Acute Metabolic Emergencies in Diabetes: DKA, HHS and EDKA

Euglycemic Diabetic Ketoacidosis and Thyroid Storm Occurring During Dapagliflozin Treatment

Euglycemic diabetic ketoacidosis (EDKA) is a type of DKA whose incidence has increased in recent years because of the widespread use of sodium-glucose transport protein 2 inhibitors in diabetes treatment. However, the concomitant occurrence of a thyroid storm is uncommon, easily misdiagnosed and missed, and has a high risk of death. This report described the case of a 46-year-old woman with type 2 diabetes mellitus who used a sodium-glucose transport protein 2 inhibitor to manage her blood glucose levels. Before undergoing hysteroscopic surgery for a uterine mass, she developed EDKA and thyroid storm after experiencing nausea, vomiting, and a high fever with persistent tachycardia. This report summarizes and analyzes the clinical characteristics, diagnosis, and treatment process and outcomes to accumulate clinical experience and improve clinicians' understanding of this acute and life-threatening disease. Timely and appropriate treatment may help reduce the incidence of morbidity and mortality associated with EDKA and thyroid storm.

Research Priorities for Diabetic Ketoacidosis: An Evidence and Gap Mapping Review

BACKGROUND/OBJECTIVES

Diabetic ketoacidosis (DKA) is a common acute complication of diabetes with treatment consisting of reversal of cause, insulin administration, fluid resuscitation and electrolyte repletion. Yet, many aspects of DKA management are currently based on low-quality evidence or physiological rationale. This evidence and gap map review presents an overview of the current body of literature and identifies evidence gaps in relation to therapeutic interventions for DKA.

METHODS

Interventions and outcomes relevant to DKA were identified and iteratively developed to produce a coding model for the proposed evidence and gap map. PubMed was searched with Me SH terms relevant to the identified interventions and outcomes. Studies identified were screened and assigned interventions and outcomes. Interventional research was uploaded to EPPI-Reviewer and EPPI-Mapper to produce the evidence and gap map.

RESULTS

The search identified 1131 studies, of which 18 were non-human and 345 were duplicates. A total of 768 unique studies were screened, and 118 were identified as interventions (52 pediatric and 66 adult studies). A total of 26 high-quality studies, 88 medium-quality studies and 4 low-quality studies were identified. These 118 studies were coded into the proposed DKA evidence and gap map. The intervention domains were fluid therapy, insulin therapy, electrolyte replacement, adjunct therapies and admission type. The outcome domains were DKA resolution, insulin duration, length of stay, morbidity and mortality, complications, and biochemical parameters.

CONCLUSIONS

Fluid type and insulin infusion administration were prominent in the current literature. These studies frequently used DKA resolution and complications associated with DKA such as electrolyte disturbances and cerebral edema as the primary outcomes. Substantial gaps were identified with scant evidence to guide prophylactic electrolyte administration, enteral intake and adjunctive therapy (thiamine, bicarbonate). Even for well-investigated interventions such as fluids and insulin, substantial gaps existed, particularly for patient-centered and healthcare service outcomes.

Development and validation of inpatient mortality prediction models for patients with hyperglycemic crisis using machine learning approaches

BACKGROUND

Hyperglycemic crisis is one of the most common and severe complications of diabetes mellitus, associated with a high motarlity rate. Emergency admissions due to hyperglycemic crisis remain prevalent and challenging. This study aimed to develop and validate predictive models for in-hospital mortality risk among patients with hyperglycemic crisis admitted to the emergency department using various machine learning (ML) methods.

METHODS

A multi-center retrospective study was conducted across six large general adult hospitals in Chongqing, western China. Patients diagnosed with hyperglycemic crisis were identified using an electronic medical record (EMR) database. Demographics, comorbidities, clinical characteristics, laboratory results, complications, and therapeutic interventions were extracted from the medical records to construct the prognostic prediction model. Seven machine learning algorithms, including support vector machines (SVM), random forest (RF), recursive partitioning and regression trees (RPART), extreme gradient boosting with dart booster (XGBoost), multivariate adaptive regression splines (MARS), neural network (NNET), and adaptive boost (AdaBoost) were compared with logistic regression (LR) for predicting the risk of in-hospital mortality in patients with hyperglycemic crisis. Stratified random sampling was used to split the data into training (80%) and validation (20%) sets. Ten-fold cross validation was performed on the training set to optimize model hyperparameters. The sensitivity, specificity, positive and negative predictive values, area under the curve (AUC) and accuracy of all models were computed for comparative analysis.

