Category: Nevin Manimala

BMJ Open. 2022 Sep 7;12(9):e062304. doi: 10.1136/bmjopen-2022-062304.

ABSTRACT

OBJECTIVE: Estimates of dementia prevalence in New Zealand (NZ) have previously been extrapolated from limited Australasian studies, which may be neither accurate nor reflect NZ’s unique population and diverse ethnic groups. This study used routinely collected health data to estimate the 1-year period prevalence for diagnosed dementia for each of the 4 years between July 2016 and June 2020 in the age 60+ and age 80+ populations and for the four main ethnic groups.

DESIGN: A population-based descriptive study.

SETTING: Seven national health data sets within the NZ Integrated Data Infrastructure (IDI) were linked. Diagnosed dementia prevalence for each year was calculated using the IDI age 60+ and age 80+ populations as the denominator and also age-sex standardised to allow comparison across ethnic groups.

PARTICIPANTS: Diagnosed dementia individuals in the health datasets were identified by diagnostic or medication codes used in each of the data sets with deduplication of those who appeared in more than one data set.

RESULTS: The crude diagnosed dementia prevalence was 3.8%-4.0% in the age 60+ population and 13.7%-14.4% in the age 80+ population across the four study years. Dementia prevalence age-sex standardised to the IDI population in the last study period of 2019-2020 was 5.4% for Māori, 6.3% for Pacific Islander, 3.7% for European and 3.4% for Asian in the age 60+ population, and 17.5% for Māori, 22.2% for Pacific Islander, 13.6% for European and 13.5% for Asian in the age 80+ population.

CONCLUSIONS: This study provides the best estimate to date for dementia prevalence in NZ but is limited to those people who were identified as having dementia based on data from the seven included data sets. The findings suggest that diagnosed dementia prevalence is higher in Māori and Pacific Islanders. A nationwide NZ community-based dementia prevalence study is much needed to confirm the findings of this study.

PMID:36691174 | DOI:10.1136/bmjopen-2022-062304

BMJ Open. 2022 Sep 7;12(9):e060326. doi: 10.1136/bmjopen-2021-060326.

ABSTRACT

INTRODUCTION: The terms ‘precision medicine’ and ‘personalised medicine’ have become key terms in health-related research and in science-related public communication. However, the application of these two concepts and their interpretation in various disciplines are heterogeneous, which also affects research translation and public awareness. This leads to confusion regarding the use and distinction of the two concepts. Our aim is to provide a snapshot of the current understanding of these concepts.

METHODS AND ANALYSIS: Our study will use Rodgers’ evolutionary concept analysis to systematically examine the current understanding of the concepts ‘precision medicine’ and ‘personalised medicine’ in clinical medicine, biomedicine (incorporating genomics and bioinformatics), health services research, physics, chemistry, engineering, machine learning and artificial intelligence, and to identify their respective attributes (clusters of characteristics) and surrogate and related terms. A systematic search of the literature will be conducted for 2016-2022 using databases relevant to each of these disciplines: ACM Digital Library, CINAHL, Cochrane Library, F1000Research, IEEE Xplore, PubMed/Medline, Science Direct, Scopus and Web of Science. These are among the most representative databases for the included disciplines. We will examine similarities and differences in definitions of ‘precision medicine’ and ‘personalised medicine’ in the respective disciplines and across (sub)disciplines, including attributes of each term. This will enable us to determine how these two concepts are distinguished.

ETHICS AND DISSEMINATION: Following ethical and research standards, we will comprehensively report the methodology for a systematic analysis following Rodgers’ concept analysis method. Our systematic concept analysis will contribute to the clarification of the two concepts and distinction in their application in given settings and circumstances. Such a broad concept analysis will contribute to non-systematic syntheses of the concepts, or occasional systematic reviews on one of the concepts that have been published in specific disciplines, in order to facilitate interdisciplinary communication, translational medical research and implementation science.

PMID:36691172 | DOI:10.1136/bmjopen-2021-060326

BMJ Open. 2022 Sep 7;12(9):e049182. doi: 10.1136/bmjopen-2021-049182.

ABSTRACT

OBJECTIVES: To evaluate the health-condition of military police officers and firefighters. To identify risk factors for not being medically ready for duty.

DESIGN: Cross-sectional study.

SETTING: Data were extracted from medical records during annual periodic health assessments of police officers and firefighters serving with the military police in Paraná, Brazil.

PARTICIPANTS: 6621 police officers (5927 men and 694 women) and 1347 firefighters (1257 men and 90 women) who underwent health assessments between July 2018 and June 2019 were analysed. Pregnant women were excluded.

OUTCOME MEASURES: Data included variables such as sex, age, anthropometric measurements, lifestyle, comorbidities and laboratory tests. Multiple logistic regression was used to estimate the probability of not being medically ready for active duty.

