COVID-19 and Diabetes

2021 ◽  
Vol 6 (1) ◽  
Keyword(s):  
Intensive Care ◽  
Blood Sugar ◽  
Intensive Care Units ◽  
Defense Mechanism ◽  
Heart Association ◽  
Low Grade ◽  
Additional Risk ◽  
Risk Of Death ◽  
Constant State ◽  
Normal Defense

COVID-19 is a disease caused by a newly discovered coronavirus which is easily transmitted among humans. One of the reasons for the greater risk of diabetes is that insulin resistance promotes low-grade chronic inflammation, leaving the immune system weakened due to this constant state of alertness. Additional risk factors such as heart disease are often present in people infected with COVID-19 who have diabetes. It is important to point out that controlling blood sugar, before and during infection, can be helpful in fighting infection. Blood sugar control in people with diabetes is a procedure that can prevent certain infections and ensure a normal defense mechanism in response to infection. The COVID-19 pandemic has caused concern around the world, especially in people with certain diseases such as diabetes. Data available to the American Heart Association show that among COVID-19 patients treated in intensive care units, 32 percent have diabetes, and among those hospitalized who are not in intensive care units, 24 percent have diabetes. It is estimated that diabetics have a nearly five times higher risk of death from COVID-19.

scholarly journals Early Prediction of Seven-Day Mortality in Intensive Care Unit Using a Machine Learning Model: Results from the SPIN-UTI Project

2021 ◽  
Vol 10 (5) ◽  
pp. 992
Author(s):  
Martina Barchitta ◽  
Andrea Maugeri ◽  
Giuliana Favara ◽  
Paolo Marco Riela ◽  
Giovanni Gallo ◽  
...  
Keyword(s):  
Machine Learning ◽  
Intensive Care ◽  
Intensive Care Units ◽  
Learning Algorithm ◽  
Area Under The Curve ◽  
Support Vector ◽  
Icu Admission ◽  
Risk Of Death ◽  
Saps Ii ◽  
Svm Algorithm

Patients in intensive care units (ICUs) were at higher risk of worsen prognosis and mortality. Here, we aimed to evaluate the ability of the Simplified Acute Physiology Score (SAPS II) to predict the risk of 7-day mortality, and to test a machine learning algorithm which combines the SAPS II with additional patients’ characteristics at ICU admission. We used data from the “Italian Nosocomial Infections Surveillance in Intensive Care Units” network. Support Vector Machines (SVM) algorithm was used to classify 3782 patients according to sex, patient’s origin, type of ICU admission, non-surgical treatment for acute coronary disease, surgical intervention, SAPS II, presence of invasive devices, trauma, impaired immunity, antibiotic therapy and onset of HAI. The accuracy of SAPS II for predicting patients who died from those who did not was 69.3%, with an Area Under the Curve (AUC) of 0.678. Using the SVM algorithm, instead, we achieved an accuracy of 83.5% and AUC of 0.896. Notably, SAPS II was the variable that weighted more on the model and its removal resulted in an AUC of 0.653 and an accuracy of 68.4%. Overall, these findings suggest the present SVM model as a useful tool to early predict patients at higher risk of death at ICU admission.

Abstract 285: Resuscitation Practices of Cardiac Arrest in Children with Cardiac Disease in Cardiac Intensive Care Units Compared to Pediatric Intensive Care Units

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_4) ◽  
Author(s):  
Tanya Perry ◽  
Tia T Raymond ◽  
Joanna Fishbein ◽  
Michael G Gaies ◽  
Todd Sweberg ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Intensive Care ◽  
Intensive Care Units ◽  
Cardiac Disease ◽  
Univariate Analysis ◽  
Pediatric Intensive Care ◽  
Heart Association ◽  
Pediatric Intensive Care Units ◽  
Achievement Measures ◽  
Cardiac Intensive Care

