Assessment of serum biochemical derangements and associated risk factors of chronic kidney disease

Mehmood, Hafiz Rehman; Khan, Zaman; Jahangir, Hafiz Muhammad Sajid; Hussain, Abid; Elahi, Amina; Askari, Syed Muhammad Hassan

doi:10.1016/j.jtumed.2021.09.009

Cited by 5 publications

(8 citation statements)

References 42 publications

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“…In this study, 24.7% of the patients with CKD progression were found with electrolyte imbalances with hyperkalemia being the most prevalent. Similar ndings have been reported from previous studies where electrolyte imbalances and hyperkalemia were associated with CKD progression and end-stage renal disease (ESRD) with serious complications (74,75). In this study 10.3% of the patients with CKD progression developed ESRD and 14(4.0%) patients died; 11 (78.6%) of the patients who died had CKD progression.…”

Section: Discussionsupporting

confidence: 90%

Progression of chronic kidney disease among adults attending tertiary hospitals in Dodoma, Tanzania

Katatwire,

Meremo

2024

Preprint

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Background Chronic kidney disease (CKD) in resource constrained settings can silently and rapidly progress to end stage kidney disease (ESKD). Thus, it is important to identify patients at risk of CKD progression for appropriate and timely interventions. Methods A prospective longitudinal study was conducted among adults with CKD attending nephrology and medical outpatient (MOPD) clinics of two tertiary hospitals in Dodoma, Tanzania between November 2020 to March 2022. Demographic and clinical data were extracted from patient files, as well as measurements of vital signs and face to face interviews conducted at baseline and at follow up. Patients provided urine and blood samples for laboratory investigations at study entry (0) and at 12 months. Descriptive and inferential statistics were performed using SPSS software version 26, and multivariable logistic regression analysis was used to identify factors associated with CKD progression. Results A total of 352 participants with median age of 54 (47–59) years were enrolled, the prevalence of CKD progression by a sustained decline in eGFR > 4 ml/min/1.73m2 per year was 28.0% (97/346). For CKD progressors; the baseline median eGFR was 43 (41–49) mL/min/1.73 m2, urine protein creatinine ratio (uPCR) was 0.099 (0.025–0.158) g/g and haemoglobin were 11.7 (9.7–12.6) g/dl. Of the patients with CKD progression, 73(75.3%) patients had diabetes mellitus, 70 (72.2%) of the patients had hypertension, 57 (58.8%) had significant proteinuria and 57 (58.8%) had anaemia. Variables associated with CKD progression after multivariate logistic regression analysis were; diabetes mellitus (OR = 7.02, 95% CI 3.01–16.39, P = 0.001), use of local herbs (OR = 27.98, 95% CI 11.08–70.70, P = 0.001), anaemia (OR = 2.49, 95% CI 1.32–4.68, P = 0.005), proteinuria (OR = 7.51, 95% CI 3.49–16.19 P = 0.001). Half (52.5%) of the patients with CKD progression were found to have left ventricular hypertrophy (LVH) and a total of 14 (11.9%) patients died during the study period. Conclusion The prevalence of CKD progression is high in our settings. Diabetes mellitus, proteinuria, anaemia and use of local herbal medicines were significant risk factors for CKD progression. More than half of the patients who had CKD progression were found to have LVH and few patients died.

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Section: Discussionsupporting

confidence: 90%

Progression of chronic kidney disease among adults attending tertiary hospitals in Dodoma, Tanzania

Katatwire,

Meremo

2024

Preprint

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“…55 On the other hand, acute kidney failure patients (or end-stage CKD) can present blood levels in the range of 15−33 mmol/L urea (41-96 mg/dL), 5.0−6.2 mmol/L potassium, and disturbed sodium and chloride concentrations. 11,15,56,57 G-LOC performance with serum samples was evaluated using certified reference material (CRM) of two different levels, healthy and renal failure levels. First, the G-LOC test-totest dispersion was evaluated by measuring more than 100 tests (Figure 3A−D).…”

Section: ■ Results and Discussionmentioning

confidence: 99%

“…Urea, potassium, sodium, and chloride levels in blood normally are in the range of 1.8–7.1 mM (5–20 mg/dL), 3.5–5, 135–145, and 96–106 mEq/L for healthy people . On the other hand, acute kidney failure patients (or end-stage CKD) can present blood levels in the range of 15–33 mmol/L urea (41-96 mg/dL), 5.0–6.2 mmol/L potassium, and disturbed sodium and chloride concentrations. ,,, …”

Section: Resultsmentioning

confidence: 99%

Noninvasive and Multiplex Self-Test of Kidney Disease Biomarkers with Graphene-Based Lab-on-a-Chip (G-LOC): Toward Digital Diagnostics in the Hands of Patients

Diforti,

Cunningham,

Piccinini

et al. 2024

Anal. Chem.

