Cardiovascular Risk Awareness, Exercise Practices and Metabolic Outcomes among Patients with Diabetes Mellitus in Northern Nigeria: A Cross-sectional, Multicentre Study.

BACKGROUND: Physical exercise helps to mitigate cardiovascular risks in people with diabetes mellitus (DM), but there are limited data in Nigeria. This study aimed to assess cardiovascular risk awareness, exercise practices and metabolic outcomes among Nigerians with diabetes. MATERIALS AND METHODS: We conducted a cross-sectional study at five tertiary hospitals using questionnaire interviews and clinical assessments. Participants' knowledge of cardiovascular risk factors and knowledge of exercise were assessed on 12- and 5-item scores, while exercise practices were classed as adequate if performed regularly on 3 or more days weekly for a total of 150 min or more based on the American Diabetes Association recommendations. Mean body mass index (BMI), blood pressure (BP), fasting blood glucose, serum haemoglobin A1C (HbA1c), lipid profile, urea, creatinine and uric acid were then compared among participant groups. RESULTS: We studied 426 participants with DM, 58.7% females. The mean age was 52.9 ± 13.1 years, with males significantly older than females (54.6 ± 12.2 vs. 51.8 ± 13.5 years; 95% confidence interval: 0.27-5.28, P = 0.03). The mean age at diabetes diagnosis was 44.8 ± 11.7 years, and the median duration of diabetes was 84 months. There was low knowledge of cardiovascular risk factors and low knowledge of exercise (mean scores of 2.94 and 2.31, respectively). Forty-three per cent of participants reported adequate exercise, which was significantly associated with younger age (P = 0.007), male gender (P = 0.001) and formal education (P = 0.021). Participants with adequate exercise had lower systolic BP and serum urea compared to those with inadequate exercise, but there were no significant differences in BMI, fasting glucose, HbA1c, serum lipids, creatinine or uric acid. CONCLUSION: Participants had low knowledge of cardiovascular risks and the appropriate exercise practices for diabetes patients. There is a need for better patient education on diabetes self-care and exercise at clinic visits.

[Decreased appetite is associated with a decreased cognitive function in elderly patients with diabetes].

OBJECTIVE: To examine the relationship between decreased appetite and the cognitive function in elderly diabetic patients. METHODS: The study subjects were outpatients with diabetes who were 60 years of age or older, and who were managed at Ise Red Cross Hospital. The cognitive function was assessed using a self-administered Dementia Checklist. The Japanese version of the Simplified Nutritional Appetite Questionnaire (SNAQ) was used to measure decreased appetite. A logistic regression analysis, in which the dependent variable was cognitive decline and the explanatory variables were appetite loss and adjustment variables, was used to calculate the odds ratio for cognitive decline according to the presence of appetite loss. RESULTS: Four hundred eighty patients were included in the analysis. Seventeen percent of the patients had decreased appetite and 21% had a decreased cognitive function. The unadjusted and adjusted odds ratios of cognitive decline for those with decreased appetite were 2.78 (95% confidence interval (CI), 1.66-4.65; P<0.001) and 2.26 (95% CI, 1.16-4.37; P=0.015), respectively, based on the absence of decreased appetite. CONCLUSION: Decreased appetite in elderly patients with diabetes was associated with a decreased cognitive function.

[Vegetable-first eating habits are associated with a reduced risk of mild cognitive impairment in elderly diabetic patients].

OBJECTIVE: To examine the relationship between vegetable-first eating habits and the cognitive function in elderly patients with diabetes. METHODS: The subjects were outpatients with diabetes ≥60 years old at Ise Red Cross Hospital. A self-administered dementia checklist was used to assess mild cognitive impairment and dementia. The participants were asked to fill out a questionnaire on their vegetable-first eating habits and were classified into 4 groups: 0, 1, 2, and 3 times a day. The dependent variables were mild cognitive impairment and dementia, and the explanatory variable was vegetable-first eating habits (0 as a reference). RESULTS: In total, 358 patients were included in the analysis. The number of vegetable-first meals was 0 in 153 (42.7%), 1 in 48 (13.4%), 2 in 46 (12.8%), and 3 in 111 (31.1%) patients. The adjusted odds ratios for 1, 2, and 3 times of mild cognitive impairment were 0.83 (95% confidence interval [CI], 0.35-1.94; P=0.680), 0.81 (95% CI, 0.32-2.00; P=0.653), and 0.37 (95% CI, 0.17-0.81; P=0.014), respectively. However, there was no significant association between vegetable-first eating habits and dementia. CONCLUSION: In elderly patients with diabetes, a vegetable-first eating habit at each meal was associated with a decreased risk of mild cognitive impairment.