RESULTS: Overall, police officers had worse health status than firefighters and greater prevalence of overweight and obesity, regardless of sex. Musculoskeletal diseases were the most commonly reported disease by police officers and firefighters of both sexes. Among men, hypertension was the second most prevalent disease, followed by psychiatric diseases and dyslipidaemia. Among women, psychiatric diseases were the second most prevalent. Male police officers ≥40 years old presented the highest probability of not being considered ready for duty (40.1%). The probability of male police officers between the ages of 31 and 40 not being ready was similar to that for male firefighters >40 years old. There was a higher chance of not being medically ready professionals with diseases such as diabetes mellitus (OR 2.95, 95% CI 1.97 to 5.03), dyslipidaemia (OR 2.65, 95% CI 1.96 to 3.58), hypertension (OR 2.29, 95% CI 1.85 to 4.70), high total cholesterol (OR 2.16, 95% CI 1.93 to 2.42), and heart disease (OR 2.13, 95% CI 1.32 to 3.45).

CONCLUSIONS: There was a high prevalence of chronic diseases and modifiable cardiovascular risk factors among police officers and firefighters. Healthy protective measures should be offered frequently, particularly to police officers at an earlier age.

PMID:36691169 | DOI:10.1136/bmjopen-2021-049182

BMJ Open. 2022 Sep 2;12(9):e060290. doi: 10.1136/bmjopen-2021-060290.

ABSTRACT

INTRODUCTION: Acute variceal haemorrhage (AVH) in patients with cirrhosis remains a topic of great interest. Although several guidelines recommend endoscopy within 24 hours after AVH, there is no consensus on the most appropriate time to perform this intervention. The purpose of this study is to identify whether urgent endoscopy (within 6 hours after gastroenterological consultation) is superior to non-urgent endoscopy (between 6 hours and 24 hours after gastroenterological consultation) in reducing the rebleeding rate of these patients.

METHODS AND ANALYSIS: This is a single-centred, prospective, randomised clinical trial. Between March 2021 and December 2023, an estimated 400 patients will be randomised in a 1:1 ratio to receive endoscopic intervention either within 6 hours or between 6 and 24 hours after gastroenterological consultation. Randomisation will be conducted by permuted block randomisation, with stratification by age, systolic blood pressure and pulse rate. The primary efficacy endpoint is rebleeding within 42 days after control of AVH. The secondary efficacy endpoints mainly include all-cause mortality within 42 days after randomisation, persistent bleeding, length of hospitalisation, etc. ETHICS AND DISSEMINATION: The study protocol was approved by the Ethical Committees of Jinling Hospital (authorised ethics no. DZQH-KYLL-21-01). This trial will provide valuable insights into the timing of endoscopic intervention for AVH in patients with cirrhosis. Furthermore, the trial results and conclusions could provide high-quality evidence to guide clinical research and treatment.

TRIAL REGISTRATION NUMBER: NCT04786743.

PMID:36691157 | DOI:10.1136/bmjopen-2021-060290

BMJ Open. 2022 Sep 5;12(9):e061519. doi: 10.1136/bmjopen-2022-061519.

ABSTRACT

OBJECTIVES: The aim of this study was to evaluate the quality of reporting of randomised controlled trials (RCTs) of artificial intelligence (AI) in healthcare against Consolidated Standards of Reporting Trials-AI (CONSORT-AI) guidelines.

DESIGN: Systematic review.

DATA SOURCES: We searched PubMed and EMBASE databases for studies reported from January 2015 to December 2021.

ELIGIBILITY CRITERIA: We included RCTs reported in English that used AI as the intervention. Protocols, conference abstracts, studies on robotics and studies related to medical education were excluded.

DATA EXTRACTION: The included studies were graded using the CONSORT-AI checklist, comprising 43 items, by two independent graders. The results were tabulated and descriptive statistics were reported.

RESULTS: We screened 1501 potential abstracts, of which 112 full-text articles were reviewed for eligibility. A total of 42 studies were included. The number of participants ranged from 22 to 2352. Only two items of the CONSORT-AI items were fully reported in all studies. Five items were not applicable in more than 85% of the studies. Nineteen per cent (8/42) of the studies did not report more than 50% (21/43) of the CONSORT-AI checklist items.

CONCLUSIONS: The quality of reporting of RCTs in AI is suboptimal. As reporting is variable in existing RCTs, caution should be exercised in interpreting the findings of some studies.

PMID:36691151 | DOI:10.1136/bmjopen-2022-061519

BMJ Open. 2022 Sep 5;12(9):e062422. doi: 10.1136/bmjopen-2022-062422.

ABSTRACT

OBJECTIVE: This study examined the prevalence and predictors of maternal and newborn skin-to-skin contact at birth in Papua New Guinea.