RESULTS

A total of 1668 patients were eligible for the present study. The in-hospital mortality rate was 7.3% (121/1668). In the training set, feature importance scores were calculated for each of the eight models, and the top 10 significant features were identified. In the validation set, all models demonstrated good predictive capability, with areas under the curve value exceeding 0.9 with a F1 score between 0.632 and 0.81, except the MARS model. Six machine learning algorithm models outperformed the referred logistic regression algorithm except the MARS model. Among the selected models, RPART, RF, and SVM achieved the best performance in the selected models (AUC values were 0.970, 0.968 and 0.968, F1 score were 0.652, 0.762, 0.762 respectively). Feature importance analysis identified novel predictors including mechanical ventilation, age, Charlson Comorbidity Index, blood gas index, first 24-hour insulin dosage, and first 24-hour fluid intake.

CONCLUSION

Most machine learning algorithms exhibited excellent performance predicting in-hospital mortality among patients with hyperglycemic crisis except the MARS model, and the best one was RPART model. These algorithms identified overlapping but different, up to 10 predictors. Early identification of high-risk patients using these models could support clinical decision-making and potentially improve the prognosis of hyperglycemic crisis patients.

CLINICAL TRIAL NUMBER

Not applicable.

Magnitude, risk factors and economic impacts of diabetic emergencies in developing countries: A systematic review

BACKGROUND

Diabetic ketoacidosis (DKA), hyperglycemic hyperosmolar syndrome (HHS) and severe hypoglycemia are considered as the life-threatening diabetic emergencies of diabetic patients worldwide. As the prevalence of diabetes grows in developing countries, so too does the impact of these costly human and economic complications. Noticeable scarcity of data concerning the magnitude, the cost expenditures as well as well unidentified predictors of these complications made the management more difficult in the resource limited health care settings. Thus, this systematic review aimed to assess the magnitude, risk factors and economic impacts of diabetes emergencies among diabetic patients in the developing countries.

METHODS

Following PRISMA (2020) guidelines, databases of PubMed, EMBASE, Cochrane and Scopus were searched for studies reporting on prevalence, risk factors, and direct costs of diabetes emergencies published in English from 2000 to 2023. Forty eligible studies were extracted and retrieved using manual data extraction form and automation tools. Studies were analyzed and combined in a narrative synthesis. The estimations of direct cost expenditure were standardized to 2023 USD.

RESULT

A comprehensive examination was conducted on the 40 eligible studies, with the majority originating from African sources. The review shows the prevalence of diabetic emergencies; DKA episodes in the range of (3.8%-73.4%), HHS (0.9%-58%) and Severe hypoglycemia (3.3%-64.7%) per year in the developing countries. Infection, new onset of the diabetes, and non-compliance to medications and diets were reported as the most common risk factors of theses diabetic emergencies. Besides, the costs of hospitalization taken from the patients' perspective, that were associated per one diabetic emergency event per patient was reported in the range of 105-230 USD in the developing countries.

CONCLUSION

The rising prevalence of diabetic emergencies in poor nations, where infections, non-compliance, and new onset of diabetes are major causes, highlighted the urgent need for preventative interventions. Identifying high-risk individuals is crucial for implementing tailored strategies to reduce emergency visits and hospital admissions. The significant economic burden of these emergencies exacerbates the strain on already limited healthcare resources. In order to enhance health outcomes and lessen the financial strain on healthcare systems in these areas, preventive strategies must be incorporated into diabetes management programs.

Incidence and predictors of hyperglycemic emergencies among adult diabetic patients at public hospitals of Sidama Region and Gedeo Zone, Southern Ethiopia: a survival analysis

Background

Hyperglycemic emergencies (HGEs) are the major deadliest acute complications of diabetes. HGEs have reached an alarming stage and increased year-to-year leading to increased morbidity, hospitalization, and mortality. Despite HGEs causing this increased healthcare, psychological, social, and economic burden, studies conducted to address this burden and its predictive factors remain limited. Thus, this study aimed to investigate the incidence and predictors of HGEs among adult diabetic patients.