[Relationship between the type and number of social participation events and the cognitive function in older diabetics].

OBJECTIVE: To examine the relationship between the type and number of social participation events and the cognitive function in elderly patients with diabetes. METHODS: The subjects were diabetic outpatients of ≥60 years of age who were managed at Ise Red Cross Hospital. Mild cognitive impairment (MCI) and dementia were assessed using a self-administered dementia checklist. Six types of social participation activities and the number of participants were investigated. A logistic regression analysis with MCI and dementia as dependent variables, social participation as an explanatory variable, and adjustment variables was used to calculate the odds ratios for social participation according to the presence of MCI and dementia. RESULTS: In total, 352 patients were included in the analysis. Volunteer activities (P=0.012), hobbies (P=0.006), activities to share skills and experiences (P=0.026), and work (P=0.003) were significantly associated with dementia. Regarding the association between the amount of social participation and dementia, there was a decrease in the risk of dementia when the number of social participation was 2. However, social participation was not significantly associated with MCI in this study. CONCLUSION: The type and number of social participation events were found to be associated with the risk of dementia in elderly patients with diabetes.

[Difficulty experienced by family in supporting elderly diabetic patients is associated with a decline in patients' higher-level functions].

OBJECTIVE: To examine the relationship between difficulties experienced by family in supporting elderly patients with diabetes and these patients' higher-level functions. METHODS: The subjects were outpatients with diabetes ≥65 years old at Ise Red Cross Hospital and their family members. The Tokyo Metropolitan Institute of Gerontology Index of Competence (TMIG-IC) was used to assess patients' higher-level functions. The Japanese version of the Diabetes Caregiver Activity and Support Scale (D-CASS-J) was used to measure difficulties experienced by family in supporting elderly patients with diabetes. Using a multiple regression analysis with TMIG-IC scores (instrumental ADL, intellectual activity, and social participation) as the dependent variable and D-CASS-J scores (based on the highest scoring Q1 group among the three quartiles of D-CASS-J scores) as the explanatory variables, standardized regression coefficients (ß) for higher-level functions on the family's perceived support difficulties were calculated. RESULTS: In total, 429 patients (254 male patients and 175 female patients) were included in the analysis. For male patients, the adjusted beta values for TMIG-IC scores in Q2 and Q3 were -0.039 (P=0.649) and -0.352 (P<0.001), respectively, and the adjusted beta values for the instrumental ADL scores were -0.064 (P=0.455), -0.192 (P=0.047), -0.090 (P=0.375), and -0.360 (P=0.002) for the Intellectually Active scores, respectively, and the adjusted beta for social role scores were 0.054 (P=0.581) and -0.261 (P=0.019), respectively. However, there was no association between the patients' higher-level functions and family support difficulties among female patients. CONCLUSIONS: Difficulty experienced by the family in supporting elderly male patients with diabetes is associated with reduced higher-level functioning.

The worldwide trend in diabetes awareness, treatment, and control from 1985 to 2022: a systematic review and meta-analysis of 233 population-representative studies.

