Investigating the prevalence of diabetic complications in overweight/obese patients:a study in a tertiary hospital in Malaysia

BACKGROUND: In Malaysia, although diabetes accounts for more than 70% of all deaths, it is unclear how it relates to BMI and diabetic complications. This study aimed to investigate the prevalence of obesity and diabetic complications among diabetic patients in Malaysia. MATERIALS AND METHODS: A cross-sectional study using an existing clinical registry was performed from 1 January 2020 to 31 December 2020 at Hospital Serdang, Malaysia. Adult patients with type 2 diabetes mellitus had their medical records examined for disease complications, as reported by the patient at first contact with the DMTAC pharmacist. RESULTS: The study comprised a total of 495 participants with an average HbA1c of 10.5%. About 91% (n = 451) of the 495 patients were obese/overweight. Around 37.8% (n = 187) of diabetic patients are between the ages of 50 and 59, and 59% (n = 292) have had diabetes for less than 10 years. A total of 8.5% (n = 42) and 9.7% (n = 48) consume alcohol and smoke, respectively. Around 29.9% (n = 148) had one other comorbidity (hypertension or dyslipidemia), and 63.4% (n = 314) had two comorbidities. Regarding the prevalence of complications, there were 18.9% (n = 94) who had myocardial infarction, 11.1% (n = 55) who had stroke, and 9% (n = 45) who had CKD. Age (adjusted OR = 1.03; 95% CI 1.00 to 1.07; p = 0.041) and hypertension (adjusted OR = 4.06; 95% CI 1.21 to 13.60; p = 0.023) were significantly related with the prevalence of complications in patients with diabetes. CONCLUSION: In our study, a BMI of more than 23 kg/m(2) (obese/overweight) does not seem to be associated with the prevalence of complications. Age and hypertension, on the other hand, appear to be strong risk predictors of the incidence of complications. With the understanding of the recent outlook on diabetes, it is recommended that public education on the targeted population should be encouraged to negate these complications. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13410-022-01131-x

Assessing mortality differences across acute respiratory failure management strategies in Covid-19

PURPOSE: Prolonged observation could avoid invasive mechanical ventilation (IMV) and related risks in patients with Covid-19 acute respiratory failure (ARF) compared to initiating early IMV. We aimed to determine the association between ARF management strategy and in-hospital mortality. MATERIALS AND METHODS: Patients in the Weill Cornell Covid-19 registry who developed ARF between March 5 – March 25, 2020 were exposed to an early IMV strategy; between March 26 – April 1, 2020 to an intermediate strategy; and after April 2 to prolonged observation. Cox proportional hazards regression was used to model in-hospital mortality and test an interaction between ARF management strategy and modified sequential organ failure assessment (mSOFA). RESULTS: Among 632 patients with ARF, 24% of patients in the early IMV strategy died versus 28% in prolonged observation. At lower mSOFA, prolonged observation was associated with lower mortality compared to early IMV (at mSOFA = 0, HR 0.16 [95% CI 0.04–0.57]). Mortality risk increased in the prolonged observation strategy group with each point increase in mSOFA score (HR 1.29 [95% CI 1.10–1.51], p = 0.002). CONCLUSION: In Covid-19 ARF, prolonged observation was associated with a mortality benefit at lower mSOFA scores, and increased mortality at higher mSOFA scores compared to early IMV

Reconsidering the Utility of Race-Specific Lung Function Prediction Equations.

