Time to acute kidney injury and its predictors among newly diagnosed Type 2 diabetic patients at government hospitals in Harari Region, East Ethiopia

Outcome and Determining Characteristics of ICU Patients with Acute Kidney Injury in a Low-Income Country, a Multicenter Experience

Background

Acute kidney injury (AKI) is a disease that affects millions of people globally making it a major public health concern. It is defined as an abrupt decrease in kidney function that occurs within ours affecting both the structure and functionality of the kidneys.The outcome of AKI and the determinants in Nigeria are largely unknown. This study aimed to describe the determining factors of the outcome of AKI patients admitted into the ICU of three tertiary health institutions in Northeast Nigeria.

Methods

The study is a prospective multicentered observational study of the patients admitted into the ICU in three tertiary health institutions from January 2022 to December 2023. KDIGO criteria was used to define AKI. The outcome of the study was to determine survivors among the patients admitted into the ICU with AKI or developed AKI while in ICU and also the determinants of mortality. A chi-square test was done to determine the association between the dependent variable (patient outcome) and the independent variables. To determine the predictors of patient outcomes, a regression analysis was done. The sociodemographic data of the patients admitted during these periods were studied in addition to Acute Physiology and Chronic Health Evaluation (APACHE) II, Kidney Disease: Improving Global Outcomes (KDIGO), Average length of stay in the ICU, Admitting/referring ward (Obstetrics, Gynae, Medical, Surgical or Emergency unit), Ability to afford care (out of pocket payment, social welfare or through Health insurance Scheme, Co-morbidity (presence or absence of comorbidity), Interventions done while in ICU (use of vasopressors and inotropes, mechanical ventilation (MV) support and renal replacement therapy (RRT) and outcome (discharge to the wards or mortality).

Results

Of 1494 patient records screened, 464 met the inclusion criteria. The overall incidence of AKI was 57%. About 53% were females, the mean age was 42.2 years, and 81% of the patients had a normal BMI (18.5 - 24.9). About 40% of the patients had APACHE II scores ≥ 29%. More than three-quarters (79.5%) of the patients paid for their health care expenditure out-of-pocket. Most patients (72%) were from the Medical and Gynae/Ward. Mortality was highest (54.2%) among patients who were brought into the ICU from the Medical ward. Most patients admitted were KDIGO I (44.3%) followed by KDIGO II (35.1%). Among the patients, 61.2% present with one or more comorbidity. Mortality was higher (50%) among those with comorbidity compared to 13.6% among those without comorbidity. Mortality was lowest among patients who stayed in the ICU between 8-14 days compared to those who stayed > 2 weeks. Most of the patients (72%) were from the Medical and Gynae/Ward. Mortality was highest (54.2%) among patients who were brought into the ICU from the Medical ward followed by those brought in from the Obstetric and Gynecological ward (20.4%). An association was found between the intervention received in the ICU and the outcome, which was found to be statistically significant (p < 0.001). A regression analysis was done to determine the predictors of patients' outcomes admitted in the ICU. The results showed that APACHE II score greater than 10 (p-value < 0.001), presence of comorbidities (p = 0.031) and intervention which included a combination of Vasopressors, mechanical ventilation and RRT (p < 0.01) are the predictors of patients' outcome. The regression model is valid (X2 = 469.894, df = 24, p < 0.001) and it fits the sample as shown by the Hosmer and Lemeshow test (X2 = 7.749, p = 0.45, df = 8,). It also shows that the predictors account for 92% of patients' outcomes (Nagelkerke R2 = 0.92).

Conclusions

Our study revealed that the presence of comorbidity, high APACHE II score, and the need for interventional supports including both mechanical ventilatory and ionotropic, were found to be strong mortality predictors in patients with AKI.

Hospital-Acquired Acute Kidney Injury in Non-Critical Medical Patients in a Developing Country Tertiary Hospital: Incidence and Predictors

Background

Acute kidney injury (AKI) is a frequent complication in critical patients, leading to a worse prognosis. Although its consequences are worse among critical patients, AKI is also associated with less favorable outcomes in non-critical patients. Therefore, understanding the magnitude of the problem in these patients is crucial, yet there is a scarcity of evidence in non-critical settings, especially in resource limited countries. Hence, the study aimed at determining the incidence and predictors of hospital acquired acute kidney injury (HAAKI) in non-critical medical patients who were admitted at a large tertiary hospital in Ethiopia.

