Hypokalemia in Diabetes Mellitus Setting

Electrolyte Imbalances and Metabolic Emergencies in Obesity: Mechanisms and Clinical Implications

Electrolyte imbalances are a frequently overlooked yet critical component of obesity-related metabolic dysfunction, contributing to an increased risk of cardiovascular disease, kidney impairment, and metabolic emergencies such as diabetic ketoacidosis (DKA), hyperosmolar hyperglycemic state (HHS), and acute kidney injury (AKI). These disturbances arise from insulin resistance, chronic inflammation, hormonal dysregulation, and renal dysfunction, leading to sodium retention, potassium depletion, and deficiencies in calcium and magnesium homeostasis. Managing electrolyte imbalances is essential in obesity management, as imbalances exacerbate hypertension, metabolic acidosis, neuromuscular complications, and insulin resistance. This review explores the pathophysiology of electrolyte disturbances in obesity and their impact on fluid balance, acid-base status, and metabolic health. Effective management strategies include individualized electrolyte monitoring, dietary sodium restriction, potassium supplementation, vitamin D and magnesium correction, and pharmacologic interventions targeting renin-angiotensin-aldosterone system (RAAS) activity and insulin resistance. Additionally, lifestyle interventions, including dietary modification, weight loss strategies, and hydration optimization, play a key role in preventing metabolic complications. Future research should investigate the long-term impact of electrolyte imbalances in obesity, the role of emerging therapies, and how lifestyle interventions can optimize electrolyte homeostasis and metabolic outcomes. A personalized, multidisciplinary approach integrating endocrinology, nephrology, and clinical nutrition is essential to improving the prevention and management of electrolyte imbalances in obese individuals.

Effectiveness of ertugliflozin during Ramadan fasting in patients with type 2 diabetes mellitus: a real-world study (ErtuRamadan study)

Background

Management of type 2 diabetes mellitus (T2DM) during Ramadan fasting presents unique challenges due to prolonged fasting periods, irregular meal schedules, and altered medication timing, potentially impacting glycemic control. Ertugliflozin, a sodium-glucose co-transporter 2 (SGLT2) inhibitor, has been shown to improve glycemic control in T2DM effectively. However, the effectiveness of ertugliflozin during Ramadan fasting, a period with unique glycemic challenges, has not been studied extensively.

Methods

This study was a multicenter, real-life experience study involving 1373 adult patients with known T2DM for at least one year, an HbA1c level of less than 10%, and who intended to fast during Ramadan. Participants were divided into two groups: the Ertu group (n=703), consisting of patients who had been on a stable dose of ertugliflozin for at least three months before Ramadan, and the non-Ertu group (n=670), which included patients receiving other oral antihyperglycemic drugs (OADs) except ertugliflozin. Patients attended a baseline visit one month before the first day of Ramadan and a follow-up visit within one month after the last day of Ramadan. Both visits included history taking, physical examinations, and laboratory tests. The primary endpoints were changes in HbA1c levels, body weight, body mass index (BMI), and the incidence of hypoglycemia during Ramadan fasting.

Results

The mean age of the study participants was 50.37 ± 11.14 (SD) years, with 40.6% male and 58.7% female. Patients receiving ertugliflozin showed significant reduction in HbA1C (-0.65 ± 0.67% vs. -0.22 ± 0.64%, p<0.001), body weight (-1.24 ± 2.58 kg vs. -0.36 ± 3.41 kg, p<0.001), and BMI (-0.48 ± 1.03 kg/m² vs. -0.11 ± 1.33 kg/m², p<0.001) compared to the non-Ertu group. Hypoglycemia was reported in 0.3% of the ertugliflozin group and 0.7% of the other group, with comparable adverse events (p=.23; ≥0.05), indicating a favorable safety profile for ertugliflozin during fasting.

Conclusion

This study demonstrates that ertugliflozin is effective and safe for patients with T2DM during Ramadan fasting.

