Unstable Blood Glucose Levels Research Articles

Clinical validity of the nursing diagnosis risk for unstable blood glucose level in persons with type 2 diabetes mellitus: A case-control study.

To assess clinical-causal validity evidence of the nursing diagnosis, risk for unstable blood glucose level (00179), in individuals with type 2 diabetes mellitus. A case-control study was conducted in 5 primary healthcare units, involving 107 subjects with type 2 diabetes mellitus, 60 in the case group and 47 in the control group. Causality was determined by the association between sociodemographic and clinical factors, risk factors related to the nursing diagnosis, and the occurrence of unstable blood glucose level. An association was considered when the risk factor had a p-value of <0.05 and odds ratio >1. Risk factors, such as stress, inadequate physical activity, and low adherence to therapeutic regimen, were prevalent in the sample. Time since diagnosis between 1-5 and 6-10 years, multiracial ethnicity, and the risk factor of low adherence to therapeutic regimen increased the likelihood of the outcome. Completion of high school education was identified as a protective factor. The clinical validation of the nursing diagnosis, risk for unstable blood glucose level, has been successfully established, revealing a clear association between sociodemographic and clinical factors and the risk factors inherent to the nursing diagnosis. The results contribute to advancing scientific knowledge related to nursing education, research, and practice and provide support for the evolution of nursing care processes for individuals with type 2 diabetes mellitus.

Progressive Muscle Relaxation for Anxiety and Hyperglycemia in Diabetes Mellitus Type 2 Patient: A Case-Study

Hyperglycemia is the main symptom in patients with diabetes mellitus. One of the risk factors that can increase blood sugar levels in diabetes mellitus (DM) patients is anxiety and stress, as a result of diabetes mellitus sufferers who experience anxiety, their physical condition does not improve, and their blood sugar levels are always high. Progressive muscle relaxation therapy (PMR) is a therapy that aims to focus the patient's attention so that they can differentiate the feelings that occur when the muscles are relaxed or relaxed from when they are contracting so that the patient can manage their body condition against their anxiety. This study aims to analyze the provision of progressive muscle relaxation therapy to control anxiety levels and blood sugar levels in patients with type 2 diabetes mellitus in the Gardena medical ward of Dr. Soebandi Hospital Jember. This research uses descriptive methods in the form of case studies on a patient with Type 2 DM. Therapy was given once a day for 20-30 minutes. Anxiety levels were measured using the DASS questionnaire, and blood sugar measurements were made using a blood sugar stick. After being given PMR therapy for 3 x 24 hours, the patients experienced a decrease in anxiety levels and blood sugar levels. Providing PMR therapy is effective in treating unstable blood glucose levels and anxiety for patient with Type 2 DM.

Stress-induced hyperglycemia is associated with the mortality of thrombotic thrombocytopenic purpura patients

BackgroundThrombotic thrombocytopenic purpura (TTP) is a rare thrombotic microangiopathy with a rapid progression and high mortality rate. We aimed to explore early risk factors for mortality in patients with TTP.MethodsWe conducted a retrospective analysis of 42 TTP patients that were admitted to our hospital between 2000 and 2021, with a median age of 49 (29–63) years. Risk factors for mortality were evaluated using multivariate logistic regression. Receiver operating characteristic curve analysis was used to determine the cut-off value of glucose for predicting mortality in patients, which was validated by comparison to a similar cohort in the published literature.ResultsElevated glucose level and reduced red blood cells (RBC) counts were risk factors for mortality in patients with TTP (glucose, odds ratio and 95% confidence interval: 2.476 [1.368–4.484]; RBC, odds ratio and 95% confidence interval: 0.095 [0.011–0.799]). The area under the curve of glucose was 0.827, and the cut-off value was 9.2 mmol/L, with a sensitivity of 75.0% and specificity of 95.8%. A total of 26 cases from the validation cohort had a sensitivity of 71.0% and a specificity of 84.0%. The change trends of the TTP-related laboratory indices differed during hospitalization.ConclusionHyperglycemia at admission and unstable blood glucose levels during hospitalization may be potential predictors of mortality for TTP patients. The improved prognosis was associated with the recovery of platelet counts and a significant decrease in serum lactate dehydrogenase after five days of treatment.