Methods

An institution-based retrospective follow-up study was employed on 538 systematically selected adult diabetic patients who had diabetic follow-up in Sidama region and Gedeo zone public hospitals from September 1, 2018, to September 1, 2022. The sample size was determined using STATA V-14. Data were collected using an extraction checklist, entered into EPI data version 4.4.2.2, and analyzed using STATA version 14. The Kaplan-Meier curve and log-rank test were used to determine the survival probabilities and to compare the survival status. The Cox proportional hazard regression model was used to determine the association and identify the predictor variables. A statistical significance was declared at a p-value of <0.05 in line with a 95% confidence interval (CI) and hazard ratios.

Results

The study was conducted on 538 diabetic adult patients with a response rate of 100%. The mean age of study participants was 44.5 years, and more than 66.7% were males. The incidence rate of HGEs was found to be 29 (95% CI: 25.3-33.2) per 1000 person-months with a total of 7176.5 person-month observations. Being farmer (adjusted hazard ratio (AHR) = 6.47; 95% CI: 2.61-16.04), poor glycemic control (AHR = 6.84; 95% CI: 3.47-13.49), less frequent diabetic follow-up (AHR = 4.00; 95% CI: 1.02-15.57), and having hypertension (HTN) (AHR = 2.94; 95% CI: 1.62-5.34) were significantly associated with increased hazard of acquiring HGEs among adult diabetic patients. Conversely, the hazard of experiencing HGE was 63% lower among patients who had diabetic nephropathy relative to those without diabetic nephropathy (AHR = 0.35; 95% CI: 0.15-0.83). Hence, setting and strengthening specific diabetic management strategies focused on the identified predictors could be paramount to reducing HGEs and their unwanted effects. Moreover, it's better to consider more frequent diabetic follow-up visits for all patients regardless of other complications.

Impact of Charlson Comorbidity Index on in-hospital mortality of patients with hyperglycemic crises: A propensity score matching analysis

AIM

This study was designed to investigate the association between Charlson Comorbidity Index (CCI) and in-hospital mortality and other clinical outcomes among patients with hyperglycemic crises.

METHOD

This retrospective cohort study was conducted using data from electric medical records. A total of 1668 diabetic patients with hyperglycemic crises from six tertiary hospitals met the inclusion criteria. CCI < 4 was defined as low CCI and CCI ≥ 4 was defined as high CCI. Propensity score matching (PSM) with the 1:1 nearest neighbour matching method and the caliper value of 0.02 was used to match the baseline characteristics of patients with high CCI and low CCI to reduce the confounding bias. In-hospital mortality, ICU admission, hypoglycemia, hypokalemia, acute kidney injury, length of stay (LOS), and hospitalisation expense between low CCI and high CCI were compared and assessed. Univariate and multivariate regression were applied to estimate the impact of CCI on in-hospital and other clinical outcomes.

OUTCOME

One hundred twenty-one hyperglycemic crisis (HC) patients died with a mortality rate of 7.3%. After PSM, compared with low CCI, patients with high CCI suffered higher in-hospital mortality, ICU admission, LOS, and hospitalisation expenses. After multivariate regression, age (aOR: 1.12, 95% confidence interval [CI]: 1.06-1.18, p < 0.001), CCI(aOR: 4.42, 95% CI: 1.56-12.53, p = 0.005), uninsured (aOR: 22.32, 95% CI: 4.26-116.94, p < 0.001), shock (aOR: 10.57, 95% CI: 1.41-79.09, p = 0.022), mechanical ventilation (aOR: 75.29, 95% CI: 12.37-458.28, p < 0.001), and hypertension (aOR: 4.34, 95% CI: 1.37-13.82, p = 0.013) were independent risk factors of in-hospital mortality of HC patients. Besides, high CCI was an independent risk factor for higher ICU Admission (aOR: 5.91, 95% CI: 2.31-15.08, p < 0.001), hypoglycemia (aOR: 2.19, 95% CI:1.01-4.08, p = 0.049), longer LOS (aOR: 1.23, 95% CI: 1.19-2.27, p = 0.021), and higher hospitalisation expense (aOR: 2089.97, 95% CI: 193.33-3988.61, p = 0.031) of HC patients.

CONCLUSION

CCI is associated with in-hospital mortality, ICU admission, hypoglycemia, LOS, and hospitalisation expense of HC patients. CCI could be an ideal indicator to identify, monitor, and manage chronic comorbidities among HC patients.