DESIGN: Data for the study was extracted from the 2016-18 Papua New Guinea Demographic and Health Survey. We included 6,044 women with birth history before the survey in the analysis. Percentages were used to summarise the prevalence of maternal and newborn skin-to-skin contact. A multivariable multilevel binary logistic regression was adopted to examine the predictors of maternal and newborn skin-to-skin contact. The results were presented using adjusted ORs (aORs), with their respective 95% confidence intervals (CIs). Statistical significance was set at p<0.05.

SETTING: The study was conducted in Papua New Guinea.

PARTICIPANT: Mothers with children under 5 years.

OUTCOME MEASURES: Mother and newborn skin-to-skin contact.

RESULTS: The prevalence of mother and newborn skin-to-skin contact was 45.2% (95% CI=42.4 to 48.0). The odds of mother and newborn skin-to-skin contact was higher among women with primary education (aOR=1.38; 95% CI=1.03 to 1.83), women with four or more antenatal care attendance (aOR=1.27; 95% CI=1.01 to 1.61), those who delivered at the health facility (aOR=1.27; 95% CI=1.01 to 1.61), and women from communities with high socioeconomic status (aOR=1.45; 95% CI=1.11 to 1.90).

CONCLUSION: The study has demonstrated that the prevalence of mother and newborn skin-to-skin contact in Papua New Guinea is low. Factors shown to be associated with mother and newborn skin-to-skin contact were maternal level of education, antenatal care attendance, health facility delivery, and community socioeconomic status. A concerted effort should be placed in improving maternal health service utilisation such as antenatal care attendance and skilled birth delivery, which subsequently lead to the practice of skin-to-skin contact. Also, women should be empowered through education as it has positive impact on their socioeconomic status and health service utilisation.

PMID:36691147 | DOI:10.1136/bmjopen-2022-062422

BMJ Open. 2022 Sep 5;12(9):e056564. doi: 10.1136/bmjopen-2021-056564.

ABSTRACT

OBJECTIVE: This study aimed to determine the prevalence and associated factors of poor sleep quality among pregnant women in Ethiopia.

METHOD: Institutional based cross-sectional study.

SETTING: University of Gondar Comprehensive Specialized Hospital, Gondar, Ethiopia.

PARTICIPANTS: A total of 415 pregnant women were recruited by using a systematic random sampling technique from 28 April 2020 to 12 June 2020.

MEASUREMENT: The desired data were collected through face-to-face interview technique by using validated questionnaires such as the Pittsburgh Sleep Quality Index, Edinburgh Postnatal Depression Scale, Perceived Stress Scale, Oslo-3 and Abuse Assessment Screen. The data were analysed by using SPSS V.20. Logistic regression analysis was used to identify associated factors with poor sleep quality. Variables having a p value of less than 0.2 in the bivariate analysis were entered to the multivariable logistic regression. A p value of less than 0.05 was considered statistically significant, at 95% CI.

RESULT: In this study, 175 (42.2%) pregnant women had poor sleep quality. According to multivariable logistic regression, being first and third trimesters of gestational age (adjusted OR (aOR) 2.31, 95% CI 1.16 to 4.61 and aOR 3.45, 95% CI 2.05 to 5.79, respectively), consumption of caffeinated substances (aOR 2.96, 95% CI 1.68 to 5.52), having depression (aOR 2.12, 95% CI 1.19 to 3.76), having high perceived stress (aOR 5.39, 95% CI 1.96 to 14.79) and experience of intimate partner violence (aOR 5.57, 95% CI 2.19 to 14.68) were positive significant associated factors with poor sleep quality.

CONCLUSION AND RECOMMENDATION: The prevalence of poor sleep quality among pregnant women was relatively high. First and third trimesters, consumption of caffeinated substances, antenatal depression, high perceived stress and intimate partner violence were factors significantly associated with poor sleep quality. This result suggests that all pregnant women should be screened and treated for poor sleep quality during the first and third trimesters.

PMID:36691143 | DOI:10.1136/bmjopen-2021-056564

BMJ Open. 2022 Sep 5;12(9):e060718. doi: 10.1136/bmjopen-2021-060718.

ABSTRACT

OBJECTIVE: This study aims to explore the rural-urban differentials in the influences of individual and geospatial preparedness on institutional childbirth in Bangladesh. A related aim of this paper is to derive estimates to measure geospatial preparedness for institutional births, through statistical modelling, when no data are available for measuring this areal indicator.

DESIGN, SETTINGS AND PARTICIPANTS: The paper used data from a large-scale nationally representative Bangladesh Multiple Indicator Cluster Survey 2019. The analytical sample included 9203 currently married women of reproductive age who had a live birth in the 2 years preceding the survey.

METHODS: Mixed effect logistic regression models were employed to explore the rural-urban differentials in influences of individual and geospatial preparedness on institutional childbirth. The district-level random effect estimation was done to measure geospatial preparedness. The conditional autoregressive model was used to examine the association of geospatial preparedness with areal variation in institutional births.

