Risk stratification of cardiac arrhythmias and sudden cardiac death in type 2 diabetes mellitus patients receiving insulin therapy: A population-based cohort study

Introduction Metabolic abnormalities may exacerbate the risk of adverse outcomes in patients with type 2 diabetes mellitus. The present study aims to assess the predictive value of HbA1c and lipid variability on the risks of sudden cardiac death (SCD) and incident atrial fibrillation (AF). Methods The retrospective observational study consists of type 2 diabetic patients prescribed with insulin, who went to publicly funded clinics and hospitals in Hong Kong between January 1, 2009 and December 31, 2009. Variability in total cholesterol, low-density lipoprotein-cholesterol (LDL-C), high-density lipoprotein-cholesterol (HDL-C), triglyceride, and HbA1c were assessed through their SD and coefficient of variation. The primary outcomes were incident (1) ventricular tachycardia/ventricular fibrillation, actual or aborted SCD and (2) AF. Results A total of 23 329 patients (mean ± SD age: 64 ± 14 years old; 51% male; mean HbA1c 8.6 ± 1.3%) were included. On multivariable analysis, HbA1c, total cholesterol, LDL-C and triglyceride variability were found to be predictors of SCD (p < .05). Conclusion HbA1c and lipid variability were predictive of SCD. Therefore, poor glucose control and variability in lipid parameters in diabetic patients are associated with aborted or actual SCD. These observations suggest the need to re-evaluate the extent of glycemic control required for outcome optimization

Treatment with Methylphenidate for Attention Deficit Hyperactivity Disorder (ADHD) and the Risk of All-Cause Poisoning in Children and Adolescents:A Self-Controlled Case Series Study

BACKGROUND: Children and adolescents with attention deficit hyperactivity disorder (ADHD) are at higher risk of all-cause poisoning by drugs and chemicals (intentional or accidental). Currently, there is limited data on whether medication treatment for ADHD can reduce the risk of all-cause poisoning. METHODS: Patients aged 5–18 years with a methylphenidate (MPH) prescription and an incident poisoning diagnosis between January 2001 and June 2020 were identified from the Hong Kong Clinical Data Analysis and Reporting System. A self-controlled case series study design was used to compare the incidence rate ratios (IRRs) of all-cause poisoning during different risk windows (30 days before the first MPH prescription, exposure periods within 30 days of the first prescription, and periods of subsequent exposure) compared with the reference window (other non-exposure periods). RESULTS: 42,203 patients were prescribed ADHD medication in Hong Kong during the study period. Of these, 417 patients who had both an MPH prescription and poisoning incident recorded were included in the main analysis. Compared with other non-exposed periods, a higher risk of poisoning was found in the 30 days before the first prescription (IRR 2.64, 95% confidence interval [CI] 1.33–5.22) and exposure periods within 30 days of the first prescription (IRR 2.18, 95% CI 1.06–4.48), but not during prolonged exposure. However, compared with 30 days before the first prescription as well as exposure periods within 30 days of the first prescription, there was a lower risk during the subsequent exposure (IRRs 0.49 and 0.60, respectively). Similar results to the main analysis were also found in the subgroup analysis of intentional poisoning and females, but not in that of accidental poisoning and males. CONCLUSIONS: The risk of all-cause poisoning was higher shortly before and after the first MPH prescription and became lower during the subsequent prescription period. Our results do not support an association between the use of MPH and an increased risk of all-cause poisoning in children and adolescents and, in fact, suggest that longer-term use of MPH may be associated with a lower risk of all-cause poisoning, although this latter finding requires further study. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40263-021-00824-x

Identifying dementia from cognitive footprints in hospital records among Chinese older adults: a machine-learning study