Nutritional risk and HbA1c as critical risk factors and predictors of opportunistic infections in HIV-DM comorbid patients: a retrospective cross-sectional study

BACKGROUND

The clinical characteristics and risk factors for opportunistic infections in HIV patients with concomitant diabetes mellitus are unclear and worth studying. Explore the risk factors and construct a predictive model for opportunistic infections in HIV-DM patients.

METHODS

Clinical data were retrospectively collected from 1,669 HIV-DM admitted to the Public Health Clinical Center of Chengdu from December 2018 to November 2023.Based on the occurrence of opportunistic infections, the patients were divided into two groups. Comparative analyses were conducted to assess nutritional status, plasma glucose levels, comorbidities of chronic noncommunicable diseases, and immune status. We applied univariate logistic regression and LASSO regression to screen independent variables. Multivariable logistic regression analysis was performed to identify risk factors and establish a prediction model for opportunistic infections.

RESULTS

In our study population of 1,669 patients (median age was 59 years, 83.22% male), 868 developed opportunistic infections, while the remaining 801 patients did not develop opportunistic infections. Additionally, 1,598 patients survived, and 71 patients died. The opportunistic infection group had a greater median age, lower median BMI, longer median length of hospital stay and greater number of deaths. Logistic regression analysis identified nutritional risk, duration of HIV infection, HbA1c, albumin, and CD4+ T cell counts as significant risk factors and predictors of opportunistic infections. Nutritional risk (OR=2.888) and HbA1c showed positive associations (P<0.001), while duration of HIV infection, albumin, and CD4+ T cell counts demonstrated negative associations with infection risk (P<0.05). The comprehensive model evaluation, based on receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA), validated the acceptable predictive performance of our model.

CONCLUSION

This study identified nutritional risk, duration of HIV infection, HbA1c and albumin as significant risk factors and predictors of opportunistic infections in HIV-DM patients, further highlighting the importance of nutritional screening and good glucose control.

Modern-Day Therapeutics and Ongoing Clinical Trials against Type 2 Diabetes Mellitus: A Narrative Review

OBJECTIVES

Diabetes Mellitus (DM) is a global health concern that affects millions of people globally. The present review aims to narrate the clinical guidelines and therapeutic interventions for Type 2 Diabetes Mellitus (T2DM) patients. Furthermore, the present work summarizes the ongoing phase 1/2/3 and clinical trials against T2DM.

METHODS

A meticulous and comprehensive literature review was performed using various databases, such as PubMed, MEDLINE, Clinical trials database (https://clinicaltrials.gov/), and Google Scholar, to include various clinical trials and therapeutic interventions against T2DM.

RESULTS

Based on our findings, we concluded that most T2DM-associated clinical trials are interventional. Anti-diabetic therapeutics, including insulin, metformin, Dipeptidyl Peptidase-4 (DPP-4) inhibitors, Glucagon-Like Peptide-1 Receptor Agonists (GLP-1RAs), and Sodium- Glucose cotransporter-2 (SGLT-2) inhibitors are frontline therapeutics being clinically investigated. Currently, the therapeutics in phase IV clinical trials are mostly SGLT-2 inhibitors, implicating their critical contribution to the clinical management of T2DM.

CONCLUSION

Despite the success of T2DM treatments, a surge in innovative treatment options to reduce diabetic consequences and improve glycemic control is currently ongoing. More emphasis needs to be on exploring novel targeted drug candidates that can offer more sustained glycemic control.

Evaluation of potential human health risks associated with Li and their relationship with Na, K, Mg, and Ca in Romania's nationwide drinking water

Background

Increasing lithium (Li) demand worldwide due to its properties and role in renewable energy will raise water reservoir pollution and side effects on human health. Divergent results regarding Li concentration in water and affective disorders are found in the literature, which is why regional reports are expected.

Objective

The present study evaluated the occurrence and human health risks resulting from oral exposure, respectively, and the relationship between alkali metals (Li, Na, and K) and minerals (Mg, Ca) in balanced purified water (bottled) and spring water.

Methods

The ICP-MS technique was used to measure a national database with 53 bottled and 42 spring water samples randomly selected. One-way ANOVA, Pearson correlation, and HCA analysis were applied to assess the possible relationship between metals in water. The possible side effects of Li poisoning of water resources on human health have been evaluated using the Estimated Daily Intake Index (EDI) and Total Hazard Quotient (THQ).