The Assessment of Diabetic Ketoacidosis Awareness Among Diabetic Patients and Their Caregivers in Makkah, Saudi Arabia: A Cross-Sectional Study

INTRODUCTION

Diabetic ketoacidosis (DKA) is a life-threatening complication of diabetes mellitus (DM). It occurs due to a decrease in the level of insulin and an increase in the level of glucose in the blood, which makes cells unable to use glucose as an energy source and begin to break fat into ketones; an overload of ketones levels in the blood can lead to DKA. The aim of the study is to assess awareness of DKA among diabetic patients and their caregivers in Makkah City, Saudi Arabia.

METHODS

This study is a cross-sectional study collected through an online questionnaire of diabetic patients and their caregivers in Makkah City. A self-reported questionnaire designed in Arabic and English through the use of Google Forms, it distributed electronically via social media to the target population with the objectives of the survey.

RESULTS

A total of 400 participants were included, 73% of them were males, while 27% were females. A 9% of the participants have been diagnosed with DKA. A high awareness level about DKA was found in 32.5% of participants, while 67.5% had a poor awareness level. Factors associated with a high level of awareness towards DKA are young age, being single, students and having a previous DKA diagnosis.

CONCLUSION

Regarding our participants who have poor awareness of DKA, further education for diabetic patients and their caregivers about DKA is crucial to prevent life-threatening complications, and improve quality of life for these patients.

Inflammatory biomarkers predict higher risk of hyperglycemic crises but not outcomes in diabetic patients with COVID-19

BACKGROUND

Inflammation is a predictor of severe complications in patients with COVID-19 infection under a variety of clinical settings. A few studies suggested that COVID-19 infection was a trigger of hyperglycemic crises including diabetic ketoacidosis (DKA) and/or hyperglycemic hyperosmolar state (HHS). However, the association between inflammation and hyperglycemic crises in diabetic patients with COVID-19 infection is unclear.

METHODS

One hundred and twenty-four patients with type 2 diabetes mellitus (T2DM) and COVID-19 infection from January 2023 to March 2023 were retrospectively analyzed. Demographic, clinical, and laboratory data, especially inflammatory markers including white blood cell (WBC), neutrophils, neutrophil-to-lymphocyte ratio (NLR), c-reactive protein (CRP) and procalcitonin (PCT) were collected and compared between patients with or without DKA and/or HHS. Multivariable logistic regression analysis was conducted to explore the association between inflammatory biomarkers and the prevalence of hyperglycemic crises. Patients were followed up 6 months for outcomes.

RESULTS

Among 124 diabetic patients with COVID-19, 9 were diagnosed with DKA or HHS. Comparing COVID-19 without acute diabetic complications (ADC), patients with DKA or HHS showed elevated levels of c-reactive protein (CRP, P=0.0312) and procalcitonin (PCT, P=0.0270). The power of CRP and PCT to discriminate DKA or HHS with the area under the receiver operating characteristics curve (AUROC) were 0.723 and 0.794, respectively. Multivariate logistic regression indicated 1.95-fold and 1.97-fold increased risk of DKA or HHS with 1-unit increment of CRP and PCT, respectively. However, neither CRP nor PCT could predict poor outcomes in diabetic patients with COVID-19.

CONCLUSION

In this small sample size study, we firstly found that elevated serum CRP and PCT levels increased the risk of hyperglycemic crises in T2DM patients with COVID-19 infection. More study is needed to confirm our findings.

From diabetic hyperglycemia to cerebrovascular Damage: A narrative review

Diabetes mellitus is a globally significant disease that can lead to systemic complications, particularly vascular damage, including cardiovascular and cerebrovascular diseases of relevance. The physiological changes resulting from the imbalance in blood glucose levels play a crucial role in initiating vascular endothelial damage. Elevated glucose levels can also penetrate the central nervous system, triggering diabetic encephalopathy characterized by oxidative damage to brain components and activation of alternative and neurotoxic pathways. This brain damage increases the risk of ischemic stroke, a leading cause of mortality worldwide and a major cause of disability among surviving patients. The aim of this review is to highlight important pathways related to hyperglycemic damage that extend to the brain and result in vascular dysfunction, ultimately leading to the occurrence of a stroke. Understanding how diabetes mellitus contributes to the development of ischemic stroke and its impact on patient outcomes is crucial for implementing therapeutic strategies that reduce the incidence of diabetes mellitus and its complications, ultimately decreasing morbidity and mortality associated with the disease.