Background: With the rapid increase in the prevalence of DM, studies on the awareness, treatment, and control of this condition are essential. Therefore, this study aimed to review the literature and pool the awareness, treatment, and control of diabetes at the global, regional, and national levels. Methods: In this systematic review and meta-analysis, several databases, including MEDLINE/PubMed, Institute of Scientific Information (ISI), Scopus, and Google Scholar, were searched using appropriate keywords up to June 2022. Observational studies investigating the awareness, treatment, and control of glucose levels among diabetic individuals were included. Awareness, treatment, and control were defined as the proportion of participants who were aware of their diabetes condition, treated pharmacologically, and achieved adequate glucose control, respectively. Two investigators independently conducted the study selection, data extraction, and quality assessment. Heterogeneity among studies was calculated using Chi-square, and a random-effect meta-analysis was used to pool the rates. Results: A total of 233 studies published between 1985 and 2022 met the inclusion criteria. The included studies had a combined population of 12,537,968. The pooled awareness of DM was 60% (95%CI: 56-63) and ranged from 41% (25-57) in low-income countries to 68% (64-72) in high-income countries, with no significant trend observed over the assessed periods at the global level. The pooled treatment of DM globally was 45% (42-48) and varied from 37% (31-43) in lower-middle-income countries to 53% (47-59) in high-income countries, showing variation over the examined time period. Before 2000, the proportion of adequate DM control was 16% (12-20), which significantly improved and reached 22% (19-25) after 2010. The pooled awareness, treatment, and control of DM were higher in females, high-income countries, and urban areas compared to males, upper and lower-middle-income countries, and rural areas, respectively. The older adults population had higher awareness and treatment rates than the adult population, but their DM control did not differ significantly. Conclusion: Despite the high level of awareness and treatment among the diabetic population, treatment success (control) is considerably low, particularly in low-income countries and rural areas. It is crucial to improve awareness, treatment, and control by strengthening the primary care system in all countries.

Diabetes technology: A primer for clinicians.

Diabetes technology is evolving rapidly and is changing the way both patients and clinicians approach the management of diabetes. With more devices gaining US Food and Drug Administration approval and insurance coverage expanding, these new technologies are being widely adopted by people living with diabetes. We provide a summary of the commonly available devices in the market today that clinicians will likely encounter. This includes continuous glucose monitors (CGMs); connected insulin pens, caps, and buttons; and insulin pumps. Clinicians' awareness of and familiarity with this technology will enhance its accessibility for patients with diabetes.

Incidence, Risk, and Clinical Course of New-Onset Diabetes in Long COVID: Protocol for a Systematic Review and Meta-Analysis of Cohort Studies.

BACKGROUND: COVID-19, an infectious disease pandemic, affected millions of people globally, resulting in high morbidity and mortality. Causing further concern, significant proportions of COVID-19 survivors endure the lingering health effects of SARS-CoV-2, the pathogen that causes COVID-19. One of the diseases manifesting as a postacute sequela of COVID-19 (also known as "long COVID") is new-onset diabetes. OBJECTIVE: The aim of this study is to examine the incidence of new-onset diabetes in patients with long COVID and assess the excess risk compared with individuals who tested negative for COVID-19. The study also aims to estimate the population-attributable fraction for COVID-19 as a risk factor for new-onset diabetes in long COVID and investigate the clinical course of new-onset diabetes cases. METHODS: This is a protocol for a systematic review and meta-analysis. PubMed, MEDLINE, Embase, Scopus, and Web of Science databases will be systematically searched to identify articles published between December 2019 and July 2024. A comprehensive search strategy for each database will be developed using a combination of Medical Subject Headings terms, subject headings, and text words to identify eligible studies. Cohort studies and randomized controlled trials (only control arms) involving patients with COVID-19 of any age, with follow-up data on new-onset diabetes in long COVID, will be considered for inclusion. Controls will comprise individuals who tested negative for COVID-19, with or without other respiratory tract infections. Three independent reviewers (AST, NB, and TT) will perform article selection, data extraction, and quality assessment of the studies. A fourth reviewer (ST) will review the identified studies for final inclusion in the analysis. The random-effects DerSimonian-Laird models will be used to estimate the pooled incidence proportion (%), incidence rate of diabetes (per 1000 person-years), and risk ratio (with 95% CIs) for diabetes incidence. RESULTS: A total of 1972 articles were identified through the initial search conducted in August 2023. After excluding duplicates, conducting title and abstract screening, and completing full-text reviews, 41 articles were found to be eligible for inclusion. The search will be updated in July 2024. Currently, data extraction is underway, and the meta-analysis is expected to be completed in August 2024. Publication of the study findings is anticipated by the end of 2024. CONCLUSIONS: The study findings should provide valuable insights to inform both clinical practice and public health policies regarding the effective management of new-onset diabetes in patients with long COVID. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/54853.

Smartphone based wearable sweat glucose sensing device correlated with machine learning for real-time diabetes screening.