Results

The toxic metals (As, Hg, and Pb) were measured, and the results indicate values above the detection limit of 22.3% of samples in the case of lead but not exceeding the safety limits. Depending on the water sources, such as bottled and spring water, the Li concentration varied between 0.06-1,557 and 0.09-984% μg/L. We found a strong positive correlation between Li and Na and Mg, varying between bottled and spring waters (p% <%0.001). Li exceeded the limit set by the Health-Based Screening Level (HBSL) in 41.37 and 19% of bottled and spring water samples. The oral reference doses (p-RfDs) for the noncancer assessment of daily oral exposure effects for a human lifetime exceeded threshold values. The THQ index shows potential adverse health effects, requiring further investigations and remedial actions in 27.58% of approved bottled waters and 2.38% of spring waters.

Conclusion

We can conclude that water is safe based on the Li concentration found in drinking water and supported by a gap in strict regulations regarding human Li ingestion. The present study can serve decision-makers and represent a starting database with metals of interest for further clinical studies. Decision-makers can also use it to find solutions for sustainable management of clean and safe drinking water.

The influence of salt reduction with encapsulated oleoresins on the quality of mayonnaise, mustard, and ketchup

Introduction

Mayonnaise, mustard, and ketchup are table sauces enjoyed worldwide, adding flavour and texture to many dishes. However, these products often contain high sodium content, which contributes to health issues such as high blood pressure and cardiovascular disease. To address these concerns, reducing salt content in the sauces has become a significant goal for both manufacturers and consumers.

Objectives

This study investigates the effects of three formulations of microencapsulated (ME) oleoresins (F1, F2, and F3), derived from aromatic plants and spices, on the mineral content, physical-chemical properties, colour, and sensory profiles of mayonnaise, mustard, and ketchup.

Results

The addition of ME ingredients resulted in significant reductions in salt content across all sauces, with reductions up to 50% in mayonnaise, 45% in mustard, and 52% in ketchup, aligning with EU sodium guidelines and allowing for a "reduced Na/NaCl content" nutrition claim. Potassium levels in mustard and ketchup were sufficient to support health claims related to blood pressure maintenance, while chloride content was reduced in ME formulations, better aligning with dietary reference values. Physical-chemical analysis revealed that ME ingredients had minimal impact on parameters like pH, lipid oxidation, and viscosity, although significant differences were observed in specific areas, such as the consistency of ketchup and chloride content in mustard and ketchup. The use of inulin, as a carrier agent, helped maintain the sauces rheological properties. Mustard showed the most similarity to the control in terms of physical-chemical parameters. Colour analysis indicated minimal changes in mayonnaise, moderate changes in mustard, and significant differences in ketchup, particularly with the ME-F3 formulation, where the light-yellow ME ingredients had a pronounced effect on the darker sauce. Despite these differences, the sensory analysis demonstrated that the overall sensory profiles of the ME formulations were similar the like control for all sauces. Mayonnaise showed the closest resemblance, while mustard had slightly lower scores in flavour and saltiness. Ketchup followed the same trend as mayonnaise, with no significant sensory differences compared to the control.

Conclusion

These findings suggest that ME ingredients can be effectively used in condiment reformulation to achieve significant salt reduction without compromising sensory qualities, while also supporting health-related claims. By incorporating ME-based salt reduction strategies and exploring low-sodium alternatives, consumers can continue to enjoy their favourite sauces while minimising sodium intake. Embracing these changes not only benefits personal health but also aligns with the industry's commitment to offering more nutritious options.

Evaluation of the systemic-immune inflammation index (SII) and systemic immune-inflammation response index (SIRI) in children with type 1 diabetes mellitus and its relationship with cumulative glycemic exposure

OBJECTIVES

In this study, the systemic proinflammatory status was assessed using the systemic immune-inflammation index (SII) and SIRI systemic immune-inflammatory response index (SIRI) in children and adolescents with type 1 diabetes mellitus (T1DM).