A Nutritional Approach to Optimizing Pump Therapy in Type 1 Diabetes Mellitus

Achieving optimal glucose control in individuals with type 1 diabetes (T1DM) continues to pose a significant challenge. While continuous insulin infusion systems have shown promise as an alternative to conventional insulin therapy, there remains a crucial need for greater awareness regarding the necessary adaptations for various special circumstances. Nutritional choices play an essential role in the efficacy of diabetes management and overall health status for patients with T1DM. Factors such as effective carbohydrate counting, assessment of the macronutrient composition of meals, and comprehending the concept of the glycemic index of foods are paramount in making informed pre-meal adjustments when utilizing insulin pumps. Furthermore, the ability to handle such situations as physical exercise, illness, pregnancy, and lactation by making appropriate adjustments in nutrition and pump settings should be cultivated within the patient-practitioner relationship. This review aims to provide healthcare practitioners with practical guidance on optimizing care for individuals living with T1DM. It includes recommendations on carbohydrate counting, managing mixed meals and the glycemic index, addressing exercise-related challenges, coping with illness, and managing nutritional needs during pregnancy and lactation. Additionally, considerations relating to closed-loop systems with regard to nutrition are addressed. By implementing these strategies, healthcare providers can better equip themselves to support individuals with T1DM in achieving improved diabetes management and enhanced quality of life.

Reducing Diabetic Ketoacidosis Readmissions with a Hospital-School-Based Improvement Partnership

Diabetic ketoacidosis (DKA) is the leading cause of morbidity and mortality in pediatric type 1 diabetes mellitus (T1D). Baseline data showed 139 of 182 DKA readmissions (76.4%) were due to missed basal insulin dosing. The team used quality improvement tools to implement a process change around basal insulin. The project utilized insulin degludec and school-based nurses when missed basal insulin was noted as a main driver for readmission. The DKA readmission rate averaged 5.25 per month from January 2017 to April 2019. The rate decreased to 3.64 per month during the intervention from May 2019 to March 2020, a 31% reduction over 11 months. This standardized approach for patients with T1D readmitted with DKA, using a school-based intervention and insulin degludec, reduced the number of DKA readmissions. This method is safe and effective for lowering DKA readmissions due to missed basal insulin in areas with reliable school nursing.

Cardiac Biomarkers and Risk Scores in Relation with History of Atherosclerotic Cardiovascular Disease in Patients Admitted with COVID-19: The Experience of an Eastern European Center

BACKGROUND

Data regarding the combined prognostic role of biomarkers and risk scores in relation with the history of atherosclerotic cardiovascular disease (ASCVD) in COVID-19 patients are lacking.

METHODS

The aim of this observational cohort study was to evaluate the combined prognostic value of N-terminal pro B-type natriuretic peptide (NT-pro BNP), troponin and risk scores in relation with ASCVD history in hospitalized COVID-19 patients. The primary composite endpoint was Intensive Care Unit (ICU) admission and death.

RESULTS

From April 2020 to June 2022, 1066 consecutive COVID-19 patients with available biomarkers upon admission were included. During a median follow-up period of 12 days, 176 patients (16.5%) died. Independent predictors of ICU admission and death in patients with ASCVD were NT-pro BNP (HR 2.63; 95% CI, 1.65-4.18) and troponin (HR 1.51; 95% CI, 1.13-2.03). In patients without ASCVD, only NT-pro BNP was predictive for the primary endpoint (HR 1.66; 95% CI, 1.10-2.53). This remained significant after adjustment for other relevant covariates (HR 3.54; 95% CI, 1.98-6.33) in patients with ASCVD and in patients without ASCVD (HR 1.82; 95% CI, 1.02-3.26).

CONCLUSIONS

These data showed the combined prognostic accuracy of NT-pro BNP and troponin in relation with ASCVD history for ICU admission and death in COVID-19 patients.

Endocrine Emergencies in the Medical Intensive Care Unit

Endocrine emergencies are underdiagnosed and often overlooked amid the management of severe multisystem pathologies in critically ill patients in the medical intensive care unit (ICU). In an appropriate clinical scenario, a low threshold of suspicion should be kept to investigate for various life-threatening, yet completely treatable, endocrinopathies. Prompt identification and treatment of endocrine emergencies such as diabetic ketoacidosis, myxedema coma, thyroid storm, and/or adrenal insufficiency leads to fewer complications, shorter ICU and hospital stay, and improved survival. This review article entails common endocrine emergencies encountered in the ICU and addresses their epidemiology, pathophysiology, clinical presentation and management.