Prevalence and clustering of NANDA-I nursing diagnoses in the pre-hospital emergency care setting: A retrospective records review study.

To determine the prevalence and clustering of NANDA-International nursing diagnoses in patients assisted by pre-hospital emergency teams. Retrospective descriptive study of electronic record review. Episodes recorded during 2019, including at least a nursing diagnosis, were recovered from the electronic health records of a Spanish public emergency agency (N = 28,847). Descriptive statistics were used to characterize the sample and determine prevalence. A two-step cluster analysis was used to group nursing diagnoses. A comparison between clusters in sociodemographic and medical problems was performed. Data were accessed in November 2020. Risk for falls (00155) (27.3%), Anxiety (00146) (23.2%), Acute pain (00132), Fear (00148) and Ineffective breathing pattern (00032) represented 96.1% of all recorded diagnoses. A six-cluster solution (n = 26.788) was found. Five clusters had a single high-prevalence diagnosis predominance: Risk for falls (00155) in cluster 1, Anxiety (00146) in cluster 2, Fear (00148) in cluster 3, Acute pain (00132) in cluster 4 and Ineffective breathing pattern (00032) in cluster 6. Cluster 5 had several high prevalence diagnoses which co-occurred: Risk for unstable blood glucose level (00179), Ineffective coping (00069), Ineffective health management (00078), Impaired comfort (00214) and Impaired verbal communication (00051). Five nursing diagnoses accounted for almost the entire prevalence. The identified clusters showed that pre-hospital patients present six patterns of nursing diagnoses. Five clusters were predominated by a predominant nursing diagnosis related to patient safety, coping, comfort, and activity/rest, respectively. The sixth cluster grouped several nursing diagnoses applicable to exacerbations of chronic diseases. Knowing the prevalence and clustering of nursing diagnoses allows a better understanding of the human responses of patients attended by pre-hospital emergency teams and increases the evidence of individualized/standardized care plans in the pre-hospital clinical setting. What problem did the study address? There are different models of pre-hospital emergency care services. The use of standardized nursing languages in the pre-hospital setting is not homogeneous. Studies on NANDA-I nursing diagnoses in the pre-hospital context are scarce, and those available are conducted on small samples. What were the main findings? This paper reports the study with the largest sample among the few published on NANDA-I nursing diagnoses in the pre-hospital care setting. Five nursing diagnoses represented 96.1% of all recorded. These diagnoses were related to patients' safety/protection and coping/stress tolerance. Patients attended by pre-hospital care teams are grouped into six clusters based on the nursing diagnoses, and this classification is independent of the medical conditions the patient suffers. Where and on whom will the research have an impact? Knowing the prevalence of nursing diagnoses allows a better understanding of the human responses of patients treated in the pre-hospital setting, increasing the evidence of individualized and standardized care plans for pre-hospital care. STROBE checklist has been used as a reporting method. Only patients' records were reviewed without further involvement.

Gambaran Diagnosis Keperawatan Pada Pasien Diabetes Melitus di Rumah Sakit Umum Daerah Tugurejo Semarang

DM (Diabetes Mellitus) is a metabolic disorder characterized by insulin hormone deficiency. Patients with DM exhibit various signs and symptoms, which serve as the basis for nursing diagnoses by nurses. This study aims to describe nursing diagnoses in DM patients at Tugurejo Hospital in Semarang. The research design employed was quantitative research using a survey analysis approach of medical record documents. The sample consisted of 112 medical record documents of DM patients who were hospitalized at Tugurejo Hospital in Semarang from October to December 2022. Data were analyzed using univariate analysis (descriptive analysis) with frequency distribution. Data were collected using a nursing diagnosis checklist that had been adapted to the Indonesian Standard Classification of Diseases. The results showed that the majority of DM patients were aged 45-60 years (54%), and the majority were female (61%). The most frequently occurring nursing diagnoses in DM patients were acute pain (46.4%), unstable blood glucose levels (45.5%), and impaired skin/tissue integrity (22%). The other frequently occurring nursing diagnosis was nausea (16%). The majority of nursing diagnoses were actual nursing diagnoses. Nurses and hospitals are expected to meet the basic needs of DM patients, especially in addressing acute pain issues.