BACKGROUND: Diabetes is a significant health threat, with its prevalence and burden increasing worldwide indicating its challenge for global healthcare management. To decrease the disease severity, the diabetic patients are recommended to regularly check their blood glucose levels. The conventional finger-pricking test possesses some drawbacks, including painfulness and infection risk. Nowadays, smartphone has become a part of our lives offering an important benefit in self-health monitoring. Thus, non-invasive wearable sweat glucose sensor connected with a smartphone readout is of interest for real-time glucose detection. RESULTS: Wearable sweat glucose sensing device is fabricated for self-monitoring of diabetes. This device is designed as a body strap consisting of a sensing strip and a portable potentiostat connected with a smartphone readout via Bluetooth. The sensing strip is modified by carbon nanotubes (CNTs)-cellulose nanofibers (CNFs), followed by electrodeposition of Prussian blue. To preserve the activity of glucose oxidase (GOx) immobilized on the modified sensing strip, chitosan is coated on the top layer of the electrode strip. Herein, machine learning is implemented to correlate between the electrochemical results and the nanomaterial content along with deposition cycle of prussian blue, which provide the highest current response signal. The optimized regression models provide an insight, establishing a robust framework for design of high-performance glucose sensor. SIGNIFICANCE: This wearable glucose sensing device connected with a smartphone readout offers a user-friendly platform for real-time sweat glucose monitoring. This device provides a linear range of 0.1-1.5 mM with a detection limit of 0.1 mM that is sufficient enough for distinguishing between normal and diabetes patient with a cut-off level of 0.3 mM. This platform might be an alternative tool for improving health management for diabetes patients.

Microstrip isoelectric focusing with deep learning for simultaneous screening of diabetes, anemia, and thalassemia.

BACKGROUND: Hemoglobin (Hb) is an important protein in red blood cells and a crucial diagnostic indicator of diseases, e.g., diabetes, thalassemia, and anemia. However, there is a rare report on methods for the simultaneous screening of diabetes, anemia, and thalassemia. Isoelectric focusing (IEF) is a common separative tool for the separation and analysis of Hb. However, the current analysis of IEF images is time-consuming and cannot be used for simultaneous screening. Therefore, an artificial intelligence (AI) of IEF image recognition is desirable for accurate, sensitive, and low-cost screening. RESULTS: Herein, we proposed a novel comprehensive method based on microstrip isoelectric focusing (mIEF) for detecting the relative content of Hb species. There was a good coincidence between the quantitation of Hb via a conventional automated hematology analyzer and the one via mIEF with R2 = 0.9898. Nevertheless, our results showed that the accuracy of disease diagnosis based on the quantification of Hb species alone is as low as 69.33 %, especially for the simultaneous screening of multiple diseases of diabetes, anemia, alpha-thalassemia, and beta-thalassemia. Therefore, we introduced a ResNet1D-based diagnosis model for the improvement of screening accuracy of multiple diseases. The results showed that the proposed model could achieve a high accuracy of more than 90 % and a good sensitivity of more than 96 % for each disease, indicating the overwhelming advantage of the mIEF method combined with deep learning in contrast to the pure mIEF method. SIGNIFICANCE: Overall, the presented method of mIEF with deep learning enabled, for the first time, the absolute quantitative detection of Hb, relative quantitation of Hb species, and simultaneous screening of diabetes, anemia, alpha-thalassemia, and beta-thalassemia. The AI-based diagnosis assistant system combined with mIEF, we believe, will help doctors and specialists perform fast and precise disease screening in the future.

Vulnerable plaque features and adverse events in patients with diabetes mellitus: a post hoc analysis of the COMBINE OCT-FFR trial.

