METHODS: This cross-sectional study recruited 201 patients. The Hospital Anxiety Depression Scale (HADS) was used to determine anxiety level. Subsequently, patients who had scored 8 and above on the HADS were interviewed using Mini International Neuropsychiatric Interview (M.I.N.I) to ascertain the diagnosis of GAD. Whilst the Numerical Rating Scale (NRS) assessed pain severity. Multiple logistic regression analysis was used to determine factors associated with GAD.
RESULTS: Among those patients with chronic pain, the prevalence of GAD was 18.9%. Gender (AOR:7.94; 95% CI:2.34, 26.93), duration of the pain (AOR:1.30; 95% CI:1.03,1.63) and pain severity (AOR:18.75; CI:1.23,285.13) were significant factors associated with GAD.
CONCLUSION: GAD is a prevalent condition among chronic pain patients.
METHODS: Ten antibiotics, including bedaquiline, clofazimine, ethambutol, ethionamide, isoniazid, levofloxacin, linezolid, moxifloxacin, pretomanid, pyrazinamide, were investigated. TB antibiotic information sources were examined, consisting of 85 Patient Information Leaflets (PILs) and 40 antibiotic web resouces. Of these 85 PILs, 72 were taken from the National Medicines Regulator from six countries (3 TB high-incidence [Rwanda, Malaysia, South Africa] + 3 TB low-incidence [UK, Ireland, Malta] countries). Readability data was grouped into three categories, including (i) high TB-incidence countries (n = 33 information sources), (ii) low TB-incidence countries (n = 39 information sources) and (iii) web information (n = 53). Readability was calculated using Readable software, to obtain four readability scores [(i) Flesch Reading Ease (FRE), (ii) Flesch-Kincaid Grade Level (FKGL), (iii) Gunning Fog Index and (iv) SMOG Index], as well as two text metrics [words/sentence, syllables/word].
RESULTS: Mean readability scores of patient-facing TB antibiotic information for FRE and FKGL, were 47.4 ± 12.6 (sd) (target ≥ 60) and 9.2 ± 2.0 (target ≤ 8.0), respectively. There was no significant difference in readability between low incidence countries and web resources, but there was significantly poorer readability associated with PILs from high incidence countries versus low incidence countries (FRE; p = 0.0056: FKGL; p = 0.0095).
CONCLUSIONS: Readability of TB antibiotic PILs is poor. Improving readability of PILs should be an important objective when preparing patient-facing written materials, thereby improving patient health/treatment literacy.
METHOD: We conducted a retrospective, cross-sectional study using administrative data from three public tertiary hospitals in Malaysia. Data for hospital admissions between 1 March 2019 and 1 March 2020 with International Classification of Diseases 10th Revision (ICD-10) codes for acute myocardial infarction (MI), ischaemic heart disease (IHD), hypertensive heart disease, stroke, heart failure, cardiomyopathy, and peripheral vascular disease (PVD) were retrieved from the Malaysian Disease Related Group (Malaysian DRG) Casemix System. Patients were stratified by T2DM status for analyses. Multivariate logistic regression was used to identify factors influencing treatment costs.
RESULTS: Of the 1,183 patients in our study cohort, approximately 60.4% had T2DM. The most common CVDE was acute MI (25.6%), followed by IHD (25.3%), hypertensive heart disease (18.9%), stroke (12.9%), heart failure (9.4%), cardiomyopathy (5.7%) and PVD (2.1%). Nearly two-thirds (62.4%) of the patients had at least one cardiovascular risk factor, with hypertension being the most prevalent (60.4%). The treatment cost for all CVDEs was RM 4.8 million and RM 3.7 million in the T2DM and non-T2DM group, respectively. IHD incurred the largest cost in both groups, constituting 30.0% and 50.0% of the total CVDE treatment cost for patients with and without T2DM, respectively. Predictors of high treatment cost included male gender, non-minority ethnicity, IHD diagnosis and moderate-to-high severity level.
CONCLUSION: This study provides real-world cost estimates for CVDE hospitalisation and quantifies the combined burden of two major non-communicable disease categories at the public health provider level. Our results confirm that CVDs are associated with substantial health utilisation in both T2DM and non-T2DM patients.
AREAS COVERED: We intend to discuss the pathogenesis, diagnosis, and treatment modalities directed toward EBV-associated LPD in patients with distinct IEIs.
EXPERT OPINION: EBV-driven lymphoproliferation in IEIs presents a diagnostic and therapeutic problem that necessitates a comprehensive understanding of host-pathogen interactions, immune dysregulation, and personalized treatment approaches. A multidisciplinary approach involving immunologists, hematologists, infectious disease specialists, and geneticists is paramount to addressing the diagnostic and therapeutic challenges posed by this intriguing yet formidable clinical entity.
METHODS: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk-outcome pairs. Pairs were included on the basis of data-driven determination of a risk-outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk-outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk-outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws.
FINDINGS: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7-9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4-9·2]), smoking (5·7% [4·7-6·8]), low birthweight and short gestation (5·6% [4·8-6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8-6·0]). For younger demographics (ie, those aged 0-4 years and 5-14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9-27·7]) and environmental and occupational risks (decrease of 22·0% [15·5-28·8]), coupled with a 49·4% (42·3-56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9-21·7] for high BMI and 7·9% [3·3-12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6-1·9) for high BMI and 1·3% (1·1-1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4-78·8) for child growth failure and 66·3% (60·2-72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP).
INTERPRETATION: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions.
FUNDING: Bill & Melinda Gates Foundation.