RESULTS: In rural settings, women who gave birth to a female newborn were 18% less likely to have facility births compared with women who gave birth to a male newborn. Also, women from households in the highest wealth quintile were twice as likely to have facility births compared with those from households in the poorest wealth quintile. In contrast, in urban areas, facility births did not vary by sex of the fetus or by households’ socioeconomic status. The geospatial preparedness explained 8% and 9% of the variability in institutional births in rural and urban areas, respectively. Geospatial mapping revealed low preparedness in the hill tracts. Findings identified geospatial preparedness as a potential source of areal variation in facility births.

CONCLUSION: Findings suggest improving district-level preparedness and developing differential programme strategies for urban and rural areas to increase the national prevalence and more equitable use of institutional childbirth in Bangladesh.

PMID:36691141 | DOI:10.1136/bmjopen-2021-060718

BMJ Open. 2022 Sep 5;12(9):e060026. doi: 10.1136/bmjopen-2021-060026.

ABSTRACT

OBJECTIVES: To develop a disease stratification model for COVID-19 that updates according to changes in a patient’s condition while in hospital to facilitate patient management and resource allocation.

DESIGN: In this retrospective cohort study, we adopted a landmarking approach to dynamic prediction of all-cause in-hospital mortality over the next 48 hours. We accounted for informative predictor missingness and selected predictors using penalised regression.

SETTING: All data used in this study were obtained from a single UK teaching hospital.

PARTICIPANTS: We developed the model using 473 consecutive patients with COVID-19 presenting to a UK hospital between 1 March 2020 and 12 September 2020; and temporally validated using data on 1119 patients presenting between 13 September 2020 and 17 March 2021.

PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome is all-cause in-hospital mortality within 48 hours of the prediction time. We accounted for the competing risks of discharge from hospital alive and transfer to a tertiary intensive care unit for extracorporeal membrane oxygenation.

RESULTS: Our final model includes age, Clinical Frailty Scale score, heart rate, respiratory rate, oxygen saturation/fractional inspired oxygen ratio, white cell count, presence of acidosis (pH <7.35) and interleukin-6. Internal validation achieved an area under the receiver operating characteristic (AUROC) of 0.90 (95% CI 0.87 to 0.93) and temporal validation gave an AUROC of 0.86 (95% CI 0.83 to 0.88).

CONCLUSIONS: Our model incorporates both static risk factors (eg, age) and evolving clinical and laboratory data, to provide a dynamic risk prediction model that adapts to both sudden and gradual changes in an individual patient’s clinical condition. On successful external validation, the model has the potential to be a powerful clinical risk assessment tool.

TRIAL REGISTRATION: The study is registered as ‘researchregistry5464’ on the Research Registry (www.researchregistry.com).

PMID:36691139 | DOI:10.1136/bmjopen-2021-060026

BMJ Open. 2022 Sep 6;12(9):e058467. doi: 10.1136/bmjopen-2021-058467.

ABSTRACT

INTRODUCTION: Poor medication adherence is associated with worsening patient health outcomes and increasing healthcare costs. A holistic tool to assess both medication adherence and drivers of adherence behaviour has yet to be developed. This study aimed to examine SPUR, a multifactorial patient-reported outcome measure of medication adherence in patients living with type 2 diabetes, with a view to develop a suitable model for psychometric analysis.Furthermore, the study aimed to explore the relationship between the SPUR model and socio-clinical factors of medication adherence.

RESEARCH DESIGN AND METHODS: The study recruited 378 adult patients living with type 2 diabetes from a mix of community and secondary-care settings to participate in this non-interventional cross-sectional study. The original SPUR-45 tool was completed by participants with other patient-reported outcome measures for comparison, in addition to the collection of two objective adherence measures; HbA_1c and the medication possession ratio (MPR).

RESULTS: Factor and reliability analysis conducted on SPUR-45 produced a revised and more concise version (27-items) of the tool, SPUR-27, which was psychometrically assessed. SPUR-27 observed strong internal consistency with significant correlations to the other psychometric measures (Beliefs about Medication Questionnaire, Diabetes Treatment Satisfaction Questionnaire, Medicine Adherence Rating Scale) completed by participants. Higher SPUR-27 scores were associated with lower HbA_1c values and a higher MPR, as well as other predicted socio-clinical factors such as higher income, increased age and lower body mass index.

CONCLUSIONS: SPUR-27 demonstrated strong psychometric properties. Further work should look to examine the test-retest reliability of the model as well as examine transferability to other chronic conditions and broader population samples. Overall, the initial findings suggest that SPUR-27 is a reliable model for the multifactorial assessment of medication adherence among patients living with type 2 diabetes.

PMID:36691135 | DOI:10.1136/bmjopen-2021-058467