An evaluation of paediatric medicines reconciliation at hospital discharge into the community

OBJECTIVE: A UK national survey of primary care physicians has indicated that the medication information on hospital discharge summary was incomplete or inaccurate most of the time. Internationally, studies have shown that hospital pharmacist's interventions reduce these discrepancies in the adult population. There have been no published studies on the incidence and severity of the discrepancies of the medication prescribed for children specifically at discharge to date. The objectives of this study were to investigate the incidence, nature and potential clinical severity of medication discrepancies at the point of hospital discharge in a paediatric setting. METHODS: Five weeks prospective review of hospital discharge letters was carried out. Medication discrepancies between the initial doctor's discharge letter and finalised drug chart were identified, pharmacist changes were recorded and their severity was assessed. The setting of the review was at a London, UK paediatric hospital providing local secondary and specialist tertiary care. The outcome measures were: - incidence and the potential clinical severity of medication discrepancies identified by the hospital pharmacist at discharge. KEY FINDINGS: 142 patients (64 female and 78 males, age range 1 month - 18 years) were discharged on 501 medications. The majority of patients were under the care of general surgery and general paediatric teams. One in three discharge letters contained at least one medication discrepancy and required pharmacist interventions to rectify prior to completion. Of these, 1 in 10 had the potential for patient harm if undetected. CONCLUSIONS: Medicines reconciliation by pharmacist at discharge may be a good intervention in preventing medication discrepancies which have the potential to cause moderate harm in paediatric patients

Cost-Effectiveness of Poly ADP-Ribose Polymerase Inhibitors in Cancer Treatment: A Systematic Review

Background: PARP inhibitors have shown significant improvement in progression-free survival, but their costs cast a considerable financial burden. In line with value-based oncology, it is important to evaluate whether drug prices justify the outcomes. / Objectives: The aim of the study was to systematically evaluate PARP inhibitors on 1) cost-effectiveness against the standard care, 2) impact on cost-effectiveness upon stratification for genetic characteristics, and 3) identify factors determining their cost-effectiveness, in four cancer types. / Methods: We systematically searched PubMed, EMBASE, Web of Science, and Cochrane Library using designated search terms, updated to 31 August 2021. Trial-based or modeling cost-effectiveness analyses of four FDA-approved PARP inhibitors were eligible. Other studies known to authors were included. Reference lists of selected articles were screened. Eligible studies were assessed for methodological and reporting quality before review. / Results: A total of 20 original articles proceeded to final review. PARP inhibitors were not cost-effective as recurrence maintenance in advanced ovarian cancer despite improved performance upon genetic stratification. Cost-effectiveness was achieved when moved to upfront maintenance in a new diagnosis setting. Limited evidence indicated non–cost-effectiveness in metastatic breast cancer, mixed conclusions in metastatic pancreatic cancer, and cost-effectiveness in metastatic prostate cancer. Stratification by genetic testing displayed an effect on cost-effectiveness, given the plummeting ICER values when compared to the “treat-all” strategy. Drug cost was a strong determinant for cost-effectiveness in most models. / Conclusions: In advanced ovarian cancer, drug use should be prioritized for upfront maintenance and for patients with BRCA mutation or BRCAness at recurrence. Additional economic evaluations are anticipated for novel indications

Glycemic and lipid variability for predicting complications and mortality in diabetes mellitus using machine learning