Methods

A retrospective chart review study was conducted from September 25, 2022 to January 20, 2023 among 232 hospitalized non-critical medical patients admitted to St. Paul's Hospital Millennium Medical College between January 2020 and January 2022. The incidence of HAAKI was estimated using incidence density per total person day (PD) observation of the study participants. To identify predictors of HAAKI, a log binomial regression model was fitted at a p value of ≤0.05. The magnitude of association was measured using adjusted relative risk (ARR) with its 95% CI.

Results

During the median follow-up duration of 11 days (IQR, 6-19 days), the incidence of HAAKI was estimated to be 6.0 per 100 PD (95% CI = 5.5 to 7.2). Significant predictors of HAAKI were found to be having type 2 diabetes mellitus (ARR = 2.36, 95% CI = 1.03, 5.39, p-value=0.042), and taking vancomycin (ARR = 3.04, 95% CI = 1.38, 6.72, p-value=0.006) and proton pump inhibitors (ARR = 3.80, 95% CI = 1.34,10.82, p-value=0.012).

Conclusion

HAAKI is a common complication in hospitalized non-critical medical patients, and is associated with a common medical condition and commonly prescribed medications. Therefore, it is important to remain vigilant in the prevention and timely identification of these cases and to establish a system of rational prescribing habits.

Time to Diabetic Nephropathy and its Predictors Among Diabetic Patients Treated in Wolaita and Dawuro Zone Hospitals, Ethiopia: A Retrospective Cohort Study

Background

Diabetic kidney disease (DKD) develops in nearly half of patients with type 2 diabetes mellitus (DM) and one-third of those with type 1 DM during their lifetime. The incidence of DKD as a cause of end stage renal disease is increasing each year. So this study aimed to assess the time to develop diabetic nephropathy and predictors among diabetic patients treated in Wolaita zone hospitals.

Methodology

A ten-year retrospective cohort study had conducted among 614 diabetic patients using systematic random sampling in Wolaita and Dawuro zone hospitals. Bivariable and multivariable Cox proportional hazards regression had used to identify the possible associations between variables. Those variables with a p-value of less than 0.25 in bivariable analysis exported to multivariable Cox regression analysis. Finally, variables with p-value less than 0.05 at multivariable Cox regression were considered significantly significant. The Cox-proportional hazard model assumption had checked using the Schoenfeld residual test.

Results

Of the total participants, 93 (15.3%; 95% CI = 12.45-18.14) patients had developed nephropathy in 820,048 people year observation. A mean time to diabetic nephropathy in this study was 189.63 (95% CI, 185.01, 194.25) months. Being illiterate (AHR: 2.21, 95% CI: 1.34-3.66), being hypertensive (AHR: 5.76, 95% CI: 3.39-9.59), and being urban dwellers (AHR: 2.25, 95% CI: 1.34-3.77) increases the hazard of nephropathy.

Conclusion

According to this follow-up study, the overall incidence rate is substantially high over ten year follow-up period. The mean time to develop diabetic nephropathy was sixteen years. Educational status, place of residence, and being hypertensive were the predictors. So stakeholders should work on complication reduction measures and awareness creation of the impact of comorbidities.

Prevalence and Factors Associated with Acute Kidney Injury in Sub-Saharan African Adults: A Review of the Current Literature

Acute kidney injury (AKI) is a complex condition that can occur in both community and hospital settings and has many aetiologies. These aetiologies may be infectious, toxic, surgical, or related to the different management methods. Although it is a major public health problem worldwide, it must be emphasised that both its incidence and mortality rate appear to be very high in sub-Saharan African (SSA) countries compared to developed countries. The profile of AKI is very different from that of more developed countries. There are no reliable statistics on the incidence of AKI in SSA. Infections (malaria, HIV, diarrhoeal, and other diseases), nephrotoxins, and obstetric and surgical complications are the main aetiologies in Africa. The management of AKI is costly and associated with high rates of prolonged hospitalisation and in-hospital mortality.

Association Between Iron Metabolism and Acute Kidney Injury in Critically Ill Patients With Diabetes

OBJECTIVE

Iron overload plays an important role in the pathogenesis of diabetes and acute kidney injury (AKI). The aim of this present study was to explore the relationship between iron metabolism and AKI in patients with diabetes.