Diabetic ketoacidosis

Diabetic ketoacidosis (DKA) is a form of a hyperglycemic emergency mainly characterized by the triad of hyperglycemia, ketosis, and anion gap metabolic acidosis. DKA may be the initial presentation in approximately 25-40 % of patients with type 1 diabetes. It may also occur in at least 34% of patients with type 2 diabetes. DKA has economic as well as medical implications. This review aims to explore and discuss diabetic ketoacidosis, its pathophysiology, clinical presentation, diagnosis, and management, including nuances in special populations such as pediatrics, obstetrics, and patients with chronic kidney disease.

Hypokalemia in Diabetes Mellitus Setting

Diabetes mellitus is a public health problem that affects millions of people worldwide regardless of age, sex, and ethnicity. Electrolyte disturbances may occur as a consequence of disease progression or its treatment, in particular potassium disorders. The prevalence of hypokalemia in diabetic individuals over 55 years of age is up to 1.2%. In patients with acute complications of diabetes, such as diabetic ketoacidosis, this prevalence is even higher. Potassium disorders, either hypokalemia or hyperkalemia, have been associated with increased all-cause mortality in diabetic individuals, especially in those with associated comorbidities, such as heart failure and chronic kidney disease. In this article, we discuss the main conditions for the onset of hypokalemia in diabetic individuals, briefly review the pathophysiology of acute complications of diabetes mellitus and their association with hypokalemia, the main signs, symptoms, and laboratory parameters for the diagnosis of hypokalemia, and the management of one of the most common electrolyte disturbances in clinical practice.

Acute esophageal necrosis complicating diabetic ketoacidosis in a patient with type II diabetes mellitus and excessive cola consumption: a case report

Acute esophageal necrosis (AEN) implicates poor tissue perfusion, functionally defective mucosal barrier, and corrosive injury of the esophageal mucosa, typically characterized by diffuse, circumferential greyish or black discoloration of the esophagus in esophagogastroduodenoscopy. Low-volume states, as diabetic ketoacidosis (DKA), predispose to AEN. Cola drinks diminish the esophageal pH by decreasing the lower esophageal sphincter pressure. We report a 47-year-old male shepherd with chest pain, nausea, odynophagia and gradual decline in level of consciousness, who reported consumption of 6-7 L of cola beverages per day, and was diagnosed with DKA. The patient had a record of type 2 diabetes mellitus and coronary heart disease, and he was administered empagliflozin 25 mg q24 hours, vildagliptin 50 mg bid, metformin 1000 mg bid, and insulin glargine 24 IU q 24. Esophagogastroduodenoscopy was indicative of a diffuse, edematous, and eroded mucosa of grey colour from the upper to the lower esophageal sphincter. CT scan supported the diagnosis, revealing diffuse thickening and edematous imaging of the esophageal wall with an abnormal edge of the mucosa in the lower half of the esophagus. Seven days after rigorous treatment with fluid resuscitation, insulin restoration, esomeprazole, fluconazole, cefoxitine, and metronidazole, the patient was ameliorated. A second endoscopy revealed obvious improvement. Pathophysiology, diagnosis, and treatment of DKA/AEN intertwining are thoroughly discussed. In conclusion, clinicians should not disregard AEN in the differential diagnosis of patients with DKA and clinical symptoms of esophagitis.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13340-021-00537-y.

Severe hypernatremia in soft drink ketoacidosis and hyperglycemic hyperosmolar state at the onset of type 2 diabetes mellitus: a case series of three adolescents

Diabetic ketoacidosis (DKA) and hyperglycemic hyperosmolar state (HHS) are diabetic emergencies. Some patients with a hyperglycemic crisis can present with an overlap of DKA and HHS. The coexistence of DKA and HHS is associated with higher mortality than in isolated DKA and HHS. In addition, electrolyte derangements caused by global electrolyte imbalance are associated with potentially life-threatening complications. Here, we describe three cases of mixed DKA and HHS with severe hypernatremia at the onset of type 2 diabetes mellitus. All patients had extreme hyperglycemia and hyperosmolarity with acidosis at the onset of diabetes mellitus. They consumed 2 to 3 L/d of high-carbohydrate drinks prior to admission to relieve thirst. They showed severe hypernatremia with renal impairment. Two patients recovered completely without any complications, while one died. Severe hypernatremia with mixed DKA and HHS is rare. However, it may be associated with excess carbohydrate beverage consumption. Reduced physical activity during the COVID19 pandemic and unhealthy eating behaviors worsened the initial presentation of diabetes mellitus. We highlight the impact of lifestyle factors on mixed DKA and HHS.