Introduction Recent studies have reported that HbA1c and lipid variability is useful for risk stratification in diabetes mellitus. The present study evaluated the predictive value of the baseline, subsequent mean of at least three measurements and variability of HbA1c and lipids for adverse outcomes. Methods This retrospective cohort study consists of type 1 and type 2 diabetic patients who were prescribed insulin at outpatient clinics of Hong Kong public hospitals, from 1st January to 31st December 2009. Standard deviation (SD) and coefficient of variation were used to measure the variability of HbA1c, total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and triglyceride. The primary outcome is all-cause mortality. Secondary outcomes were diabetes-related complications. Result The study consists of 25,186 patients (mean age = 63.0, interquartile range [IQR] of age = 15.1 years, male = 50%). HbA1c and lipid value and variability were significant predictors of all-cause mortality. Higher HbA1c and lipid variability measures were associated with increased risks of neurological, ophthalmological and renal complications, as well as incident dementia, osteoporosis, peripheral vascular disease, ischemic heart disease, atrial fibrillation and heart failure (p <  0.05). Significant association was found between hypoglycemic frequency (p <  0.0001), HbA1c (p <  0.0001) and lipid variability against baseline neutrophil-lymphocyte ratio (NLR). Conclusion Raised variability in HbA1c and lipid parameters are associated with an elevated risk in both diabetic complications and all-cause mortality. The association between hypoglycemic frequency, baseline NLR, and both HbA1c and lipid variability implicate a role for inflammation in mediating adverse outcomes in diabetes, but this should be explored further in future studies

Development of a predictive risk model for all-cause mortality in patients with diabetes in Hong Kong

Introduction Patients with diabetes mellitus are risk of premature death. In this study, we developed a machine learning-driven predictive risk model for all-cause mortality among patients with type 2 diabetes mellitus using multiparametric approach with data from different domains. Research design and methods This study used territory-wide data of patients with type 2 diabetes attending public hospitals or their associated ambulatory/outpatient facilities in Hong Kong between January 1, 2009 and December 31, 2009. The primary outcome is all-cause mortality. The association of risk variables and all-cause mortality was assessed using Cox proportional hazards models. Machine and deep learning approaches were used to improve overall survival prediction and were evaluated with fivefold cross validation method. Results A total of 273 678 patients (mean age: 65.4±12.7 years, male: 48.2%, median follow-up: 142 (IQR=106–142) months) were included, with 91 155 deaths occurring on follow-up (33.3%; annualized mortality rate: 3.4%/year; 2.7 million patient-years). Multivariate Cox regression found the following significant predictors of all-cause mortality: age, male gender, baseline comorbidities, anemia, mean values of neutrophil-to-lymphocyte ratio, high-density lipoprotein-cholesterol, total cholesterol, triglyceride, HbA1c and fasting blood glucose (FBG), measures of variability of both HbA1c and FBG. The above parameters were incorporated into a score-based predictive risk model that had a c-statistic of 0.73 (95% CI 0.66 to 0.77), which was improved to 0.86 (0.81 to 0.90) and 0.87 (0.84 to 0.91) using random survival forests and deep survival learning models, respectively. Conclusions A multiparametric model incorporating variables from different domains predicted all-cause mortality accurately in type 2 diabetes mellitus. The predictive and modeling capabilities of machine/deep learning survival analysis achieved more accurate predictions

Predictive scores for identifying patients with type 2 diabetes mellitus at risk of acute myocardial infarction and sudden cardiac death

Introduction The present study evaluated the application of incorporating non-linear J/U-shaped relationships between mean HbA1c and cholesterol levels into risk scores for predicting acute myocardial infarction (AMI) and non-AMI-related sudden cardiac death (SCD) respectively, amongst patients with type 2 diabetes mellitus. Methods This was a territory-wide cohort study of patients with type 2 diabetes mellitus above the age 40 and free from prior AMI and SCD, with or without prescriptions of anti-diabetic agents between January 1st, 2009 to December 31st, 2009 at government-funded hospitals and clinics in Hong Kong. Patients recruited were followed up until 31 December 2019 or their date of death. Risk scores were developed for predicting incident AMI and non-AMI-related SCD. The performance of conditional inference survival forest (CISF) model compared to that of random survival forests (RSF) model and multivariate Cox model. Results This study included 261 308 patients (age = 66.0 ± 11.8 years old, male = 47.6%, follow-up duration = 3552 ± 1201 days, diabetes duration = 4.77 ± 2.29 years). Mean HbA1c and low high-density lipoprotein-cholesterol (HDL-C) were significant predictors of AMI on multivariate Cox regression. Mean HbA1c was linearly associated with AMI, whilst HDL-C was inversely associated with AMI. Mean HbA1c and total cholesterol were significant multivariate predictors with a J-shaped relationship with non-AMI-related SCD. The AMI and SCD risk scores had an area under the curve (AUC) of 0.666 (95% confidence interval (CI) = [0.662, 0.669]) and 0.677 (95% CI = [0.673, 0.682]), respectively. CISF significantly improves prediction performance of both outcomes compared to RSF and multivariate Cox models. Conclusion A holistic combination of demographic, clinical and laboratory indices can be used for the risk stratification of patients with type 2 diabetes mellitus for AMI and SCD

