Clinical and epidemiological study of stress hyperglycemia among medical intensive care unit patients in Central India

Hyperglycemic Patterns in Acute Stroke Patients

Background and objective Hyperglycemia following a stroke can independently aggravate the ischemic area. Ensuring adequate glucose management can help avoid complications and minimize mortality and disability in these patients. This study aimed to investigate hyperglycemic patterns in acute stroke patients. Materials and methods We conducted a non-interventional prospective observational study involving acute stroke patients by employing continuous glucose monitoring (CGM) for 72 hours after the onset of stroke symptoms. Admission glucose, patients' total mean glucose (TMG), and time in range (TIR) (70-140 mg/dl) were correlated with the hyperglycemic patterns elicited by the CGM system software. Data were analyzed using SPSS Statistics 26.0 (IBM Corp., Armonk, NY) with descriptive statistics, the Kruskal-Wallis test, and χ2 test. Results Our cohort comprised 105 diabetic and non-diabetic stroke patients. The hyperglycaemic patterns that we observed were as follows: (i) hyperglycemia from 23:00 to 10:00, (ii) 06.00 to 10.00, (iii) at night and after meals, iv) no pattern, v) unspecified patterns. Patients with nocturnal and morning hyperglycemia had admission glucose of 183 mg/dl, mean 72-hour glucose of 156 mg/dl, and TIR of 37%. Patients who did not develop a hyperglycemic pattern either had admission glucose of 131 mg/dl and TIR of 89% or had high admission glucose (197 mg/dl) and a short TIR (14%). Conventional pre-meal capillary glucose tests do not appear to detect these patients' hyperglycemic tendencies. Conclusions These results may indicate the necessity for more intensive measurements during the night or dawn in this patient population. Admission glucose could be considered a predictor of hyperglycemic patterns and contribute to the patient's care plan.

Glucose Fluctuations in Acute Ischemic Stroke

INTRODUCTION

The Oxfordshire Community Stroke Project denotes four subtypes of ischemic stroke (total and partial anterior infarct, posterior, and lacunar). Hyperglycemia has been associated with a larger infarct size and poor prognosis.

AIM

The purpose of the study was to investigate the correlation of glucose fluctuations with the Oxford sub-categories and patient outcomes using a blinded continuous glucose monitoring system.

METHODS

This is a non-interventional prospective observational study. Stroke patients with symptoms onset in the last 24h, participated in the study. A glucose sensor was placed for 72 hours. Disability was assessed using the modified Rankin Scale. Stroke subtypes were compared with total mean glucose and time in range using ANOVA analysis. Multiple ordinal logistic regression was employed to analyze outcomes and survival.

RESULTS

The sample consisted of 105 diabetic and non-diabetic patients. The overall mean glucose was 127.06 mg/dL and the time in range (70-140 mg/dL) was 70.98%. There was no significant difference between the stroke sub-categories and the total mean glucose. For every one-point increase in the time in range, we expect a 1.5% reduction in the odds of having a worse outcome. Patients with total anterior infarct are 2.31 times more likely to have a worse outcome than lacunar patients.

CONCLUSION

The utilization of the Oxford classification may not be necessary for managing acute ischemic stroke glucose levels. Achieving glucose regulation and an increase in time in range can be attained through meticulous control, potentially extending life expectancy. Continuous glucose monitors may aid in achieving this objective.

Effect of different acupuncture sequences of Huiyangjiuzhen acupoints on blood glucose and hemorheology in the anesthetized rabbits

Background and objective

Hemorheology and blood glucose are commonly used to estimate the risks of thrombosis and stress hyperglycemia after anaesthesia. The sequence of acupoint stimulation might influence the therapeutic effects of acupuncture. In the current study, we aimed at investigating the effect of different acupuncture sequences of "Huiyangjiuzhen" acupoints on the blood glucose and hemorheology in anesthetized rabbits.

Methods

Twenty-five rabbits were randomly divided into five groups, including the control group (CG), the positive-sequence group (PSG), the reverse-sequence group (RSG), the disorder-sequence group (DSG), and the random group (RG). Except for the CG and RG, the rabbits in other groups were acupunctured with different sequences of "Huiyangjiuzhen"acupoints when the rabbits were anesthetized. The acupoints in rabbits of the RG were chosen randomly. The levels of blood glucose and hemorheology indexes before and after anaesthesia was detected.

Results

In the PSG, Hηb 200/s, Mηb 30/s, Hηr 200/s, ERI, hematocrit and plasma viscosity levels were decreased, and the blood glucose level was not changed. In the DSG, the levels of Mηb 30/s and hematocrit were decreased, and the blood glucose was increased. In the CG, RSG and RG, no hemorheology indexes were changed and the blood glucose was increased.