Nursing Care Of Type Ii Diabetes Mellitus Patients

Background: Type II Diabetes Mellitus is a chronic disease with a high prevalence in Indonesia. As nursing care providers, nurses have an essential role in managing patients with type II Diabetes Mellitus. Purpose: Get an overview of the implementation of nursing care in patients with Type II Diabetes Mellitus. Methodology: A case study was conducted on Mrs. D in Dahlia Room RSUD Ciamis on 27 - 30 June 2022. Results: The results of the nursing evaluation obtained: ineffective peripheral perfusion, acute pain, nutritional deficits, impaired skin integrity, unstable blood glucose levels, impaired physical mobility, and disturbed sleep patterns are partially resolved, and the risk of hypovolemia has been determined. Conclusion: Nursing care carried out can overcome the problems experienced by patients.

Newly diagnosed type 1 diabetes mellitus in a human immunodeficiency virus-infected patient with antiretroviral therapy-induced immune reconstitution inflammatory syndrome: a case report

BackgroundDiabetes that develops in human immunodeficiency virus (HIV)-infected patients who receive antiretroviral therapy (ART) is usually type 2 diabetes mellitus (T2DM); however, autoimmune diabetes, such as type 1 diabetes mellitus (T1DM) can also develop in this population. After treatment with ART, patients might experience clinical deterioration following an increase in the CD4 cell count, which is termed immune reconstitution inflammatory syndrome (IRIS). Here, we describe an HIV-infected patient on ART who developed T1DMat due to IRIS, highlighting the clinical complexity in diagnosis and treatment.Case presentationA 36-year-old man infected with HIV had a nadir CD4 cell count of 15.53/μL before medication, which increased to 429.09/μL after 9 months of regular ART. The fasting serum glucose at 9 months was between 96 mg/dL and 117 mg/dL. After 11 months of ART, the patient was admitted to hospital for diabetic ketoacidosis (DKA) and Graves’ disease (GD). Noninsulin antidiabetics (NIADs) were prescribed following the resolution of DKA. However, poor glycemic control was noted despite well-titrated NIADs. Further investigation demonstrated poor pancreatic beta cell function and elevated anti-glutamic acid decarboxylase (anti-GAD) and anti-tyrosine phosphatase-like insulinoma antigen 2 (anti-IA2) titers. According to the results, he was diagnosed with T1DM and received multiple daily injections(MDI) of insulin. The regimen of MDI was insulin degludec as basal insulin and insulin aspart as prandial insulin. After MDI therapy, his glycemic control was improved.ConclusionIn this case, T1DM was ascribed to IRIS. Although this phenomenon has been demonstrated in previous case reports, further study is necessary to realize the mechanism of this association. Therefore, we emphasize that when HIV-infected patients on ART experience an unstable blood glucose level and abnormal thyroid function, physicians should consider T1DM and GD associated with ART-induced IRIS to reduce the subsequent complications and more serious endocrine dysfunction.

Diagnostic concordance among nursing clinical decision support system users: a pilot study.

To analyze the nursing diagnostic concordance among users of a clinical decision support system (CDSS), The Electronic Documentation System of the Nursing Process of the University of São Paulo (PROCEnf-USP®), structured according to the Nanda International, Nursing Intervention Classification and Nursing Outcome Classification (NNN) Taxonomy. This pilot, exploratory-descriptive study was conducted from September 2017 to January 2018. Participants were nurses, nurse residents, and nursing undergraduates. Two previously validated written clinical case studies provided participants with comprehensive initial assessment clinical data to be registered in PROCEnf-USP®. After having registered the clinical data in PROCEnf-USP®, participants could either select diagnostic hypotheses offered by the system or add diagnoses not suggested by the system. A list of nursing diagnoses documented by the participants was extracted from the system. The concordance was analyzed by Light's Kappa (K). The research study included 37 participants, which were 14 nurses, 10 nurse residents, and 13 nursing undergraduates. Of the 43 documented nursing diagnoses, there was poor concordance (K = 0.224) for the diagnosis "Ineffective airway clearance" (00031), moderate (K = 0.591) for "Chronic pain" (00133), and elevated (K = 0.655) for "Risk for unstable blood glucose level" (00179). The other nursing diagnoses had poor or no concordance. Clinical reasoning skills are essential for the meaningful use of the CDSS. There was concordance for only 3 nursing diagnoses related to biological needs. The low level of concordance might be related to the clinical judgment skills of the participants, the written cases, and the sample size.