METHODS

The study involved 159 patients aged between 6 and 16 years. The SII and SIRI values were calculated based on the complete blood count. Basic blood biochemistry evaluated, and carotid intima-media thickness (cIMT) was measured and recorded. The cumulative glycemic exposure was calculated by multiplying the value above the normal reference range of the HbA1c value. The sum of all these values obtained from the time of diagnosis to obtain the cumulative glycemic exposure. All findings were compared statistically. All statistically significant parameters were evaluated in the multivariate logistic regression analysis.

RESULTS

The analysis revealed that only cIMT (Exp(B)/OR: 0.769, 95 % CI: 0.694-0.853, p<0.001), high-density lipoprotein (Exp(B)/OR: 3.924, 95 % CI: 2.335-6.596, p<0.001), monocyte count (Exp(B)/OR: 1.650, 95 % CI: 1.257-2.178, p<0.001), hematocrit (Exp(B)/OR: 0.675, 95 % CI: 0.523-0.870, p<0.001), and SIRI (Exp(B)/OR: 1.005, 95 % CI: 1.002-1.008, p<0.001) were significantly associated with T1DM. A statistically significant positive association was found between cumulative glycemic exposure and SIRI only (r=0.213, p=0.032). To our knowledge, this is the first study to evaluate SII and SIRI in children with type 1 diabetes.

CONCLUSIONS

These findings indicate that SIRI could serve as a potential biomarker for detecting early-onset proatherosclerotic processes in diabetic children. However, further clinical studies are required to confirm this.

Prevalence and impact of diabetes and prediabetes on presentation and complications of primary hyperaldosteronism at diagnosis

BACKGROUND

Primary hyperaldosteronism (PH) is considered to contribute to increased risk of developing type 2 diabetes mellitus (T2DM) and prediabetes. Both PH and DM are associated with increased risk for hypertension, cardiovascular diseases, and chronic kidney diseases. However, data on prevalence of T2DM and prediabetes in PH, and impact of T2DM and prediabetes on presentation and cardio renal complications in PH at presentation is sparse.

AIM

To determine the prevalence of T2DM and prediabetes in PH at diagnosis and impact on presentation and complications of PH.

METHODS

A retrospective cohort study was conducted in tertiary care settings in individuals with confirmed diagnosis of PH at presentation. Demographic variables, clinical presentations, duration and degree of hypertension, complications, laboratory parameters including sodium, potassium levels, plasma aldosterone concentration (PAC), plasma renin activity (PRA), and aldosterone to renin ratio (ARR) and cardio-renal parameters were collected. Comparison was done between three groups: PH with no DM (Group A) or with pre-diabetes (Group B) or with T2DM (Group C). P < 0.05 was statistically significant.

RESULTS

Among 78 individuals with confirmed PH, 62% had pre-diabetes or diabetes; with 37% having DM. Mean duration of T2DM was 5.97 ± 4.7 years. The mean levels of glycaemic parameters among the group A vs B vs C individuals were fasting plasma glucose (mg/dL): 87.9 ± 6.5, 105.4 ± 9.02, 130.6 ± 21.1; post prandial plasma glucose (mg/dL): 122.7 ± 9.8, 154.9 ± 14, 196.7 ± 38.0; glycated haemoglobin (%) (5.3 ± 0.2, 5.9 ± 0.2, 7.5 ± 0.6, P < 0.05), respectively. There was no significant difference in the biochemical parameters (PAC, PRA, ARR, sodium, potassium levels), presentation and complications between the groups. Cardio renal parameters or degree and duration of hypertension were comparable between the groups.

CONCLUSION

Significant prevalence of T2DM and prediabetes in PH at diagnosis does not impact its presentation or complications. Early screening for undetected PH in T2DM and prediabetes subjects with hypertension may prevent complications.

Cellular senescence molecules expression in type 2 diabetes mellitus: CDKN2A, CDKN2B, and lncRNA ANRIL

AIMS

Cellular senescence in type 2 diabetes mellitus (T2DM) has received widespread attention. However, the cellular senescence molecules involved in T2DM are unclear. Furthermore, there are no consistent biomarkers for cellular senescence in T2DM. Therefore, this study aimed to identify cellular senescence molecules in T2DM and investigate their expression in peripheral blood mononuclear cells of individuals with T2DM.