METHODS

The clinical data of diabetes patients from MIMIC-III database in intensive care unit (ICU) were retrospectively analyzed. Regression analyses were used to explore the risk factors of AKI and all-cause death in critical patients with diabetes. Area under the receiver operating characteristic curves (AUROCs) were used to analyze serum ferritin (SF), and regression model to predict AKI in critical patients with diabetes. All diabetes patients were followed up for survival at 6 months, and Kaplan-Meier curves were used to compare the survival rate in patients with different SF levels.

RESULTS

A total of 4,997 diabetic patients in ICU were enrolled, with a male-to-female ratio of 1.37:1 and a mean age of 66.87 ± 12.74 years. There were 1,637 patients in the AKI group (32.8%) and 3,360 patients in the non-AKI group. Multivariate logistic regression showed that congestive heart failure (OR = 2.111, 95% CI = 1.320-3.376), serum creatinine (OR = 1.342, 95% CI = 1.192-1.512), Oxford Acute Severity of Illness Score (OR = 1.075, 95% CI = 1.045-1.106), increased SF (OR = 1.002, 95% CI = 1.001-1.003), and decreased transferrin (OR = 0.993, 95% CI = 0.989-0.998) were independent risk factors for AKI in critical patients with diabetes. Multivariate Cox regression showed that advanced age (OR = 1.031, 95% CI = 1.025-1.037), AKI (OR = 1.197, 95% CI = 1.011-1.417), increased Sequential Organ Failure Assessment score (OR = 1.055, 95% CI = 1.032-1.078), and increased SF (OR = 1.380, 95% CI = 1.038-1.835) were independent risk factors for 6-month all-cause death in critical diabetic patients. The AUROCs of SF and the regression model to predict AKI in critical patients with diabetes were 0.782 and 0.851, respectively. The Kaplan-Meier curve showed that the 6-month survival rate in SF-increased group was lower than that in SF-normal group (log-rank χ² = 16.989, P < 0.001).

CONCLUSION

Critically ill diabetic patients with AKI were easily complicated with abnormal iron metabolism. Increase of SF is an important risk factor for AKI and all-cause death in critically ill patients with diabetes.

Incidence and Predictors of Acute Kidney Injury Among Newly Diagnosed Type 2 Diabetes Patients at Chronic Follow-Up Clinic of University of Gondar Comprehensive Specialized Hospital: A Retrospective Follow-Up Study

Background

Acute kidney injury is a common disorder worldwide, occurring in more than 13 million per year, 85% of whom live in developing countries. The high incidence of acute kidney injury among type 2 diabetic patients is a major cause of morbidity and mortality. There is limited data that address the incidence and predictors of acute kidney injury to apply evidence-based interventions in developing countries including Ethiopia specifically in the study area.

Methods

Institution-based retrospective follow-up study was conducted among 420 adults with newly diagnosed type 2 diabetes patients from January 1, 2014, to December 31, 2019. Log rank test and Kaplan–Meier curve were used to compare different categories of survival probability. In a multivariable analysis, variable having a p-value <0.05 in the Cox, proportional hazard model was considered as independent predictors.

Results

Overall, 19.76% (95% CI; 16.2–23.8) of the study population developed acute kidney injury, with a median follow-up period of 30.75 months. Congestive heart failure [adjusted hazard ratio (AHR): 2.89 (95% CI; 1.62, 5.13)], chronic kidney disease [AHR: 2.92 (95% CI; 1.56, 5.48)], hypertension [AHR: 2.87 (95% CI; 1.20, 6.90)], and diabetic nephropathy [AHR: 2.04 (95% CI; 1.13, 3.68)] were found to be predictors of acute kidney injury.

Conclusion

The incidence of acute kidney injury among type 2 diabetes patients was high in the study area. In patients with hypertension congestive heart failure, chronic kidney disease, and diabetic nephropathy efforts should be made to diagnose AKI early and treat it – in addition to better control accordingly among type 2 diabetes mellitus patients.

Impact of diabetes mellitus on short-term prognosis, length of stay, and costs in patients with acute kidney injury: A nationwide survey in China

Background

International data suggest that people with diabetes mellitus (DM) are at increased risk for worse acute kidney injury (AKI) outcomes; however, the data in China are limited. Therefore, this study aimed to describe the association of DM with short-term prognosis, length of stay, and expenditure in patients with AKI.