Diabetes-related acute metabolic emergencies in COVID-19 patients: a systematic review and meta-analysis

AIMS

COVID-19 is associated with diabetic ketoacidosis (DKA), hyperglycaemic hyperosmolar state (HHS) and euglycaemic DKA (EDKA); however, evidence regarding parameters affecting outcome and mortality rates is scarce.

METHODS

A systematic literature review was conducted using EMBASE, PubMed/Medline, and Google Scholar from January 2020 to 7 January 2021 to identify all studies describing clinical profile, outcome and mortality rates regarding DKA, HHS, DKA/HHS and EDKA cases in COVID-19 patients. The appropriate Joanna Briggs Institute tools were used for quality assessment; quality of evidence was approached using GRADE. Univariate and multivariate analyses were used to assess correlations between clinical characteristics and outcome based on case reports. Combined mortality rates (CMR) were estimated from data reported in case report series, cross-sectional studies, and meta-analyses. The protocol was submitted to PROSPERO (ID: 229356/230737).

RESULTS

From 312 identified publications, 44 were qualitatively and quantitatively analyzed. Critical COVID-19 necessitating ICU (P = 3 × 10-8), DKA/HHS presence (P = 0.021), and AKI (P = 0.037) were independently correlated with death. Increased COVID-19 severity (P = 0.003), elevated lactates (P < 0.001), augmented anion gap (P < 0.001), and AKI (P = 0.002) were associated with DKA/HHS. SGLT-2i were linked with EDKA (P = 0.004) and negatively associated with AKI (P = 0.023). CMR was 27.1% (95% CI 11.2-46.9%) with considerable heterogeneity (I 2 = 67%).

CONCLUSION

Acute diabetes-related metabolic emergencies in COVID-19 patients lead to increased mortality; key determinants are critical COVID-19 illness, coexistence of DKA/HHS and AKI. Previous SGLT-2i treatment, though associated with EDKA, might preserve renal function in COVID-19 patients.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13340-021-00502-9.

Calculated plasma osmolality at hospital admission correlates well with eGFR and D-Dimer, a simple outcome predictor and guiding tool for management of severe COVID-19 patients

AIMS

To evaluate calculated total plasma osmolality as a marker of outcome prediction, fluid and metabolic balance, thrombotic risk in severe COVID-19 patients.

METHODS

Retrospective data of RT-PCR confirmed hospitalized severe COVID-19 patients (total: n = 175 patients, including diabetic subset: n = 102) were analyzed. Clinically applicable cut-offs were derived using receiver operating characteristic (ROC) curve analysis for calculated total osmolality, eGFR, and D-dimer, and their correlations were studied.

RESULTS

Among 175 severe COVID-19 patients, a significant association with mortality was seen with respect to calculated total osmolality (p < 0.001), eGFR (p < 0.001), and D-dimer (p < 0.001). In the total cohort, applicable cut-offs based on ROC curve in predicting outcome were, for total osmolality 299 mosm/kg (area under the curve (AUC)-0.773, odds ratio (OR)-1.09), eGFR 61.5 ml/min/m2 (AUC-0.789, OR-0.96), D-dimer 5.13 (AUC-0.814, OR-2.65) respectively. In diabetic subset, the cut-offs for total osmolality were 298 mosm/kg (AUC-0.794, OR-1.12), eGFR 44.9 ml/min/m2 (AUC-0.774, OR-0.96) and D-dimer 1.59 (AUC-0.769, OR-1.52) respectively.

CONCLUSIONS

Applicable cut-offs for calculated total plasma osmolality, eGFR, and D-dimer predicts clinical outcome in severe COVID-19 with and without diabetes. Correlation studies validated calculated total osmolality as a marker of the combined effect of fluid and metabolic imbalance, compromised renal function and hypercoagulability.