BACKGROUND: Thin-cap fibroatheroma (TCFA) lesions are associated with a high risk of future major adverse cardiovascular events. However, the impact of other optical coherence tomography-detected vulnerability features (OCT-VFs) and their interplay with TCFA in predicting adverse events remains unknown. AIMS: We aimed to evaluate the individual as well as the combined prognostic impact of OCT-VFs in predicting the incidence of the lesion-oriented composite endpoint (LOCE) in non-ischaemic lesions in patients with diabetes mellitus (DM). METHODS: COMBINE OCT-FFR (ClinicalTrials.gov: NCT02989740) was a prospective, double-blind, international, natural history study that included DM patients with ≥1 non-culprit lesions with a fractional flow reserve>0.80 undergoing systematic OCT assessment. OCT-VFs included the following: TCFA, reduced minimal lumen area (r-MLA), healed plaque (HP), and complicated plaque (CP). The primary endpoint, LOCE - a composite of cardiac mortality, target vessel myocardial infarction, or clinically driven target lesion revascularisation up to 5 years - was analysed according to the presence of these OCT-VFs, both individually and in combination. RESULTS: TCFA, r-MLA, HP and CP were identified in 98 (25.3%), 190 (49.0%), 87 (22.4%), and 116 (29.9%) patients, respectively. The primary endpoint rate increased progressively from 6.3% to 55.6% (hazard ratio 15.2, 95% confidence interval: 4.53-51.0; p<0.001) in patients without OCT-VFs as compared to patients with concomitant HP, r-MLA, CP, and TCFA. The coexistence of TCFA with other OCT-VFs resulted in an increased risk of the LOCE at 5 years. CONCLUSIONS: In DM patients with non-ischaemic lesions, TCFA was the strongest predictor of future LOCE events. However, lesions that present additional OCT-VFs are associated with a higher risk of adverse events than OCT-detected TCFA alone. Further randomised studies are warranted to confirm these findings and their potential clinical implications.

The Effect of Nursing Approach on the Self-Management and Adjustment to the Illness among Newly Diagnosed Diabetic Patients According to Meleis's Transition Theory.

This study aimed to determine how the nursing approach based on Meleis's transition theory affects the self-management and adjustment to the illness among newly diagnosed diabetic patients. The study was conducted as one-group and pretest-posttest quasi-experimental design. The data were collected using the Introductory Questionnaire, the Diabetes Self-Management Questionnaire (DSMQ), and the Psychosocial Adjustment to Illness Scale-Self Report (PAIS-SR). It was determined that there was a positive increase in the total score of the DSMQ after the intervention, and a positive decrease in the total score of the PAIS-SR, and the difference between the scores were statistically significant (p < .05).

Voices of care: unveiling patient journeys in primary care for hypertension and diabetes management in Kerala, India.

Background: Diabetes and hypertension are leading public health problems, particularly affecting low- and middle-income countries, with considerable variations in the care continuum between different age, socio-economic, and rural and urban groups. In this qualitative study, examining the factors affecting access to healthcare in Kerala, we aim to explore the healthcare-seeking pathways of people living with diabetes and hypertension. Methods: We conducted 20 semi-structured interviews and one focus group discussion (FGD) on a purposive sample of people living with diabetes and hypertension. Participants were recruited at four primary care facilities in Malappuram district of Kerala. Interviews were transcribed and analyzed deductively and inductively using thematic analysis underpinned by Levesque et al.'s framework. Results: The patient journey in managing diabetes and hypertension is complex, involving multiple entry and exit points within the healthcare system. Patients did not perceive Primary Health Centres (PHCs) as their initial points of access to healthcare, despite recognizing their value for specific services. Numerous social, cultural, economic, and health system determinants underpinned access to healthcare. These included limited patient knowledge of their condition, self-medication practices, lack of trust/support, high out-of-pocket expenditure, unavailability of medicines, physical distance to health facilities, and attitude of healthcare providers. Conclusion: The study underscores the need to improve access to timely diagnosis, treatment, and ongoing care for diabetes and hypertension at the lower level of the healthcare system. Currently, primary healthcare services do not align with the "felt needs" of the community. Practical recommendations to address the social, cultural, economic, and health system determinants include enabling and empowering people with diabetes and hypertension and their families to engage in self-management, improving existing health information systems, ensuring the availability of diagnostics and first-line drug therapy for diabetes and hypertension, and encouraging the use of single-pill combination (SPC) medications to reduce pill burden. Ensuring equitable access to drugs may improve hypertension and diabetes control in most disadvantaged groups. Furthermore, a more comprehensive approach to healthcare policy that recognizes the interconnectedness of non-communicable diseases (NCDs) and their social determinants is essential.

Diabetes and Infectious Diseases with a Focus on Melioidosis.

