and diabetes and pregnancy care. The 1.5% of diabetes among HIV, the low number of pregnancies per a mother in diabetes (1.8) and HIV (1.3); the high adverse pregnancy outcomes among HIV (13.4% abortion, 12.4% low birth weight (LBW), 3.5% pre-term birth, 2.1% congenital malformation) and diabetes (3.2% big baby, 3.2% LBW, 3.1% Cesarean-section); the respective absent and low (16.2%) diabetes screening service at anti-natal and HIV clinics, the absent pregnancy care service for diabetic females justified the development of the tripartite integrated service delivery model of diabetes, HIV and pregnancy care.
Conclusions: The model suggests active diabetes screening, evaluation and treatment at HIV and antenatal clinics. It considers the coordination between non-communicable diseases (NCD), HIV and maternal health units. Pregnancy care could be coordinated at HIV and NCD units. Full integration can be practiced between HIV and pregnancy care units. Preparing policy guide, building the capacity of health providers, advocating and piloting the model may be prioritized before the implementation of the model. / Health Studies / D. Litt. et Phil. (Health Studies)
|
113 |
Best practice guidelines to monitor and prevent morbidity and mortality related to gestational diabetes mellitus in Addis Ababa, Ethiopia / Dintlhakaelo tsa tiriso e e gaisang ya go tlhokomela le go thibela ditshwaetsego tsa bomme le dintsho tse di golaganeng le bolwetsi jwa sukiri (diabetis mellitus) jwa baimana kwa Addis Ababa, EthiopiaGetahun Sinetsehay Alemayehu 08 1900 (has links)
Text in English with abstracts and keywords in English and Setswana / Aim: The purpose of the research was to determine the magnitude and factors associated
with gestational diabetes mellitus (GDM), and to explore the experiences of
gynaecologists/obstetricians and midwives in the monitoring and prevention of GDM- related
adverse maternal outcomes in order to propose best practice guidelines which may be
implemented to overcome the problem.
Methods: A concurrent mixed methods design was used. Participants for the quantitative
study were selected using systematic random sampling, with purposive sampling being used
for the qualitative part of the study. A total of 2000 medical records were reviewed using a
checklist, in addition to which 7 gynaecologists/obstetricians and 12 midwives were
interviewed using an in-depth interview guide. Descriptive and inferential statistics were used
for the quantitative part, while Colaizzi’s manual qualitative data analysis method wasused
for the qualitative part of the study.
Findings: The magnitude of GDM was found to be 2.2%. Age and family history of diabetes
mellitus were found to be factors associated with GDM (at p < 0.001). Other factors such as
obesity, previous GDM, previous history of fetal macrosomia and multiple gestations were
identified by respondents as factors related with GDM. In addition, the study explored the
experiences of health professionals (HPs) in the monitoring and prevention of adverse maternal outcomes related to GDM, with the results showing some differences in screening
and diagnostic techniques. It was also shown that lifestyle modification (physical exercise,
diet management) and medication were utilised for managing women with GDM. In this
regard, all the HPs agreed that creating awareness is the best intervention for preventing
GDM as well as its adverse maternal outcomes.
Conclusions: The magnitude of GDM is increasing, and much needs to be done to draw
attention to the burden that GDM places on the health of pregnant women and the public.
Since GDM is not considered a public health problem, little is being done to monitor the
condition and its adverse maternal outcomes. It is hoped that the best practice guidelines
developed from this research study may assist in reducing the adverse maternal outcomes
of GDM in Ethiopia / Maikaelelo: Lebaka la patlisiso e ne e le go tlhotlhomisa go nna teng le mabaka a a
golaganeng le bolwetsi jwa sukiri jwa baimana (GDM), le go tlhotlhomisa maitemogelo a
dingaka tsa malwetsi a basadi (gynaeologists/ obstetricians) le babelegisi mo go
tlhokomeleng le go thibeleng ditlamorago tse di maswe mo baimaneng tse di amanang le
GDM gore go tshitshinngwe dintlhakaelo tse di gaisang tse di ka diragadiwang go fenya
bothata.
Mekgwa: Go dirisitswe thadiso ya mekgwa e e tlhakantsweng. Banni-le-seabe ba
thutopatlisiso e e lebelelang dipalopalo ba ne ba tlhophiwa go diriswa go tlhopha sampole
ka go se latele thulaganyo, mme go tlhopha sampole ka maikaelelo go ne ga diriswa mo
karolong ya thutopatlisiso e e lebelelang mabaka. Go sekasekilwe palogotlhe ya direkoto tsa
kalafi tse 2 000 go diriswa lenanetshekatsheko, mme mo godimo ga moo, go ne ga nna le
dipotsolotso le dingaka tsa malwetsi a basadi di le supa le babelegisi ba le 12 go diriswa
kaedi ya dipotsolotso tse di tseneletseng. Dipalopalo tse di tlhalosang le tse go sweditsweng
ka tsona di ne tsa diriswa mo karolong ya dipalopalo ya thutopatlisiso, fa go dirisitswe
mokgwa wa ga Colaizi wa tokololo ya data ya mabaka mo karolong e e lebelelang mabaka.
Diphitlhelelo: Go nna teng ga GDM go ne ga fitlhelwa e le 2.2%. Dingwaga le hisetori ya bolwetsi jwa sukiri ya baimana mo lelapeng di fitlhetswe e le dintlha tse di golaganeng le
GDM (ka p < 0.001). Dintlha dingwe, jaaka go nona phetelela, GDM mo nakong e e fetileng,
go nna teng ga macrosomia ya masea mo nakong e e fetileng le boimana jwa masea a feta
bongwe di ne tsa supiwa ke batsibogi jaaka dintlha tse di golaganeng le GDM. Go tlaleletsa
foo, thuto e ne ya sekaseka maitemogelo a baporofešenale ba boitekanelo (HPs) mo
tlhokomelong le thibelo ya ditlamorago tse di sa siamang mo baimaneng tse di golaganeng
le GDM, mme dipholo di bontshitse dipharologano dingwe mo dithekeniking tsa
go sekirina le go phekola. Go bonagetse gape gore phetolo ya mokgwa wa botshelo
(katiso ya mmele, tsamaiso ya mokgwa wa go ja) le kalafi di ne tsa diriswa go laola bolwetsi
jwa basadi ba ba nang le GDM. Mo lebakeng le, baporofešenale botlhe ba boitekanelo ba
ne ba dumelana gore go dira temoso ke tsereganyo e e gaisang ya go thibela GDM ga
mmogo le ditlamorago tsa yona tse di sa siamang mo baimaneng.
Ditshwetso: Go nna teng ga GDM go a oketsega, mme go tshwanetse go dirwa go le gontsi
go lemosa ka mokgweleo o bolwetse jono bo o bayang mo boitekanelong jwa baimana le
setšhaba. Ka ntlha ya gore GDM ga e kaiwe jaaka bothata jwa boitekanelo jwa setšhaba,
ga go dirwe go le kalo go tlhokomela bolwetsi le ditlamorago tsa jona tse di sa siamang mo
baimaneng. Go solofelwa gore dintlhakaelo tsa tiriso e e gaisang tse di dirilweng mo
thutopatlisisong eno di ka thusa go fokotsa ditlamorago tse di sa siamang tsa GDM mo
baimaneng kwa Ethiopia. / Health Studies / D. Litt. et Phil. (Public Health)
|
Page generated in 0.055 seconds