METHODS

Patients with T2DM (n = 40) and healthy controls (n = 40) were enrolled. We used different databases to identify cellular senescence molecules in T2DM and confirmed the obtained genes and lncRNA using real-time PCR.

RESULTS

Bioinformatics analysis indicated that CDKN2A and CDKN2B genes, and long noncoding RNA ANRIL are the most effective cellular senescence molecules in T2DM. Furthermore, CDKN2A and ANRIL expression decreased in individuals with T2DM.

CONCLUSIONS

Cellular senescence may have a protective effect against T2DM. In addition, the cellular senescence molecules CDKN2A and ANRIL may be potential biomarkers of cellular senescence in T2DM.

The relationship between potassium levels and 28-day mortality in sepsis patients: Secondary data analysis using the MIMIC-IV database

Objective

The goal of the research is to investigate the link between serum potassium levels and death after 28 days in sepsis patients, utilizing an extensive sample of patients from the multi-center Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Current research on serum potassium levels and 28-day mortality in sepsis patients is questionable. This study adds to the growing body of evidence linking serum potassium levels to the 28-day possibility of death in patients with sepsis.

Methods

We collected 349,08 patients with sepsis from the retrospective cohort MIMIC-IV database, using serum potassium level on the first day of admission to the intensive care unit as the exposure variable and mortality at 28 days as the outcome variable. And controlled for confounding characteristics including gender, age, ethnicity, and vital signs during admission.

Results

Serum potassium has a U-shaped connection with 28-day mortality in patients suffering from sepsis. The turning point was 4.10 mmol/L (95 % confidence interval: 4.03 to 4.22). Serum potassium and 28-day mortality were negatively linked on the inflection point's left side (OR: 0.72; 95 % CI: 0.63 to 0.83, P < 0.0001); on the opposing side of the point of inflexion, serum potassium was enthusiastically attached to 28-day mortality. (OR: 1.13; 95 % CI: 1.06 to 1.21, P < 0.0001).

Conclusion

The research conducted found that too high or too low potassium levels were linked to a 28-day risk of mortality in humans with sepsis.

Initial eGFR Changes with SGLT2 Inhibitor in Patients With Type 2 Diabetes and Associations With the Risk of Abnormal Serum Potassium Level

BACKGROUND

Both high and low levels of serum potassium measurements are linked with a higher risk of adverse clinical events among patients with type 2 diabetes. The study was aimed at evaluating the implications of the various degrees of initial estimated glomerular filtration rate (eGFR) change on subsequent serum potassium homeostasis following sodium-glucose cotransporter-2 inhibitor (SGLT2i) initiation among patients with type 2 diabetes.

METHODS AND RESULTS

We used medical data from a multicenter health care provider in Taiwan and recruited 5529 patients with type 2 diabetes with baseline/follow-up eGFR data available after 4 to 12 weeks of SGLT2i treatment from June 1, 2016, to December 31, 2018. SGLT2i treatment was associated with an initial mean (SEM) eGFR decline of -3.5 (0.2) mL/min per 1.73 m2 in overall study participants. A total of 36.7% (n=2028) of patients experienced no eGFR decline, and 57.9% (n=3201) and 5.4% (n=300) of patients experienced an eGFR decline of 0% to 30% and >30%, respectively. Patients with an initial eGFR decline of >30% were associated with higher variability in consequent serum potassium measurement when compared with those without an initial eGFR decline. Participants with a pronounced eGFR decline of >30% were associated with a higher risk of hyperkalemia ≥5.5 (adjusted hazard ratio,4.59 [95% CI, 2.28-9.26]) or use of potassium binder (adjusted hazard ratio, 2.65 [95% CI, 1.78-3.95]) as well as hypokalemia events <3.0 mmol/L (adjusted hazard ratio, 3.21 [95% CI, 1.90-5.42]) or use of potassium supplement (adjusted hazard ratio, 1.87 [95% CI, 1.37-2.56]) following SGLT2i treatment after multivariate adjustment.