Background: By combining theory-driven and data-driven methods, this study aimed to develop dementia predictive algorithms among Chinese older adults guided by the cognitive footprint theory. Methods: Electronic medical records from the Clinical Data Analysis and Reporting System in Hong Kong were employed. We included patients with dementia diagnosed at 65+ between 2010 and 2018, and 1:1 matched dementia-free controls. We identified 51 features, comprising exposures to established modifiable factors and other factors before and after 65 years old. The performances of four machine learning models, including LASSO, Multilayer perceptron (MLP), XGBoost, and LightGBM, were compared with logistic regression models, for all patients and subgroups by age. Findings: A total of 159,920 individuals (40.5% male; mean age [SD]: 83.97 [7.38]) were included. Compared with the model included established modifiable factors only (area under the curve [AUC] 0.689, 95% CI [0.684, 0.694]), the predictive accuracy substantially improved for models with all factors (0.774, [0.770, 0.778]). Machine learning and logistic regression models performed similarly, with AUC ranged between 0.773 (0.768, 0.777) for LASSO and 0.780 (0.776, 0.784) for MLP. Antipsychotics, education, antidepressants, head injury, and stroke were identified as the most important predictors in the total sample. Age-specific models identified different important features, with cardiovascular and infectious diseases becoming prominent in older ages. Interpretation: The models showed satisfactory performances in identifying dementia. These algorithms can be used in clinical practice to assist decision making and allow timely interventions cost-effectively

Use of multiple antidiabetic medications in patients with diabetes and its association with hypoglycaemic events

OBJECTIVE: To assess whether the use of multiple antidiabetic medications is associated with an increased risk of hypoglycaemia in patients with type 2 diabetes mellitus. DESIGN: A case-crossover study. SETTING: Cases were enrolled from the National Center for Diabetes, Endocrinology and Genetics in Amman, Jordan. PARTICIPANTS: Patients were those with diabetes mellitus and reported incident of a hypoglycaemic event in their medical records during the period January 2007 to July 2017. Patients with multiple antidiabetic medications were those with at least two antidiabetic medications. PRIMARY OUTCOME: History of antidiabetic medication use was extracted from the pharmacy records. The use of multiple antidiabetic medications during the risk window (before hypoglycaemia) was compared with a control window(s) (earlier time) of the same length after a washout period. Conditional logistic regression was applied to evaluate the OR of hypoglycaemia between the treatment groups. A secondary analysis was performed in patients with a blood glucose measurement of ≤70 mg/dL. RESULTS: 182 patients (106 females, 58.2%) were included in the study with an average age of 59.9 years (SD=9.9). The patients' average body mass index was 31.7 kg/m2 (SD=6.2). Compared with monotherapy, the OR of hypoglycaemic events for patients with multiple antidiabetic medications was 5.00 (95% CI 1.10 to 22.82). The OR was 6.00 (95% CI 0.72 to 49.84) for the secondary analysis patient group (n=94). Ten-fold increased risk was found in patients (n=155) with insulin and sulfonylurea-based combination therapy (OR 10.00;95% CI 1.28 to 78.12). CONCLUSION: This study shows that the use of multiple antidiabetic medications appears to increase the risk of hypoglycaemic events. Patients and healthcare professionals should be extra vigilant when patients are on multiple antidiabetic medications therapy, especially the combination of sulfonylurea and insulin