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

Paediatric/young versus adult patients with long QT syndrome

Introduction Long QT syndrome (LQTS) is a less prevalent cardiac ion channelopathy than Brugada syndrome in Asia. The present study compared the outcomes between paediatric/young and adult LQTS patients. Methods This was a population-based retrospective cohort study of consecutive patients diagnosed with LQTS attending public hospitals in Hong Kong. The primary outcome was spontaneous ventricular tachycardia/ventricular fibrillation (VT/VF). Results A total of 142 LQTS (mean onset age=27±23 years old) were included. Arrhythmias other than VT/VF (HR 4.67, 95% CI (1.53 to 14.3), p=0.007), initial VT/VF (HR=3.25 (95% CI 1.29 to 8.16), p=0.012) and Schwartz score (HR=1.90 (95% CI 1.11 to 3.26), p=0.020) were predictive of the primary outcome for the overall cohort, while arrhythmias other than VT/VF (HR=5.41 (95% CI 1.36 to 21.4), p=0.016) and Schwartz score (HR=4.67 (95% CI 1.48 to 14.7), p=0.009) were predictive for the adult subgroup (>25 years old; n=58). A random survival forest model identified initial VT/VF, Schwartz score, initial QTc interval, family history of LQTS, initially asymptomatic and arrhythmias other than VT/VF as the most important variables for risk prediction. Conclusion Clinical and ECG presentation varies between the paediatric/young and adult LQTS population. Machine learning models achieved more accurate VT/VF prediction

Evaluation of the risk of cardiovascular events with clarithromycin using both propensity score and self-controlled study designs

Aim: Some previous studies suggest a long term association between clarithromycin use and cardiovascular events. This study investigates this association for clarithromycin given as part of Helicobacter pylori treatment (HPT). Methods: Our source population was the Clinical Practice Research Datalink (CPRD), a UK primary care database. We conducted a self-controlled case series (SCCS), a case–time–control study (CTC) and a propensity score adjusted cohort study comparing the rate of cardiovascular events in the 3 years after exposure to HPT containing clarithromycin with exposure to clarithromycin free HPT. Outcomes were first incident diagnosis of myocardial infarction (MI), arrhythmia and stroke. For the cohort analysis we included secondary outcomes all cause and cardiovascular mortality. Results: Twenty-eight thousand five hundred and fifty-two patients were included in the cohort. The incidence rate ratio of first MI within 1 year of exposure to HPT containing clarithromycin was 1.07 (95% CI 0.85, 1.34, P = 0.58) and within 90 days was 1.43 (95% CI 0.99, 2.09 P = 0.057) in the SCCS analysis. CTC and cohort results were consistent with these findings. Conclusions There was some evidence for a short term association for first MI but none for a long term association for any outcome

Ventricular tachyarrhythmia risk in paediatric/young vs. adult Brugada syndrome patients: a territory-wide study