Conclusion

"Huiyangjiuzhen" acupuncture could decrease the risks of post-operative thrombosis and stress hyperglycemia in anesthetized rabbits. This effectiveness depends on both acupuncture and acupuncture sequence at the "Huiyangjiuzhen" acupoints.

Glucometrics in the first week of critical illness and its association with mortality

OBJECTIVE

Evaluation of glucometrics in the first week of ICU stay and its association with outcomes.

DESIGN

Prospective observational study.

SETTING

Mixed ICU of teaching hospital.

PATIENTS

Adults initiated on insulin infusion for 2 consecutive blood glucose (BG) readings ≥180mg/dL.

MAIN VARIABLES OF INTEREST

Glucometrics calculated from the BG of first week of admission: hyperglycemia (BG>180mg/dL) and hypoglycemia (BG<70mg/dL) episodes; median, standard deviation (SD) and coefficient of variation (CV) of BG, glycemic lability index (GLI), time in target BG range (TIR). Factors influencing glucometrics and the association of glucometrics to patient outcomes analyzed.

RESULTS

A total of 5762 BG measurements in 100 patients of median age 55 years included. Glucometrics: hyperglycemia: 2253 (39%), hypoglycemia: 28 (0.48%), median BG: 169mg/dL (162-178.75), SD 31mg/dL (26-38.75), CV 18.6% (17.1-22.5), GLI: 718.5 [(mg/dL)²/h]/week (540.5-1131.5) and TIR 57% (50-67). Diabetes and higher APACHE II score were associated with higher SD and CV, and lower TIR. On multivariate regression, diabetes (p=0.009) and APACHE II score (p=0.016) were independently associated with higher SD. Higher SD and CV were associated with less vasopressor-free days; lower TIR with more blood-stream infections (BSI). Patients with higher SD, CV and GLI had a higher 28-day mortality. On multivariate analysis, GLI alone was associated with a higher mortality (OR 2.99, p=0.04).

CONCLUSIONS

Glycemic lability in the first week in ICU patients receiving insulin infusion is associated with higher mortality. Lower TIR is associated with more blood stream infections.

Association between Glycemic Gap and Adverse Outcomes in Critically Ill Patients with Diabetes

OBJECTIVES

Glycemic excursions are commonly seen in patients admitted to the Intensive Care Unit (ICU) and are related to adverse outcomes. Glycemic gap is a marker of this excursion in patients with diabetes. It can be used to predict adverse outcomes in patients with diabetes admitted to the ICU. It is calculated by subtracting A1C-derived average glucose (ADAG) = ([28.7 × HbA1c]-46.7) from plasma glucose at admission. Objective of this study was to correlate glycemic gap and adverse outcomes in patients with type 2 diabetes mellitus (DM) admitted to the ICU.

MATERIALS AND METHODS

We conducted an ambispective study to include patients with type 2 DM admitted to the ICUs from July 2015 to June 2016. The following adverse outcomes were recorded: Multiorgan dysfunction syndrome (MODS), acute respiratory distress syndrome (ARDS), shock, upper gastrointestinal (UGI) bleed, acute kidney injury (AKI), and acute respiratory failure (ARF).

RESULTS

A total of 200 patients were enrolled, with a mean age ± standard deviation of 62 ± 11.24 years, and 64.5% were males. The median (interquartile range) duration of hospital stay and ICU stay were 8 (6-12) days and 4 (3-7) days, respectively. The most common primary diagnosis was cardiovascular (39.5%) followed by neurological (16.5%), infection at diagnosis (16.5%), respiratory (14%), gastrointestinal (7.5%), and others (6%). A higher glycemic gap was associated with occurrence of MODS (P < 0.01), ARDS (P = 0.026), shock (P = 0.043), UGI bleed (P = 0.013), AKI (P = 0.01), and ARF (P < 0.01). Glycemic gap cutoffs of 43.31, 45.26, and 39.12 were found to be discriminatory for predicting ICU mortality (area under the receiver operating characteristic [AUROC]=0.631, P = 0.05), MODS (AUROC = 0.725, P < 0.001), and ARF (AUROC = 0.714, P < 0.001).

CONCLUSION

This study showed that higher glycemic gap levels were associated with an increased risk of MODS, ARDS, shock, UGI bleed, AKI, and ARF. Glycemic gap is a tool that can be used to determine prognosis in patients with diabetes admitted to the ICU.