CONCLUSIONS

Physicians should be aware that the eGFR trough occurs shortly, and consequent serum potassium changes following SGLT2i initiation.

Association between circulating micronutrient pattern, glycemic control, and insulin resistance in type 2 diabetes mellitus

The circulating micronutrient pattern in type 2 diabetes mellitus (T2DM) may impact glycemic control and insulin resistance; however, there is a scarcity of studies that have evaluated the circulating micronutrient pattern in the T2DM population. Therefore, our objective was to identify circulating micronutrient pattern and their association with markers of glycemic control and insulin resistance in individuals with T2DM. We developed a cross-sectional observational study involving adults with T2DM in Sergipe, Brazil. We assessed plasma levels of magnesium, zinc, calcium, potassium, and serum 25-hydroxyvitamin D. Additionally, also measured fasting glucose levels, the percentage of glycated hemoglobin (%HbA1c), and calculated the homeostatic model assessment for insulin resistance (HOMA-IR). Patterns of body reserve were established using principal component analysis and categorized into quartiles. Binary logistic regression models were employed. We evaluated 114 individuals (63.7% women), with a median age and body mass index of 49 years and 29.6 kg/m², respectively. Two circulating micronutrient patterns were identified, explaining 62.5% of the variance: Pattern 1 (positive contributions from magnesium, zinc, calcium, and potassium) and Pattern 2 (positive contributions from 25-hydroxyvitamin D and zinc, with a negative contribution from potassium). Lowest quartile for Pattern 1 and Pattern 2 exhibiting a 4.32-fold (p = 0.019) and 3.97-fold (p = 0.038) higher likelihood of increasing HOMA-IR and %HbA1c values, respectively, compared to the larger quartiles. However, no associations were found between these patterns and fasting glucose values. Lowest quartile for both patterns of micronutrients was associated with inadequate metabolic control in individuals with T2DM.

Design and clinical application of a risk prediction model for diabetic foot

OBJECTIVE

To construct and evaluate a nomogram prediction model for the risk of diabetic foot in patients with type 2 diabetes based on their clinical data, and to assist clinical healthcare professionals in identifying high-risk factors and developing targeted intervention measures.

METHODS

We retrospectively collected clinical data from 478 hospitalized patients with type 2 diabetes at the First Affiliated Hospital of Shantou University Medical College from January 2019 to December 2021. The patients were divided into a diabetic foot group (n=312) and a non-diabetic foot group (n=166) based on whether they had diabetic foot. The baseline data of both groups were collected. Univariate and multivariate analyses as well as logistic regression analysis were conducted to explore the risk factors for diabetic foot. A nomogram prediction model was established using the package "rms" version 4.3. The model was internally validated using the area under the receiver operating characteristic curve (AUC). Additionally, the decision curve analysis (DCA) was performed to evaluate the performance of the nomogram model.

RESULTS

The results from the logistic regression analysis revealed that being male, smoking, duration of diabetes, glycated hemoglobin, hyperlipidemia, and atherosclerosis were influencing factors for diabetic foot (all P<0.05). The AUC of the model in predicting diabetic foot was 0.804, with a sensitivity of 75.3% and specificity of 74.4%. Harrell's C-index of the nomogram prediction model for diabetic foot was 0.804 (95% CI: 0.762-0.844), with a threshold value of >0.675. The DCA findings demonstrated that the nomogram model provided a net clinical benefit.

CONCLUSION

The nomogram prediction model constructed in this study showed good predictive performance and can provide a basis for clinical workers to prevent and intervene in diabetic foot, thereby improving the overall diagnosis and treatment.

Ion homeostasis in diabetic kidney disease

The complications of type 2 diabetes are a major global public health problem with high incidence and mortality, affecting almost all individuals with diabetes worldwide. Diabetic kidney disease (DKD) is one such primary complication and has become a leading cause of end-stage renal disease in patients with diabetes. Progression from diabetes to DKD is a complex process typically involving multiple mechanisms. Recent remarkable clinical benefits of sodium-glucose cotransporter 2 (SGLT2) inhibitors in diabetes and DKD highlight the critical impact of renal ion homeostasis on disease progression. This review comprehensively examines the impact of ion homeostasis on the transition from diabetes to DKD, outlining possible therapeutic interventions and addressing the ongoing challenges in this rapidly developing field.