Diabetes mellitus (DM) leads to impaired innate and adaptive immune responses. This renders individuals with DM highly susceptible to microbial infections such as COVID-19, tuberculosis and melioidosis. Melioidosis is a tropical disease caused by the bacterial pathogen Burkholderia pseudomallei, where diabetes is consistently reported as the most significant risk factor associated with the disease. Type-2 diabetes is observed in 39% of melioidosis patients where the risk of infection is 13-fold higher than non-diabetic individuals. B. pseudomallei is found in the environment and is an opportunistic pathogen in humans, often exhibiting severe clinical manifestations in immunocompromised patients. The pathophysiology of diabetes significantly affects the host immune responses that play a critical role in fighting the infection, such as leukocyte and neutrophil impairment, macrophage and monocyte inhibition and natural killer cell dysfunction. These defects result in delayed recruitment as well as activation of immune cells to target the invading B. pseudomallei. This provides an advantage for the pathogen to survive and adapt within the immunocompromised diabetic patients. Nevertheless, knowledge gaps on diabetes-infectious disease comorbidity, in particular, melioidosis-diabetes comorbidity, need to be filled to fully understand the dysfunctional host immune responses and adaptation of the pathogen under diabetic conditions to guide therapeutic options.

Asociación entre Glucemia inestable, tiempo de estancia y mortalidad de pacientes en estado críticos: Estudio de cohorte / Associação Entre Glicemia Instável, Tempo de Permanência e Mortalidade de Pacientes Críticos: Estudo de Coorte / Relationships between unstable Glycemia, Hospital Length Of Stay, and mortality In Critically Ill patients: A cohort study

Resumen Introducción: El control y la evaluación de los niveles glucémicos de pacientes en estado críticos es un desafío y una competencia del equipo de enfermería. Por lo que, determinar las consecuencias de esta durante la hospitalización es clave para evidenciar la importancia del oportuno manejo. Objetivo: Determinar la asociación entre la glucemia inestable (hiperglucemia e hipoglucemia), el resultado de la hospitalización y la duración de la estancia de los pacientes en una unidad de cuidados intensivos. Metodología: Estudio de cohorte prospectivo realizado con 62 pacientes a conveniencia en estado crítico entre marzo y julio de 2017. Se recogieron muestras diarias de sangre para medir la glucemia. Se evaluó la asociación de la glucemia inestable con la duración de la estancia y el resultado de la hospitalización mediante ji al cuadrado de Pearson. El valor de p<0.05 fue considerado significativo. Resultados: De las 62 personas participantes, 50 % eran hombres y 50 % mujeres. La edad media fue de 63.3 años (±21.4 años). La incidencia de glucemia inestable fue del 45.2 % y se asoció con una mayor duración de la estancia en la UCI (p<0.001) y una progresión a la muerte como resultado de la hospitalización (p=0.03). Conclusión: Entre quienes participaron, la glucemia inestable se asoció con una mayor duración de la estancia más prolongada y con progresión hacia la muerte, lo que refuerza la importancia de la actuación de enfermería para prevenir su aparición.

Resumo Introdução: O controle e avaliação dos níveis glicêmicos em pacientes críticos é um desafio e uma competência da equipe de enfermagem. Portanto, determinar as consequências da glicemia instável durante a hospitalização é chave para evidenciar a importância da gestão oportuna. Objetivo: Determinar a associação entre glicemia instável (hiperglicemia e hipoglicemia), os desfechos hospitalares e o tempo de permanência dos pacientes em uma unidade de terapia intensiva. Métodos: Um estudo de coorte prospectivo realizado com 62 pacientes a conveniência em estado crítico entre março e julho de 2017. Foram coletadas amostras diariamente de sangue para medir a glicemia. A associação entre a glicemia instável com o tempo de permanência e o desfecho da hospitalização foi avaliada pelo teste qui-quadrado de Pearson. O valor de p <0,05 foi considerado significativo. Resultados: Das 62 pessoas participantes, 50% eram homens e 50% mulheres. A idade média foi de 63,3 anos (±21,4 anos). A incidência de glicemia instável foi de 45,2% e se associou a um tempo de permanência mais prolongado na UTI (p <0,001) e uma progressão para óbito como desfecho da hospitalização (p = 0,03). Conclusão: Entre os participantes, a glicemia instável se associou a um tempo mais longo de permanência e com progressão para óbito, enfatizando a importância da actuação da equipe de enfermagem para prevenir sua ocorrência.