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Chronic kidney disease is one of the major health issues worldwide. However, diagnosis is now highly centralized in large laboratories, resulting in low access to patient monitoring and poor personalized treatments. This work reports the development of a graphene-based lab-on-a-chip (G-LOC) for the digital testing of renal function biomarkers in serum and saliva samples. G-LOC integrates multiple bioelectronic sensors with a microfluidic system that enables multiplex self-testing of urea, potassium, sodium, and chloride. The linearity, limit of detection (LOD), accuracy, and coefficient of variability (CV) were studied. Accuracy values higher than 95.5% and CV lower than 9% were obtained for all of the biomarkers. The analytical performance was compared against three reference lab benchtop analyzers by measuring healthy-and renal-failure-level samples of serum. From receiver operating characteristic (ROC) plots, sensitivities (%) of 99.7, 97.6, 99.1, and 89.0 were obtained for urea, potassium, sodium, and chloride, respectively. Then, the test was evaluated in noninvasive saliva samples and compared against reference methods. Correlation and Bland−Altman plots showed good correlation and agreement of the G-LOC with the reference methods. It is noteworthy that the precision of G-LOC was similar to better than benchtop lab analyzers, with the advantage of being highly portable. Finally, a user testing study was conducted. The analytical performance obtained with untrained volunteers was similar to that obtained with trained chemists. Additionally, based on a user experience survey, G-LOC was found to have very simple usability and would be suitable for at-home diagnostics.

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“…Proteinuria, a marker of kidney damage, may not provide a definite diagnoses and should be evaluated alongside other kidney0based biomarkers. Biomarkers such as chlorine, sodium, calcium, urea nitrogen, potassium, and carbon dioxide directly relate to acute renal insufficiency and chronic kidney disease( 46 – 50 ). These conditions manifest as sudden onset, reduced urine output, acidosis, fluid imbalance, and electrolyte disorders( 51 ).…”

Section: Discussionmentioning

confidence: 99%

Prediction of Adverse Events Risk in Patients with Comorbid Post- Traumatic Stress Disorder and Alcohol Use Disorder Using Electronic Medical Records by Deep Learning Models

Miranda,

Fan,

et al. 2023

Preprint

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Background Prediction of high-risk events in mental disorder patients is crucial. In our previous study, we developed a deep learning model: DeepBiomarker by using electronic medical records (EMR) to predict suicide related event (SRE) risk in post-traumatic stress disorder (PTSD) patients. Methods We applied DeepBiomarker2 through data integration of multimodal information: lab test, medication, co-morbidities, and social determinants of health. We analyzed EMRs of 5,565 patients from University of Pittsburgh Medical Center with a diagnosis of PTSD and alcohol use disorder (AUD) on risk of developing an adverse event (opioid use disorder, SREs, depression and death). Results DeepBiomarker2 predicted whether a PTSD + AUD patient will have a diagnosis of any adverse events (SREs, opioid use disorder, depression, death) within 3 months with area under the receiver operator curve (AUROC) of 0.94. We found piroxicam, vilazodone, dronabinol, tenofovir, suvorexant, empagliflozin, famciclovir, veramyst, amantadine, sulfasalazine, and lamivudine to have potential to reduce risk. Conclusions DeepBiomarker2 can predict multiple adverse event risk with high accuracy and identify potential risk and beneficial factors. Our results offer suggestions for personalized interventions in a variety of clinical and diverse populations.

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Assessment of serum biochemical derangements and associated risk factors of chronic kidney disease

Cited by 5 publications

References 42 publications

Progression of chronic kidney disease among adults attending tertiary hospitals in Dodoma, Tanzania

Progression of chronic kidney disease among adults attending tertiary hospitals in Dodoma, Tanzania

Noninvasive and Multiplex Self-Test of Kidney Disease Biomarkers with Graphene-Based Lab-on-a-Chip (G-LOC): Toward Digital Diagnostics in the Hands of Patients

Prediction of Adverse Events Risk in Patients with Comorbid Post- Traumatic Stress Disorder and Alcohol Use Disorder Using Electronic Medical Records by Deep Learning Models

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