Introduction: Brugada syndrome (BrS) is a cardiac ion channelopathy with a higher prevalence in Asia compared to the Western populations. The present study compared the differences in clinical and electrocardiographic (ECG) presentation between paediatric/young (≤25 years old) and adult (>25 years) BrS patients. Method: This was a territory-wide retrospective cohort study of consecutive BrS patients presenting to public hospitals in Hong Kong. The primary outcome was spontaneous ventricular tachycardia/ventricular fibrillation (VT/VF). Results: The cohort consists of 550 consecutive patients (median age of initial presentation = 51 ± 23 years; female = 7.3%; follow-up period = 83 ± 80 months), divided into adult (n = 505, mean age of initial presentation = 52 ± 19 years; female = 6.7%; mean follow-up period = 83 ± 80 months) and paediatric/young subgroups (n = 45, mean age of initial presentation = 21 ± 5 years, female = 13.3%, mean follow-up period = 73 ± 83 months). The mean annual VT/VF incidence rate were 17 and 25 cases per 1,000 patient-year, respectively. Multivariate analysis showed that initial presentation of type 1 pattern (HR = 1.80, 95% CI = [1.02, 3.15], p = 0.041), initial asymptomatic presentation (HR = 0.26, 95% CI = [0.07, 0.94], p = 0.040) and increased P-wave axis (HR = 0.98, 95% CI = [0.96, 1.00], p = 0.036) were significant predictors of VT/VF for the adult subgroup. Only initial presentation of VT/VF was predictive (HR = 29.30, 95% CI = [1.75, 492.00], p = 0.019) in the paediatric/young subgroup. Conclusion: Clinical and ECG presentation of BrS vary between the paediatric/young and adult population in BrS. Risk stratification and management strategies for younger patients should take into consideration and adopt an individualised approach

Adverse Cardiovascular Complications following prescription of programmed cell death 1 (PD-1) and programmed cell death ligand 1 (PD-L1) inhibitors: a propensity-score matched Cohort Study with competing risk analysis

Background Programmed death-1 (PD-1) and programmed death- ligand 1 (PD-L1) inhibitors, such as pembrolizumab, nivolumab and atezolizumab, are major classes of immune checkpoint inhibitors that are increasingly used for cancer treatment. However, their use is associated with adverse cardiovascular events. We examined the incidence of new-onset cardiac complications in patients receiving PD-1 or PD-L1 inhibitors. Methods Patients receiving PD-1 or PD-L1 inhibitors since their launch up to 31st December 2019 at publicly funded hospitals of Hong Kong, China, without pre-existing cardiac complications were included. The primary outcome was a composite of incident heart failure, acute myocardial infarction, atrial fibrillation, or atrial flutter with the last follow-up date of 31st December 2020. Propensity score matching between PD-L1 inhibitor use and PD-1 inhibitor use with a 1:2 ratio for patient demographics, past comorbidities and non-PD-1/PD-L1 medications was performed with nearest neighbour search strategy (0.1 caliper). Univariable and multivariable Cox regression analysis models were conducted. Competing risks models and multiple propensity matching approaches were considered for sensitivity analysis. Results A total of 1959 patients were included. Over a median follow-up of 247 days (interquartile range [IQR]: 72-506), 320 (incidence rate [IR]: 16.31%) patients met the primary outcome after PD-1/PD-L1 treatment: 244 (IR: 12.57%) with heart failure, 38 (IR: 1.93%) with acute myocardial infarction, 54 (IR: 2.75%) with atrial fibrillation, 6 (IR: 0.31%) with atrial flutter. Compared with PD-1 inhibitor treatment, PD-L1 inhibitor treatment was significantly associated with lower risks of the composite outcome both before (hazard ratio [HR]: 0.32, 95% CI: [0.18-0.59], P value=0.0002) and after matching (HR: 0.34, 95% CI: [0.18-0.65], P value=0.001), and lower all-cause mortality risks before matching (HR: 0.77, 95% CI: [0.64-0.93], P value=0.0078) and after matching (HR: 0.80, 95% CI: [0.65-1.00], P value=0.0463). Patients who developed cardiac complications had shorter average readmission intervals and a higher number of hospitalizations after treatment with PD-1/PD-L1 inhibitors in both the unmatched and matched cohorts (P value<0.0001). Multivariable Cox regression models, competing risk analysis with cause-specific and subdistribution hazard models, and multiple propensity approaches confirmed these observations. Conclusions Compared with PD-1 treatment, PD-L1 treatment was significantly associated with lower risk of new onset cardiac complications and all-cause mortality both before and after propensity score matching