Abstract Introduction: The control and evaluation of glycemic levels in critically ill patients is a challenge and a responsibility of the nursing team; therefore, determining the consequences of this during hospitalization is key to demonstrate the importance of timely management. Objective: To determine the relationship between unstable glycemia (hyperglycemia and hypoglycemia), hospital length of stay, and the hospitalization outcome of patients in an Intensive Care Unit (ICU). Methods: A prospective cohort study conducted with 62 critically ill patients by convenience sampling between March and July 2017. Daily blood samples were collected to measure glycemia. The correlation of unstable glycemia with the hospital length of stay and the hospitalization outcome was assessed using Pearson's chi-square. A p-value <0.05 was considered significant. Results: Among the 62 patients, 50% were male and 50% were female. The mean age was 63.3 years (±21.4 years). The incidence of unstable glycemia was 45.2% and was associated with a longer ICU stay (p<0.001) and a progression to death as a hospitalization outcome (p=0.03). Conclusion: Among critically ill patients, unstable glycemia was associated with an extended hospital length of stay and a progression to death, emphasizing the importance of nursing intervention to prevent its occurrence.

Explainable hypoglycemia prediction models through dynamic structured grammatical evolution.

Effective blood glucose management is crucial for people with diabetes to avoid acute complications. Predicting extreme values accurately and in a timely manner is of vital importance to them. People with diabetes are particularly concerned about suffering a hypoglycemia (low value) event and, moreover, that the event will be prolonged in time. It is crucial to predict hyperglycemia (high value) and hypoglycemia events that may cause health damages in the short term and potential permanent damages in the long term. This paper describes our research on predicting hypoglycemia events at 30, 60, 90, and 120 minutes using machine learning methods. We propose using structured Grammatical Evolution and dynamic structured Grammatical Evolution to produce interpretable mathematical expressions that predict a hypoglycemia event. Our proposal generates white-box models induced by a grammar based on if-then-else conditions using blood glucose, heart rate, number of steps, and burned calories as the inputs for the machine learning technique. We apply these techniques to create three types of models: individualized, cluster, and population-based. They all are then compared with the predictions of eleven machine learning techniques. We apply these techniques to a dataset of 24 real patients of the Hospital Universitario Principe de Asturias, Madrid, Spain. The resulting models, presented as if-then-else statements that incorporate numeric, relational, and logical operations between variables and constants, are inherently interpretable. The True Positive Rate and True Negative Rate metrics are above 0.90 for 30-minute predictions, 0.80 for 60 min, and 0.70 for 90 min and 120 min for the three types of models. Individualized models exhibit the best metrics, while cluster and population-based models perform similarly. Structured and dynamic structured grammatical evolution techniques perform similarly for all forecasting horizons. Regarding the comparison of different machine learning techniques, on the shorter forecasting horizons, our proposals have a high probability of winning, a probability that diminishes on the longer time horizons. Structured grammatical evolution provides advanced forecasting models that facilitate model explanation, modification, and retesting, offering flexibility for refining solutions post-creation and a deeper understanding of blood glucose behavior. These models have been integrated into the glUCModel application, designed to serve people with diabetes.

Long-term health conditions among household families in Aotearoa New Zealand: cross-sectional analysis of integrated Census and administrative data.

AIM: Little is known about the extent to which families in Aotearoa New Zealand are affected by long-term health conditions (HCs). This study aimed to explore the rates of nine selected HCs among New Zealand family members within the same household. METHOD: Linked population and administrative health data were obtained for families living in the same household according to the 2013 New Zealand Census (N=1,043,172). Health data (2008-2013) were used to ascertain whether people in these families (N=3,137,517) received treatment or services for nine selected HCs: cancer, chronic obstructive pulmonary disease, heart disease, diabetes, dementia, gout, stroke, traumatic brain injury (TBI), or mental health/behaviour conditions (MHBCs). RESULTS: Over 60% of families included at least one person with a HC, and this rate was higher among multi-generation families (73.9%). The most common HCs were MHBCs (39.4% of families), diabetes (16.0%) and TBI (13.9%). At the highest level of socio-economic deprivation, 57.6% of children aged under 18 years lived with a family member who had a HC. CONCLUSION: Three in five New Zealand household families included someone with at least one of nine selected HCs, with differences in the proportion affected according to family composition, socio-economic status and an individual's ethnicity. This suggests that there are a substantial number of people at risk of the poor outcomes associated with the experience of HCs within their family.