Aktivitas Fisik Jalan Santai Untuk Penanganan Ketidakstabilan Kadar Glukosa Darah Pada Pasien Diabetes Mellitus

&#x0D; &#x0D; &#x0D; Introduction: Instability of blood glucose levels (hyperglycemia) is a condition of increased blood glucose levels that can take place acutely and chronically caused by heredity, obesity, overeating, lack of exercise, and lifestyle changes. One of the diseases that can cause unstable blood glucose levels is Diabetes Mellitus. In the case of Diabetes Mellitus, it is caused by an increase in blood glucose levels which is characterized by the absence of insulin in the body accompanied by the classic symptoms of Diabetes Mellitus, namely polyuria, polydipsia, polyphagia. The Aim of this study is to describe the physical activity of leisure walking to reduce blood glucose levels in patients with Diabetes Mellitus. This research method uses a descriptive case study method by analyzing in depth a research object whose unit of analysis is individual from assessment, diagnosis, intervention, implementation and evaluation. Two respondents with a medical diagnosis of Diabetes Mellitus were selected using a purposive sampling technique. Results: The results showed that on the third day of R1, patients said they were tired or lethargic (decreased), patients said they had increased thirst (decreased), high blood glucose levels (improved), GDA: 90 mg/dL the problem was resolved. Whereas in patient R2 the patient said he was tired or lethargic (decreased) and had high blood glucose levels (improved), GDA: 165 mg/dL and the problem was resolved. Conclusion: After being given nursing care with leisurely walking physical activity to 2 patients, it can be concluded that this therapy can reduce blood glucose levels in Diabetes Mellitus patients.&#x0D; &#x0D; &#x0D;

Analytical study of relationship between diabetes mellitus and COVID-19 (literature review)

In modern society Diabetes Mellitus (DM) is one of the topic health issues. DM is one of the main risk factors for severe diseases and chronic complications that may arise from COVID-19. There are some reasons why patients with DM may be more susceptible to the severe effects of COVID-19: unstable blood glucose level, weakened immune system, greater susceptibility to infections, micro- and macrovascular damage. Current studies on the COVID-19 pandemic confirm that DM is the most common associated disease in patients with COVID-19. There is increasing evidence that COVID-19 can lead to the development of type 1 and type 2 DM. However, it is important to note that the conclusions are based on a limited data in this review, and now require further research to confirm. More detailed and objective studies are needed to determine more accurate detection rate of newly diagnosed DM (NDD). The authors conducted a review of literature sources to identify NDD due to СОVID-19. In this review, we aimed to highlight the two-way relationship between DM and COVID-19 by examining the published data and their generalizations on NDD after COVID-19. According to the results of analysis it was concluded that patients had diabetes were being associated with a higher risk of acquiring COVID-19, placing them at greater risk for the severity and lethality of COVID-19, patients had an elevated incidence risk for NDD after COVID-19. Keywords: newly diagnosed diabetes mellitus, hyperglycemia, diabetic ketoacidosis, SARS-CoV-2.

