INTRODUCTION
The severe consequences of acute kidney injury (AKI) have been well-documented in high-risk patient populations. However, the effects of milder forms in non-critically ill patients remain understudied, particularly in resource-limited settings. While the risk of mortality associated with these cases is considered low, it can still lead to various complications including prolonged hospitalization, which may influence long-term renal and patient survival. Hence, the objective of this study was to study the impact of non-dialysis-requiring AKI (NDR-AKI) on survival outcomes of non-critically ill medical patients admitted to St. Paul’s Hospital Millennium Medical College in Ethiopia during the period from July 2019 to January 2022.
METHODS
A retrospective cohort study was conducted among 300 non-critically ill medical patients, 93 with NDR-AKI and 207 without AKI. Descriptive statistics, including frequency distributions and median survival times, were employed to summarize the data. Kaplan-Meier curves and the log-rank test were utilized to compare survival experiences of groups. A Cox proportional hazards survival model was fitted to estimate the impact of NDR-AKI on time to recovery. Adjusted hazard ratio (AHR) with 95% confidence interval (CI) was used to report findings.
RESULTS
Two hundred four (68.0%) were discharged after improvement and the median recovery time was 16 days (95%CI: 13.5-18.5 days). Having NDR-AKI was associated with a 43% lower rate of achieving recovery (AHR=0.57, 95%CI=0.38, 0.84, p-value=0.004). Females were found to have a 1.41 times higher rate of recovery (AHR=1.41, 95%CI=1.03,1.94, p-value=0.033). Additionally, having tuberculosis (AHR=0.41, 95%CI=0.23,0.72, p-value=0.002) and being on anticoagulant (AHR=0.67, 95%CI=0.47,0.95, p-value=0.027) were associated with a 59% and 33% lower rate of recovery, respectively.
CONCLUSION
NDR-AKI significantly delays recovery compared to patients without AKI suggesting that even milder forms of AKI in non-critically ill patients can negatively impact patient outcomes. Early identification, prompt management, and addressing underlying causes are key to improving recovery and reducing long-term morbidity and mortality. Strict screening and monitoring of high-risk groups such as men, patients with tuberculosis, and those on anticoagulants is also crucial.
AIMS
Most glucose self-monitoring devices have been developed with high-income countries in mind. We developed a target product profile (TPP) for new glucose self-monitoring technologies for users in low- and middle-income countries (LMICs).
METHODS
A draft TPP including 39 characteristics was developed by an expert group including diabetes specialists, device specialists, and people with diabetes, incorporating findings from qualitative research in LMICs. Each characteristic had minimal and optimal requirements for two use cases, frequent and sporadic use. Characteristics requiring refinement were identified via online survey. Characteristics with agreement level <90% for any requirement were reviewed by the expert group and amended as appropriate.
RESULTS
One characteristic (shelf life) had agreement <75% (both requirements for both use cases). Characteristics with agreement ≥75% and <90% for the frequent use case included infrastructure level, measurement cycle, duration of use before replacement, interchangeability, and calibration (both requirements), and activity log and price per month to end payer (minimal requirement). Intended use (both requirements), accuracy, and price per month to end payer (optimal requirement) had agreement ≥75% and <90% for the sporadic use case.
CONCLUSIONS
This TPP will inform developers on requirements for glucose self-monitoring technologies for LMICs, and support decision-makers in evaluating existing devices.
The burden of diabetes is growing worldwide. The costs associated with diabetes put substantial pressure on patients and health budgets, especially in low- and middle-income countries. The prices of diabetes medicines are a key determinant for access, yet little is known about the association between manufacturing costs and current market prices.
OBJECTIVES
To estimate the cost of manufacturing insulins, sodium-glucose cotransporter 2 inhibitors (SGLT2Is), and glucagonlike peptide 1 agonists (GLP1As), derive sustainable cost-based prices (CBPs), and compare these with current market prices.
DESIGN, SETTING, AND PARTICIPANTS
In this economic evaluation, the cost of manufacturing insulins, SGLT2Is, and GLP1As was modeled. Active pharmaceutical ingredient cost per unit (weighted least-squares regression model using data from a commercial database of trade shipments, data from January 1, 2016, to March 31, 2023) was combined with costs of formulation and other operating expenses, plus a profit margin with an allowance for tax, to estimate CBPs. Cost-based prices were compared with current prices in 13 countries, collected in January 2023 from public databases. Countries were selected to provide representation of different income levels and geographic regions based on the availability of public databases.