External validation of three diabetes prediction scores in a Spanish cohort: does adding high risk for depression improve the validation of the FINDRISC score (FINDRISC-MOOD)?

OBJECTIVES: To evaluate the external validity of the FINDRISC, DESIR and ADA risk scores for the prediction of diabetes in a Spanish population aged >45 years and to test the possible improvement of FINDRISC by adding a new variable of high risk of depression when Patient Health Questionnaire-9 (PHQ-9) questionnaire score ≥10 (FINDRISC-MOOD). DESIGN: Prospective population-based cohort study. SETTING: 10 primary healthcare centres in the north of the city of Madrid (Spain). PARTICIPANTS: A total of 1242 participants without a history of diabetes and with 2-hour oral glucose tolerance test (OGTT) plasma glucose <200 mg/dL (<11.1 mmol/L) were followed up for 7.3 years (median) using their electronic health records (EHRs) and telephone contact. PRIMARY AND SECONDARY OUTCOME MEASURES: Diabetes risk scores (FINDRISC, DESIR, ADA), PHQ-9 questionnaire and 2-hour-OGTT were measured at baseline. Incident diabetes was defined as treatment for diabetes, fasting plasma glucose ≥126 mg/dL (≥7.0 mmol/L), new EHR diagnosis or self-reported diagnosis. External validation was performed according to optimal cut-off, sensitivity, specificity and Youden Index. Comparison between diabetes risk scores, including FINDRISC-MOOD (original FINDRISC score plus five points if PHQ-9 ≥10), was measured by area under the receiver operating characteristic curve (AUROC). RESULTS: During follow-up, 104 (8.4%; 95% CI, 6.8 to 9.9) participants developed diabetes and 185 had a PHQ-9 score ≥10. The AUROC values were 0.70 (95% CI, 0.67 to 0.72) for FINDRISC-MOOD and 0.68 (95% CI, 0.65 to 0.71) for the original FINDRISC. The AUROCs for DESIR and ADA were 0.66 (95% CI, 0.63 to 0.68) and 0.66 (95% CI, 0.63 to 0.69), respectively. There were no significant differences in AUROC between FINDRISC-MOOD and the other scores. CONCLUSIONS: The results of FINDRISC-MOOD were like those of the other risk scores and do not allow it to be recommended for clinical use.

Association between blood lipids and diabetes mellitus in older Chinese adults aged 65 years or older: a cross-sectional analysis of residents' electronic health records.

AIM: This study aimed to investigate how blood lipids are associated with diabetes among older Chinese adults. METHODS: 3,268,928 older Chinese adults without known diabetes were included. Logistic regression and restricted cubic spline (RCS) models were conducted to study associations between blood lipids (total cholesterol [TC], triglycerides [TG], low-density lipoprotein cholesterol [LDL-C], and high-density lipoprotein cholesterol [HDL-C]) and diabetes. RESULTS: 202,832 diabetes cases were included. Compared with the lowest quintiles, TC, TG, and LDL-C in the highest quintiles showed a higher diabetes prevalence risk and HDL-C presented a lower risk in multivariate-adjusted logistic regression models. Odds ratios (ORs) and 95% confidence intervals (95% CIs) for the highest quintiles of TC, TG, and HDL-C were 1.39 (1.37-1.41), 2.56 (2.52-2.60), and 0.73 (0.72-0.74), respectively. For LDL-C, 3-5% lower risk was found in the second and third quintiles, and 4-23% higher risk was found in the fourth and fifth quintiles. RCS curves showed a non-linear relationship between each blood lipid parameters and diabetes (P-non-linear < 0.001). TG and HDL-C curves presented monotonically increasing and L-shaped patterns, respectively, whereas TC and LDL-C curves exhibited a J-shaped pattern. When TC < 4.04 mmol/L or LDL-C < 2.33 mmol/L, ORs of diabetes increased with the decrease of corresponding indexes. However, after excluding participants with lower LDL-C, the J-shaped association with TC disappeared. CONCLUSIONS: This study demonstrates non-linear associations between lipids and diabetes. Low cholesterol levels are associated with a high risk of diabetes. The cholesterol paradox should be considered during lipid-lowering treatments.