A novel blood glucose time series prediction framework based on a novel signal decomposition method

Unstable blood glucose levels will bring about a series of complications, and even threaten our life in severe cases. Therefore, accurately predicting and controlling blood glucose has become an indispensable part of diabetes treatment. For the sake of boosting the accuracy of blood glucose prediction, a novel time-frequency signal analytical technology called improved ensemble empirical mode decomposition based on fractal dimension (FEEMD) is first proposed to decompose the nonlinear and non-stationary raw blood glucose series to obtain intrinsic mode functions (IMFs) and residual components (Rs) in different frequency bands. Then, in order to overcome the problem that the kernel extreme learning machine (KELM) is easy to fall into the local optimum, the sparrow search algorithm (SSA) is introduced to further enhance the robustness and stability of KELM model. Ultimately, the predictions of each optimized KELM are fused to achieve the final prognostic results. Through the experimental results of three patients, the following contributions can be summarized: (a) FEEMD exploits the box-counting dimension to remove abnormal signals in the original sequence, which guarantees the completeness of decomposition and obtains better decomposition results; (b) SSA is exploited to optimize the KELM, which can significantly boost the prediction effects; (c) When compared with the other seven benchmark models, the proposed framework in this paper is more suitable for predicting blood glucose and has higher prediction accuracy; (d) This paper also verifies that the proposed architecture can effectively reduce the false negative rate and increase the overall alarming accuracy in early warning of hypoglycemia.

Ankle Brachial Index (ABI) Score in Patient with Type 2 Diabetes Mellitus

Introduction: Unstable blood glucose levels in patient with Type 2 Diabetes Mellitus (DM) can cause various complications, one of which is peripheral neuropathy. Peripheral neuropathy is caused by atherosclerosis. The incidence of atherosclerosis can be seen by assessing the Ankle Brachial Index (ABI). This study aims to describe the ABI score in type 2 DM patients.&#x0D; Methods: The design of this study is a descriptive observational located at the Wirasatya Army Hospital, Singaraja in April 2022. The subjects were 81 patients with type 2 DM. The sampling technique used is purposive sampling. Measurement of the ABI score is carried out using an Oscillometric Sphygmomanometer. Descriptive analysis is used in this study and presented by frequency distribution.&#x0D; Results: This study found that 33.3% of subjects aged 44-55 years, 63.0% of subjects of male, 77.8% of subjects suffering from type 2 DM between 1 to 5 years, 32.1% working as entrepreneurs, and 78.2% having ABI scores between 1.0-1.4 so that they are included in the normal category.&#x0D; Conclusion: Patients with type 2 DM in the age group of 44-55 years, male, suffering from type 2 DM between 1 to 5 years, working as self-employed and more have normal ABI scores.

Cross-mapping medical records to NANDA-I to identify nursing diagnoses in a vulnerable population.

To assess the association between vulnerable populations and nursing care needs, using NANDA-I diagnostics, in the population of the Canary Islands, Spain. Nursing social epidemiology study. Cross Mapping of Medical Records to NANDA-I to Identify Nursing Diagnoses in a Population usinga medical, epidemiological follow-up study of a cohort of 7,190 people. The level of vulnerability of the participants was assigned, among those who were also assigned nursing diagnoses, using the "ICE index" to calculate the expected associations. The most prevalent nursing diagnosis in our sample was Sedentary lifestyle (60.5%), followed by Ineffective health self-management (33.8%) and Risk-prone health behaviour (28.7%). Significant differences were found by sex, age group and social class, with the nursing diagnoses included in the study being more prevalent among the most socio-economically disadvantaged social class. The cross-mapping method is useful to generate diagnostic information in terms of care needs, using the NANDA-I classification. The expected associations between high social vulnerability and care needs have been verified in a comprehensive and representative sample of the Canarian population (Spain). From an epidemiological perspective, identifying nursing diagnoses at the population level allows us to find the most prevalent needs in the different community groups and to focus appropriate nursing interventions for their implementation and impact assessment.

Analysis of Nursing Management Unstable Blood Glucose Levels in Type 2 Diabetes Mellitus Patients