Probing the Reactivity of the Ce=O Multiple Bond in a Cerium(IV) Oxo Complex

The reactivity of the cerium­(IV) oxo complex [(L_OEt)₂Ce^IV(O)­(H₂O)]·MeC­(O)­NH₂ (<b>1</b>; L_OEt^– = [CoCp­{P­(O)­(OEt)₂}₃]⁻, where Cp = η⁵-C₅H₅) toward electrophiles and Brønsted acids has been investigated. The treatment of <b>1</b> with acetic anhydride afforded the diacetate complex [Ce^IV(L_OEt)₂(O₂CMe)₂] (<b>2</b>). The reaction of <b>1</b> with B­(C₆F₅)₃ yielded [Ce^IV(L_OEt)₂(Me₂CONH₂)₂]­[B­(C₆F₅)₃(OH)]₂ (<b>3</b>), in which the [B­(C₆F₅)₃(OH)]⁻ anions are H-bonded to the O-bound acetamide ligands. The treatment of <b>1</b> with HCl and HNO₃ afforded [Ce^IV(L_OEt)₂Cl₂] and [Ce^IV(L_OEt)₂(NO₃)₂], respectively. Protonation of <b>1</b> with triflic acid (HOTf) gave the diaqua complex [Ce^IV(L_OEt)₂(H₂O)₂]­(OTf)₂ (<b>4</b>), in which the triflate anions are H-bonded to the two aqua ligands. The treatment of <b>1</b> with phenol afforded the phenoxide complex [Ce^IV(L_OEt)₂(OPh)₂] (<b>5</b>). The oxo-bridged bimetallic complex [(L_OEt)₂(Me₂CONH₂)­Ce^IV(O)­NaL_OEt] (<b>6</b>) with the Ce–O_oxo and Na–O_oxo distances of 1.953(4) and 2.341(4) Å, respectively, was obtained from the reaction of <b>1</b> with [NaL_OEt]. Density functional theory calculations showed that the model complex [(L_OMe)₂Ce^IV(Me₂CONH₂)­(O)­NaL_OMe] (<b>6A</b>; L_OMe^– = [CoCp­{P­(O)­(OMe)₂}₃]⁻) contains a polarized CeO multiple bond. The energy for dissociation of the {NaL_OMe} fragment from <b>6A</b> in acetonitrile was calculated to be +33.7 kcal/mol, which is higher than that for dissociation of the H-bonded acetamide from [(L_OMe)₂Ce^IV(O)­(H₂O)]·MeC­(O)­NH₂ (<b>1A</b>) (calculated to be +17.4 kcal/mol). In hexanes containing trace water, complex <b>1</b> decomposed readily to a mixture of a tetranuclear cerium­(IV) oxo cluster, [Ce^IV₄(L_OEt)₄(μ₄-O)­(μ₂-O)₄(μ₂-OH)₂] (<b>7</b>), and a cerium­(III) complex, [Ce^III(L_OEt)₂(H₂O)₂]­[L_OEt] [<b>8</b>(L_OEt)], whereas the cerium/sodium oxo complex <b>6</b> is stable under the same conditions. The crystal structures of <b>3</b>, <b>4</b>·H₂O, <b>6</b>, and <b>8</b>(L_OEt) have been determined

Specific two-photon imaging of live cellular and deep-tissue lipid droplets by lipophilic AIEgens at ultra-low concentration

Lipid droplets are highly associated with obesity, diabetes, inflammatory disorders and cancer. A reliable two-photon dye for specific lipid droplets imaging in live cells and live tissues at ultra-low concentration has rarely been reported. In this work, four new aggregation-induced emission luminogens (AIEgens) based on the naphthalene core were designed and synthesized for specific two-photon lipid droplets staining. The new molecules, namely NAP AIEgens, exhibit large Stokes shift (>110 nm), high solid-state fluorescence quantum yield (up to 30%), good two-photon absorption cross section (45–100 GM at 860 nm), high biocompatibility and good photostability. They could specifically stain lipid droplets at ultra-low concentration (50 nM) in a short time of 15 min. Such ultra-low concentration is the lowest value for lipid droplets staining in live cells reported so far. In vitro and ex vivo two-photon imaging of lipid droplets in live cells and live mice liver tissues were successfully demonstrated. In addition, selective visualization of lipid droplets in live mice liver tissues could be achieved at a depth of about 70 μm. These excellent properties render them as promising candidates for investigating lipid droplets-associated physiological and pathological processes in live biological samples

Risks of COVID-19-related hospitalisation and mortality among individuals with mental disorders following BNT162b2 and CoronaVac vaccinations: A case-control study

Concerns have been raised regarding potential weaker vaccine immunogenicity with higher immune suppression for individuals with pre-existing mental disorders. Yet, data on the effectiveness of COVID-19 vaccinations among this vulnerable population are limited. A case-control study was conducted to investigate the risks of COVID-19-related hospitalisation and mortality among individuals with mental disorders following one to three doses of BNT162b2 and CoronaVac vaccinations in Hong Kong. Data were extracted from electronic health records, vaccination and COVID-19 confirmed case records. Conditional logistic regression was applied with adjustment for comorbidities and medication history. Subgroup analyses were performed with stratification: by age (< 65 and ≥ 65) and mental disorders diagnosis (depression, schizophrenia, anxiety disorder, and bipolar disorder). Two doses of BNT162b2 and CoronaVac significantly reduced COVID-19-related hospitalisation and mortality. Further protection for both outcomes was provided after three doses of BNT162b2 and CoronaVac. The vaccine effectiveness magnitude of BNT162b2 was generally higher than CoronaVac, but the difference diminished after the third dose. Individuals with mental disorders should be prioritised in future mass vaccination programmes of booster doses or bivalent COVID-19 vaccines. Targeted strategies should be developed to resolve the reasons behind vaccine hesitancy among this population and increase their awareness on the benefits of vaccination