Methods

This study was based on the 2013 nationwide survey in China. According to the 2012 Kidney Disease: Improving Global Outcomes (KDIGO) and expanded criteria of AKI, 7604 patients with AKI were identified, and 1404 and 6200 patients were with and without DM, respectively. Clinical characteristics, outcomes, length of stay, and costs of these patients were compared. Multivariate regression analyses were conducted to evaluate the association of DM with mortality, failed renal recovery, length of stay, and costs.

Results

Patients with AKI and DM were older, had higher male preponderance (61.9%), presented with more comorbidities, and had higher serum creatinine levels compared with those without DM. An apparent increase in all-cause in-hospital mortality, length of stay, and costs was found in patients with DM. DM was not independently associated with failed renal recovery (adjusted OR (95%CI): 1.08 (0.94–1.25)) and in-hospital mortality (adjusted OR (95%): 1.16 (0.95–1.41)) in multivariate models. However, the diabetic status was positively associated with the length of stay (β = 0.06, p<0.05) and hospital expenditure (β = 0.10, p<0.01) in hospital after adjusting for possible confounders.

Conclusion

In hospitalized AKI patients, DM (vs. no DM) is independently associated with longer length of stay and greater costs, but is not associated with an increased risk for failed renal recovery and in-hospital mortality.

Magnitude and predictors of hospital admission, readmission, and length of stay among patients with type 2 diabetes at public hospitals of Eastern Ethiopia: a retrospective cohort study

BACKGROUND

Type 2 Diabetes (T2D) represents one of the leading causes for hospital admissions and outpatient visits. Hence, T2D continuously imposes a significant burden to healthcare systems. The aim of this study was to assess predictors of hospital admission, readmission rates, and length of hospital stay among T2D patients in government hospitals of Eastern Ethiopia from 2013 to 2017.

METHODS

This study utilized retrospective data from a cohort of T2D patients following their treatment in government hospitals in Harari regional state of Ethiopia. Predictor of hospital admission was determined using parametric survival analysis methods. The readmission rate and length of hospital stay were determined by Poisson regression and mixed effect Poisson regression, respectively. All association were performed at 95% confidence level. Significance of association with determinants was reported using the hazard rate for hospital admission, and the incidence rate for readmission and length of hospital stay. Optimal model for each outcome was selected by using information criteria after fitness was checked.

RESULTS

The hospital admission rate for T2D patients was 9.85 (95%CI: 8.32, 11.66) per 1000-person-year observation. Alcohol drinking, inactive lifestyle, being a rural resident, history of comorbidities, and experiencing chronic diabetes complications were predictors of hospital admission. Seventy-one (52.2%) of the admitted patients had a history of readmission. Readmission rate was increased by being female, duration of disease, inactive lifestyle, having BMI greater than 29.9 kg/m2, and higher blood glucose. The median time of hospital stay for admitted patients was 18 (IQR:7). The length of hospital stay was longer among females, patients with the history of insulin administration, and higher blood glucose.

CONCLUSION

Multiple and complex factors were contributing for high diabetes admission and readmission rates as well as for longer in-hospital duration among T2D patients in Harari regional state. Socio-demographic characteristics (sex, place of residence), behavioral factors (alcohol intake, lifestyle), and medical conditions (longer duration of disease, comorbidities, chronic diabetes complications, higher blood glucose level, and treatment modality) were significant determinants of hospital admission, readmission and longer hospital stay among T2D patients.

Effects of physical activity on the progression of diabetic nephropathy: a meta-analysis

Background: Diabetic nephropathy (DN) is an important microvascular complication of diabetes. Physical activity (PA) is part of a healthy lifestyle for diabetic patients; however, the role of PA in DN has not been clarified. Our aim was to conduct a meta-analysis to explore the association between PA and DN risk.

Methods: PubMed, Embase, Cochrane Library and Web of Science were systematically searched for articles examining PA in diabetic patients and its effect on renal function. Standardized mean differences (SMDs) and odds ratios (ORs) with 95% confidence intervals (CIs) were calculated. The study protocol is registered with PROSPERO (CRD42020191379).