Background: Diabetes Mellitus (DM) is a clinical syndrome of impaired metabolic secretion, insulin action, or both characterized by hyperglycemia. Various nursing problems can occur due to hyperglycemic conditions that are not handled properly. The instability of blood glucose levels is a major problem that occurs in uncontrolled DM patients. This condition can lead to various complications and complications so comprehensive treatment management is needed.&#x0D; Objectives: This study aims to explore and analyze the nursing management of unstable blood glucose levels in type 2 DM patients who were hospitalized.&#x0D; Methods: This study is a qualitative study using an exploratory case study method in diabetes mellitus patients type 2 who were hospitalized. The data obtained were processed and analyzed based on theories that explain the occurrence of the problem of instability in blood glucose levels and the nursing management carried out in patients with type 2 diabetes mellitus.&#x0D; Results: The results of this study indicate that the main problem in patients with type 2 diabetes mellitus is the instability of blood glucose levels which is characterized by hyperglycemia. Nursing management carried out is monitoring blood glucose level laboratory results, management of hyperglycemia, medication management, nutrition/diet management, treatment, and care education programs can reduce blood glucose levels.&#x0D; Conclusion: The problem of blood glucose instability is a priority problem in type 2 diabetes mellitus and comprehensive nursing management will determine the success of controlling blood glucose levels so that they are normal and stable.

Nursing diagnoses of preterm infants in the neonatal intensive care unit: A cross sectional study

Background and aimNursing diagnoses help nurses in effective intervention to get the best results. This study aimed to identify common nursing diagnoses of some of domains of NANDA taxonomy in premature infants admitted to the neonatal intensive care unit. MethodIn this descriptive cross-sectional study, a researcher-made instrument was used. The instrument contained two sections on maternal and neonatal demographic information and a checklist, extracted from literature, on infant-related nursing diagnoses. After obtaining the necessary permits, 96 infants were evaluated during a six-month period at the neonatal intensive care unit of Taleghani Hospital, according to inclusion criteria, and using the convenience sampling method. Data on each infant was collected and categorized into six domains of NANDA nursing diagnosis taxonomy based on the relevant checklist. ResultsThe most common actual nursing diagnoses included interrupted breastfeeding (00105), ineffective breastfeeding (00104), impaired gas exchange (00030), ineffective airway clearance (00031). The most common risk for nursing diagnoses in the first assessment were risk for infection (00004), risk for injury (00035), risk for delayed development (00112). risk for electrolyte imbalance (00195), risk for unstable blood glucose level (00179), risk for hypothermia (00253), and risk for neonatal jaundice (00230). ConclusionSome of the common nursing diagnoses in some domains of NANDA taxonomy were determined for preterm infants and can help nurses to develop more specialized care plan for this age group.

Electronic nursing care plans through the use of NANDA, NOC, and NIC taxonomies in community setting: A descriptive study in northern Italy.

PurposeTo carry on a descriptive analysis of nursing standardized language through the use of a software within outpatient facilities in northern Italy, organized according to the Chronic Care Model (CCM) and called Community Health Centers (CHC).MethodsA descriptive design was adopted for the study. NANDA‐I, NOC, and NIC taxonomies have been used to analyze care plans pulled from the software. Both qualitative and quantitative data were analyzed.FindingsThe average of nursing diagnosis correctly identified with respect to the nursing assessment is 83.7% (SD 29.9%). Class 4 diagnoses from Domains 4 have been identified as the most prevalent (22.4%), followed by risk for unstable blood glucose level 00179 (16.4%) and risk for overweight 00234 (13%). The main nursing outcomes were vital signs 0802 (22.5%), blood glucose level 2300 (16%), and weight loss behavior 1627 (11%). The most prevalent nursing interventions are wound care 3660 (27%), medication administration: intramuscular 2313 (19%), and health education 5510 (14%). The analysis shows ability in identifying nursing diagnoses, but a larger variability with outcomes and interventions. The study highlights the nursing role within CHC and identifies the main areas of expertise in chronic disease management: prevention and health education.ConclusionsNurses’ role is fundamental for chronic disease management within CHC; NANDA‐I taxonomy helps to analyze care plans.Implications for nursing practice‐ A taxonomy such as NANDA‐I represents a valid opportunity to make more visible how much nursing skills affect the achievement of a higher level of health in chronic patients.‐ This study is useful in the further training of outpatient nurses who works in CHC.‐ The study represents the starting point for future research to deepen the development of a standardized nursing language in outpatient facilities.