MAIN OUTCOMES AND MEASURES
Estimated CBPs; lowest current market prices (2023 US dollars).
RESULTS
In this economic evaluation of manufacturing costs, estimated CBPs for treatment with insulin in a reusable pen device could be as low as $96 (human insulin) or $111 (insulin analogues) per year for a basal-bolus regimen, $61 per year using twice-daily injections of mixed human insulin, and $50 (human insulin) or $72 (insulin analogues) per year for a once-daily basal insulin injection (for type 2 diabetes), including the cost of injection devices and needles. Cost-based prices ranged from $1.30 to $3.45 per month for SGLT2Is (except canagliflozin: $25.00-$46.79) and from $0.75 to $72.49 per month for GLP1As. These CBPs were substantially lower than current prices in the 13 countries surveyed.
CONCLUSIONS AND RELEVANCE
High prices limit access to newer diabetes medicines in many countries. The findings of this study suggest that robust generic and biosimilar competition could reduce prices to more affordable levels and enable expansion of diabetes treatment globally.
This study seeks to confirm the risk factors linked to cardiovascular (CV) events in chronic kidney disease (CKD), which have been identified as CKD-related. We aim to achieve this using a larger, more diverse, and nationally representative dataset, contrasting with previous research conducted on smaller patient cohorts.
METHODS
The study utilized the nationwide inpatient sample database to identify adult hospitalizations for CKD from 2016 to 2020, employing validated ICD-10-CM/PCS codes. A comprehensive literature review was conducted to identify both traditional and CKD-specific risk factors associated with CV events. Risk factors and CV events were defined using a combination of ICD-10-CM/PCS codes and statistical commands. Only risk factors with specific ICD-10 codes and hospitalizations with complete data were included in the study. CV events of interest included cardiac arrhythmias, sudden cardiac death, acute heart failure, and acute coronary syndromes. Univariate and multivariate regression models were employed to evaluate the association between CKD-specific risk factors and CV events while adjusting for the impact of traditional CV risk factors such as old age, hypertension, diabetes, hypercholesterolemia, inactivity, and smoking.
RESULTS
A total of 690,375 hospitalizations for CKD were included in the analysis. The study population was predominantly male (375,564, 54.4%) and mostly hospitalized at urban teaching hospitals (512,258, 74.2%). The mean age of the study population was 61 years (SD 0.1), and 86.7% (598,555) had a Charlson comorbidity index (CCI) of 3 or more. At least one traditional risk factor for CV events was present in 84.1% of all CKD hospitalizations (580,605), while 65.4% (451,505) included at least one CKD-specific risk factor for CV events. The incidence of CV events in the study was as follows: acute coronary syndromes (41,422; 6%), sudden cardiac death (13,807; 2%), heart failure (404,560; 58.6%), and cardiac arrhythmias (124,267; 18%). A total of 91.7% (113,912) of all cardiac arrhythmias were atrial fibrillations. Significant odds of CV events on multivariate analyses included: malnutrition (aOR: 1.09; 95% CI: 1.06-1.13; p<0.001), post-dialytic hypotension (aOR: 1.34; 95% CI: 1.26-1.42; p<0.001), thrombophilia (aOR: 1.46; 95% CI: 1.29-1.65; p<0.001), sleep disorder (aOR: 1.17; 95% CI: 1.09-1.25; p<0.001), and post-renal transplant immunosuppressive therapy (aOR: 1.39; 95% CI: 1.26-1.53; p<0.001).
CONCLUSION
The study confirmed the predictive reliability of malnutrition, post-dialytic hypotension, thrombophilia, sleep disorders, and post-renal transplant immunosuppressive therapy, highlighting their association with increased risk for CV events in CKD patients. No significant association was observed between uremic syndrome, hyperhomocysteinemia, hyperuricemia, hypertriglyceridemia, leptin levels, carnitine deficiency, anemia, and the odds of experiencing CV events.