Rationale: African American individuals have worse outcomes in chronic obstructive pulmonary disease (COPD). Objectives: To assess whether race-specific approaches for estimating lung function contribute to racial inequities by failing to recognize pathological decrements and considering them normal. Methods: In a cohort with and at risk for COPD, we assessed whether lung function prediction equations applied in a race-specific versus universal manner better modeled the relationship between FEV1, FVC, and other COPD outcomes, including the COPD Assessment Test, St. George's Respiratory Questionnaire, computed tomography percent emphysema, airway wall thickness, and 6-minute-walk test. We related these outcomes to differences in FEV1 using multiple linear regression and compared predictive performance between fitted models using root mean squared error and Alpaydin's paired F test. Measurements and Main Results: Using race-specific equations, African American individuals were calculated to have better lung function than non-Hispanic White individuals (FEV1, 76.8% vs. 71.8% predicted; P = 0.02). Using universally applied equations, African American individuals were calculated to have worse lung function. Using Hankinson's Non-Hispanic White equation, FEV1 was 64.7% versus 71.8% (P < 0.001). Using the Global Lung Initiative's Other race equation, FEV1 was 70.0% versus 77.9% (P < 0.001). Prediction errors from linear regression were less for universally applied equations compared with race-specific equations when examining FEV1% predicted with the COPD Assessment Test (P < 0.01), St. George's Respiratory Questionnaire (P < 0.01), and airway wall thickness (P < 0.01). Although African American participants had greater adversity (P < 0.001), less adversity was only associated with better FEV1 in non-Hispanic White participants (P for interaction = 0.041). Conclusions: Race-specific equations may underestimate COPD severity in African American individuals.Clinical trial registered with www.clinicaltrials.gov (NCT01969344)

Characterizing COPD Symptom Variability in the Stable State Utilizing the Evaluating Respiratory Symptoms in COPD Instrument.

RationaleIt has been suggested that patients with chronic obstructive pulmonary disease (COPD) experience considerable daily respiratory symptom fluctuation. A standardized measure is needed to quantify and understand the implications of day-to-day symptom variability.ObjectivesTo compare standard deviation with other statistical measures of symptom variability and identify characteristics of individuals with higher symptom variability.MethodsIndividuals in the SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) Exacerbations sub-study completed an Evaluating Respiratory Symptoms in COPD (E-RS) daily questionnaire. We calculated within-subject standard deviation (WS-SD) for each patient at week 0 and correlated this with measurements obtained 4 weeks later using Pearson's r and Bland Altman plots. Median WS-SD value dichotomized participants into higher versus lower variability groups. Association between WS-SD and exacerbation risk during 4 follow-up weeks was explored.Measurements and main resultsDiary completion rates were sufficient in 140 (68%) of 205 sub-study participants. Reproducibility (r) of the WS-SD metric from baseline to week 4 was 0.32. Higher variability participants had higher St George's Respiratory Questionnaire (SGRQ) scores (47.3 ± 20.3 versus 39.6 ± 21.5, p=.04) than lower variability participants. Exploratory analyses found no relationship between symptom variability and health care resource utilization-defined exacerbations.ConclusionsWS-SD of the E-RS can be used as a measure of symptom variability in studies of patients with COPD. Patients with higher variability have worse health-related quality of life. WS-SD should be further validated as a measure to understand the implications of symptom variability

Development of Decadal (1985–1995–2005) Land Use and Land Cover Database for India

India has experienced significant Land-Use and Land-Cover Change (LULCC) over the past few decades. In this context, careful observation and mapping of LULCC using satellite data of high to medium spatial resolution is crucial for understanding the long-term usage patterns of natural resources and facilitating sustainable management to plan, monitor and evaluate development. The present study utilizes the satellite images to generate national level LULC maps at decadal intervals for 1985, 1995 and 2005 using onscreen visual interpretation techniques with minimum mapping unit of 2.5 hectares. These maps follow the classification scheme of the International Geosphere Biosphere Programme (IGBP) to ensure compatibility with other global/regional LULC datasets for comparison and integration. Our LULC maps with more than 90% overall accuracy highlight the changes prominent at regional level, i.e., loss of forest cover in central and northeast India, increase of cropland area in Western India, growth of peri-urban area, and relative increase in plantations. We also found spatial correlation between the cropping area and precipitation, which in turn confirms the monsoon dependent agriculture system in the country. On comparison with the existing global LULC products (GlobCover and MODIS), it can be concluded that our dataset has captured the maximum cumulative patch diversity frequency indicating the detailed representation that can be attributed to the on-screen visual interpretation technique. Comparisons with global LULC products (GlobCover and MODIS) show that our dataset captures maximum landscape diversity, which is partly attributable to the on-screen visual interpretation techniques. We advocate the utility of this database for national and regional studies on land dynamics and climate change research. The database would be updated to 2015 as a continuing effort of this study