2020 NICE guideline update: Good news for pregnant women with type 1 diabetes and past or current gestational diabetes.

In December 2020, the National Institute for Health and Care Excellence (NICE) reviewed the evidence and updated their recommendations on intermittently scanned (commonly known as Flash) and Continuous Glucose Monitoring (CGM) during pregnancy for women with type 1 diabetes (1). The NICE guidelines now recommend offering CGM to all pregnant women with type 1 diabetes to help them meet their pregnancy glucose targets and improve neonatal outcomes. Their evidence review, based on the CONCEPTT randomised trial (2) and a Swedish observational study (3) found that, compared to capillary glucose monitoring, CGM resulted in more women achieving their blood glucose targets, fewer caesarean sections and fewer neonatal intensive care admissions.

Incidence and Prediction of Unstable Blood Glucose Level among Critically Ill Patients: A Cohort Study.

To evaluate the incidence and the prediction of unstable blood glucose level among critically ill patients hospitalized in an intensive care unit. A cohort study was conducted with 62 adult patients hospitalized at an intensive care unit of a hospital located in Minas Gerais, Brazil, between March and July of 2017. Patient's demographic information, along with scores for Simplified Acute Physiology Score III, primary medical diagnosis, discharge status, diagnosis of diabetes and/or sepsis, length of stay, glycemic variability, type of nutrition, types of medications and treatments, and oxygen therapy were collected daily. A daily venous blood sample was collected to measure blood glucose levels during the patient's hospitalization period. Bivariate analysis was used to explore the association among the potential diagnostic indicators and the outcome of unstable blood glucose levels. Multivariate Cox regression was used to identify the potential predictors for the outcome. Of the total of 62 participants, 45.1% (n=28) had unstable blood glucose level. Among the 28 patients with unstable blood glucose levels, half of them (n=14, 50%) had hypoglycemia and the other half had hyperglycemia (n=14, 50%). Decreased number of days hospitalized and the use of intensive glucose control with regular insulin were associated with decreased odds of developing hyperglycemia. The presence of mechanical ventilation was associated with a higher risk for the development of hypoglycemia. This study provides knowledge and evidence of diagnostic indicators for unstable blood glucose levels that are not currently included in the NANDA-International terminology for the nursing diagnosis Risk for unstable blood glucose level (00179). This study identified important diagnostic indicators that nurses can observe during the assessment to identify patients that are at risk for developing unstable blood glucose level and provide the appropriate care.

Nursing Diagnosis Risk for Unstable Blood Glucose Level in Patients with Diabetes Mellitus.

To validate the nursing diagnosis risk for unstable blood glucose level in adult/elderly patients with type 1 and type 2 diabetes. Study Methodological was used in this article. The validation process was carried out using the model proposed by Hoskins (1989). The risk factors ineffective medication management and high carbohydrate and lipid food intake achieved a concordance index greater than 85%. This study contributed to the identification of new risk factors, at risk populations, and important associated conditions. It is believed that the findings reported in this paper can be used to improve clinical protocols for the prevention of unstable blood glucose, in addition to contributions to the advancement of nursing science.

Non Invasive Method of Diabetes Measurement using Teg Sensor via Foot Skin Temperature

Diabetes is a type of metabolic dieses identified by unstable blood glucose level due to the defect in body to generate or use of insulin. Diabetes is created due to the defect in metabolism of converting the glucose to energy in blood. Hyperglycaemia is a stage were glucose value in the body is greater than 140 mg/dl which leads to type 1 diabetes for the patient. Type 1 diabetes is caused due to lack of generation of insulin in human blood and type 2 diabetes is caused due to resistance to insulin action which leads to several other diseases like foot ulcer and sever wounds in human foot or other parts of the body. Early diagnosing of diabetes disease plays an important task in improving the standard of healthy living. Traditional methods of identifying diabetes does not provides effective results and the results are not more reliable. Temperature based diabetes diagnosing model is defined using TEG sensor to analyse the heat changes in human foot. Imbalanced glucose level affects the performance of nerves system which leads to slower response for temperature change in the foot surface. TEG sensor is used to measure the heat transfer in foot by applying cold water over foot. The rate of temperature changes in foot represents the level of diabetes caused in the patient body. The signals from TEG sensor was collected and processed using signal analysis algorithm using MATLAB software.