Pharmacological Considerations in the Interpretation of Biochemical Results in Diabetic Patients with Cardiovascular Complications

Diabetes mellitus with cardiovascular diseases is often a multi-systemic disease that requires a multi-therapeutic approach which mostly poses a challenge to laboratory result interpretation. The non-availability of information on many patients due to poor referral, documentation and record keeping has resulted in isolated interpretation of laboratory result of diabetic patients with multisystemic complications. This has led to both analytical and post-analytical errors which has a negative impact on total quality of results. Therefore, this review showed the possible therapeutic treatment of a diabetic patient with cardiovascular disease and how their pharmacological role could affect laboratory result.

Application of serum SERS technology combined with deep learning algorithm in the rapid diagnosis of immune diseases and chronic kidney disease

Surface-enhanced Raman spectroscopy (SERS), as a rapid, non-invasive and reliable spectroscopic detection technique, has promising applications in disease screening and diagnosis. In this paper, an annealed silver nanoparticles/porous silicon Bragg reflector (AgNPs/PSB) composite SERS substrate with high sensitivity and strong stability was prepared by immersion plating and heat treatment using porous silicon Bragg reflector (PSB) as the substrate. The substrate combines the five deep learning algorithms of the improved AlexNet, ResNet, SqueezeNet, temporal convolutional network (TCN) and multiscale fusion convolutional neural network (MCNN). We constructed rapid screening models for patients with primary Sjögren's syndrome (pSS) and healthy controls (HC), diabetic nephropathy patients (DN) and healthy controls (HC), respectively. The results showed that the annealed AgNPs/PSB composite SERS substrates performed well in diagnosing. Among them, the MCNN model had the best classification effect in the two groups of experiments, with an accuracy rate of 94.7% and 92.0%, respectively. Previous studies have indicated that the AgNPs/PSB composite SERS substrate, combined with machine learning algorithms, has achieved promising classification results in disease diagnosis. This study shows that SERS technology based on annealed AgNPs/PSB composite substrate combined with deep learning algorithm has a greater developmental prospect and research value in the early identification and screening of immune diseases and chronic kidney disease, providing reference ideas for non-invasive and rapid clinical medical diagnosis of patients.

Application of Machine Learning Algorithms to Predict Uncontrolled Diabetes Using the All of Us Research Program Data

There is a paucity of predictive models for uncontrolled diabetes mellitus. The present study applied different machine learning algorithms on multiple patient characteristics to predict uncontrolled diabetes. Patients with diabetes above the age of 18 from the All of Us Research Program were included. Random forest, extreme gradient boost, logistic regression, and weighted ensemble model algorithms were employed. Patients who had a record of uncontrolled diabetes based on the international classification of diseases code were identified as cases. A set of features including basic demographic, biomarkers and hematological indices were included in the model. The random forest model demonstrated high performance in predicting uncontrolled diabetes, yielding an accuracy of 0.80 (95% CI: 0.79-0.81) as compared to the extreme gradient boost 0.74 (95% CI: 0.73-0.75), the logistic regression 0.64 (95% CI: 0.63-0.65) and the weighted ensemble model 0.77 (95% CI: 0.76-0.79). The maximum area under the receiver characteristics curve value was 0.77 (random forest model), while the minimum value was 0.7 (logistic regression model). Potassium levels, body weight, aspartate aminotransferase, height, and heart rate were important predictors of uncontrolled diabetes. The random forest model demonstrated a high performance in predicting uncontrolled diabetes. Serum electrolytes and physical measurements were important features in predicting uncontrolled diabetes. Machine learning techniques may be used to predict uncontrolled diabetes by incorporating these clinical characteristics.