Results: A total of 38991 participants were identified from 18 studies. The results indicated that PA was associated with increases in the glomerular filtration rate (SMD = 0.01, 95% CI = [0.02–0.17]) and decreases in the urinary albumin creatinine ratio (SMD = −0.53, 95% CI: −0.72 to −0.34), rate of microalbuminuria (OR = 0.61, 95% CI = [0.46–0.81]), rate of acute kidney injury (OR = 0.02, 95% CI = [0.01–0.04]), rate of renal failure (OR = 0.71, 95% CI = [0.52–0.97]) and risk of DN in patients with Type 1 diabetes (OR = 0.67, 95% CI = [0.51–0.89]).

Conclusions: This meta-analysis indicated that PA is effective for improving DN and slowing its progression; however, more high-quality randomized controlled trials are required on this topic.

Sleep Quality and Associated Factors Among Diabetes Mellitus Patients in a Follow-Up Clinic at the University of Gondar Comprehensive Specialized Hospital in Gondar, Northwest Ethiopia: A Cross-Sectional Study

INTRODUCTION

Diabetic mellitus has a negative impact on the quality of sleep. It is one of the leading public health conditions which can result in poor sleep quality. Poor sleep quality is an unreported and unrecognized problem which can affect the prognosis of diabetes patients.

OBJECTIVE

The aim of this study is to assess the prevalence of poor sleep quality and its associated factors among patients with diabetes mellitus attending follow-up clinics at the University of Gondar Comprehensive Specialized Hospital, Northwest Ethiopia, 2019.

METHODS

An institution-based cross-sectional study was conducted among 430 diabetes mellitus patients at the University of Gondar Comprehensive Specialized Hospital from February 1, 2020 to March 28, 2020. A systematic random sampling method was used to reach the study subjects. An interviewer-administered questionnaire was used for data collection. Pittsburgh sleep quality index was used for assessing sleep quality. To explain study variables, frequency tables and percentages were used. A binary logistic regression was conducted to see the relation between dependent and independent variables.

RESULTS

A total of 430 diabetes mellitus patients participated in the study with a response rate of 100%. The overall prevalence of poor sleep quality was 47.2%. Drinking alcohol (AOR = 2.45, 95% CI: 1.28-4.69), smokers (AOR = 6.26, 95% CI: 2.04-19.21), comorbidity (AOR = 1.80, 95% CI: 1.10-2.96), BMI ≥ 30 (AOR = 4.87, 95% CI: 1.07-22.09), having type 2 diabetes mellitus (AOR = 2.16, 95% CI: 1.04-4.50), poor glycemic control (AOR = 2.61, 95% CI: 1.81-4.81) and having depression (AOR = 9.95, 95% CI: 4.85-20.38) were associated with poor sleep quality.

CONCLUSION

In this study, nearly half of the patients had poor sleep quality. Drinking alcohol, smoking, comorbidities, higher BMI, type 2 diabetes mellitus, poor glycemic control and having depression were factors in poor sleep quality. Creating awareness of the need for weight reduction, minimizing alcohol intake, cessation of smoking, and improving sleep hygiene for DM patients would be effective management for improving poor sleep quality.

Factors influencing breath analysis results in patients with diabetes mellitus

Breath analysis is used to detect the composition of exhaled gas. As a quick and non-invasive detection method, breath analysis provides deep insights into the progression of various kinds of diseases, especially those with metabolism disorders. Abundant information on volatile compounds in diabetic patients has been studied in numerous articles in the literature. However, exhaled gas in diabetic patients can be altered by various complications. So far, little attention has been paid to this alteration. In our paper, we found that under air pollution conditions, diabetic patients exhale more nitric oxide. Diabetic patients with heart failure exhale more acetone than those without heart failure. After ¹³C-labeled glucose intake, patients infected with Helicobacter pylori exhaled more ¹³C and less ¹⁸O than those without infection. Exhalation with chronic kidney disease changes volatile organic compounds on a large scale. Diabetic patients with ketoacidosis exhale more acetone than those without ketoacidosis. Some specific volatile organic compounds also emanate from diabetic feet. By monitoring breath frequency, diabetic patients with obstructive sleep apnea syndrome exhibit a unique breath pattern and rhythm as compared with other diabetic patients, and sleep apnea is prevalent among diabetic patients. In addition to clinical findings, we analyzed the underlying mechanisms at the levels of molecules, cells and whole bodies, and provided suggestions for further studies.