Multiple Dyselectrolytemia in a Chronic Alcohol Abuser: A Case Report

Electrolyte disorders in alcohol-dependent patients can be due to a multitude of reasons. We discuss a patient with diabetes mellitus, seizure disorder, and alcoholism who presented with seizure episodes and vomiting following a binge alcohol intake. The evaluation showed life-threatening metabolic derangements that included hyponatremia, hypokalemia, hypomagnesemia, hypocalcemia, hypochloremia, hypophosphatemia with elevated blood glucose, and metabolic alkalosis with a normal anion gap. Subsequently, a detailed urinary analysis revealed a urinary loss of electrolytes. We emphasize that alcohol-induced tubular injury is a possibility when such a clinical presentation is seen in the emergency room. The complex interplay of various electrolytes in homeostasis posed a great challenge in the management of this patient. Our case reiterates this intricate electrolyte correction policy.

Association between Hypokalemia and Albuminuria in a Japanese General Population

INTRODUCTION

Hypokalemia is associated with an increased risk of chronic kidney disease (CKD) and is a risk factor for mortality. Albuminuria is an early manifestation of CKD. We investigated the association between hypokalemia and the prevalence of albuminuria in a Japanese general population.

METHODS

We analyzed the data of 18,289 subjects who underwent annual health checkups in 2018. We categorized them into four groups according to their concentration of serum potassium (sK) and performed a multivariate logistic regression analysis to determine the association between hypokalemia and the prevalence of albuminuria in this population. Hypokalemia was defined as having an sK = 3.1-3.5 mEq/L. After dividing the subjects into those with/without renal dysfunction, those with/without hypertension, and those with/without hyperglycemia, we examined the association between hypokalemia and albuminuria in each group.

RESULTS

Compared to the subjects with sK = 4.1-4.5 mEq/L, the subjects with hypokalemia had a significantly high prevalence of albuminuria: multivariable-adjusted odds ratio (OR) = 2.70 (95% confidence interval [CI] 1.84-3.96). The subgroup analyses showed the following multivariable-adjusted ORs (95% CIs) of the subjects: without renal dysfunction, 3.08 (2.00-4.73); with renal dysfunction, 2.05 (0.89-4.69); without hypertension, 2.89 (1.36-6.16); with hypertension, 2.60 (1.67-4.04); without hyperglycemia, 2.49 (1.62-3.84); and with hyperglycemia, 3.55 (1.43-8.79).

CONCLUSIONS

Hypokalemia was significantly associated with the high prevalence of albuminuria in general population. Regardless of the presence/absence of renal dysfunction, hypertension, or hyperglycemia, hypokalemia was positively associated with the prevalence of albuminuria, and the associations were significant except for the subjects with renal dysfunction.

Stable sensing platform for diagnosing electrolyte disturbance using laser-induced breakdown spectroscopy

Electrolyte disturbance is very common and harmful, increasing the mortality of critical patients. Hence, rapid and accurate detection of electrolyte levels is vital in clinical practice. Laser-induced breakdown spectroscopy (LIBS) has the advantage of rapid and simultaneous detection of multiple elements, which meets the needs of clinical electrolyte detection. However, the cracking caused by serum drying and the effect of the coffee-ring led to the unstable spectral signal of LIBS and inaccurate detection results. Herein, we propose the ordered microarray silicon substrates (OMSS) obtained by laser microprocessing, to solve the disturbance caused by cracking and the coffee-ring effect in LIBS detection. Moreover, the area of OMSS is optimized to obtain the optimal LIBS detection effect; only a 10 uL serum sample is required. Compared with the silicon wafer substrates, the relative standard deviation (RSD) of the serum LIBS spectral reduces from above 80.00% to below 15.00% by the optimized OMSS, improving the spectral stability. Furthermore, the OMSS is combined with LIBS to form a sensing platform for electrolyte disturbance detection. A set of electrolyte disturbance simulation samples (80% of the ingredients are human serum) was prepared for this platform evaluation. Finally, the platform can achieve an accurate quantitative detection of Na and K elements (Na: RSD < 6.00%, R² = 0.991; K: RSD < 4.00%, R² = 0.981), and the detection time is within 5 min. The LIBS sensing platform has a good prospect in clinical electrolyte detection and other blood-related clinical diagnoses.