Introduction: Hospitalized children with critical cardiac disease experience cardiac arrest more than any other disease type. Varying models are devoted to caring for this population, including pediatric intensive care units (PICU) and dedicated cardiac intensive care units (CICU). The process of CPR delivery has not been evaluated in CICUs in comparison to PICUs. Hypothesis: There will be no difference in cardiac arrest resuscitation practices between unit types. Methods: We analyzed patients <18 years from the American Heart Association Get with the Guidelines-Resuscitation database (GWTG-R) with an illness category of medical or surgical cardiac disease who received CPR in a CICU or PICU from 2014 to 2018. Events were assessed for compliance with GWTG-R achievement measures of time to first chest compressions ≤ 1 minute, time to IV/IO epinephrine ≤ 5 minutes, time to first shock ≤ 2 minutes for VF/pulseless VT first documented rhythm, and confirmation of endotracheal tube (ETT) placement in trachea. Results: CPR practices were evaluated on 866 patients, 687 CICU and 179 PICU (55% male and 65% neonatal). Surgical cardiac disease was present in 56%. Cardiac malformations were present in 81% (45% cyanotic 29% acyanotic). Pulseless arrest was the initial event in 41% with a shockable rhythm in 14%. Return of spontaneous circulation occurred in 86% and survival to hospital discharge in 58%. Univariate analysis comparing resuscitation practice is shown in Table 1. ECPR use was the only variable noted to be significantly different between units (CICU 22% vs PICU 6%, P<0.01). On multivariate analysis, there were no differences in GWTG-R achievement measures between ICU types for ETT placement confirmation, time to IV/IO epinephrine dose, time to first chest compression to first shock (P>0.05). Conclusion: Despite differences in infrastructure, process, and provider expertise, there were no differences in cardiac arrest resuscitation practice between CICUs and PICUs.

Ketogenic Diet in Status Epilepticus

2016 ◽  
Author(s):  
Rima Nabbout
Keyword(s):  
Intensive Care ◽  
Status Epilepticus ◽  
Intensive Care Units ◽  
Ketogenic Diet ◽  
Significant Risk ◽  
Refractory Status Epilepticus ◽  
Dietary Therapy ◽  
Risk Of Death ◽  
Refractory Status ◽  
Neurological Morbidity

Refractory status epilepticus (RSE) is associated with a significant risk of death or neurological morbidity. The ketogenic diet (KD) is a dietary therapy that succeeds in controlling seizures in otherwise RSE in children and adult patients. Inflammatory etiologies might be a particular target, but KD has reported efficacy in other etiologies. KD is well tolerated, and the effect is seen within days. Randomized and controlled studies are lacking in this area, and studies are needed to prove the efficacy of KD in RSE and to identify specific indications. This would help to increase its use and to implement it in intensive care units to resolve severe epileptic conditions quickly.

scholarly journals Construction of an instrument for the prognostic evaluation of elderly persons in intensive care units

2017 ◽  
Vol 20 (3) ◽  
pp. 319-329
Author(s):  
Ivanilda Lacerda Pedrosa ◽  
Djacyr Magna Cabral Freire ◽  
Rodolfo Herberto Schneider
Keyword(s):  
Intensive Care ◽  
High Risk ◽  
Data Collection ◽  
Elderly Patients ◽  
Intensive Care Units ◽  
Total Sample ◽  
Cutoff Score ◽  
Elderly Persons ◽  
Prognostic Evaluation ◽  
Risk Of Death

Abstract Objective: To create an instrument for the prognostic evaluation of elderly patients hospitalized in an intensive care unit. Methods: A cohort study, with prospective data collection, which included elderly persons aged 60 years or older, was carried out in the city of João Pessoa, in the state of Paraíba, Brazil. Data collection was performed using an instrument created from a pilot study and the Katz Index. Poisson’s regression was used for data analysis. This technique estimates relative risk, retaining variables with p≤0.10 in the instrument, and ensures biological plausibility. The classification of risk of death was performed using quartile analysis, confirmed by the Receiver Operator Characteristic (ROC) curve. Results: 205 elderly patients with an average age of 74.6 years and a 59% risk of mortality, were included. Of the total sample and based on the scores, 16.6% of elderly persons had a low risk of developing death, 23.9% were at moderate risk, 40% had a high risk, and 19.5% exhibited a very high risk of death. The positive predictive value of the instrument was 77% and the negative value was 67.5%, with a concordance index of 0.78. The cutoff score of the instrument was 9 points or over. The sensitivity was 77.7% and the specificity was 66.7%. Conclusions: The instrument developed may be useful in the identification of elderly people with risk factors who require increased care. The instrument described can therefore be applied in Brazilian intensive care units.

scholarly journals Ophthalmology and SARS-CoV-2: Blind toward those who fight blindness?

2020 ◽  
Vol 30 (5) ◽  
pp. 1185-1187 ◽  
Author(s):  
Alessandro Arrigo ◽  
Emanuela Aragona ◽  
Maurizio Battaglia Parodi ◽  
Francesco Loperfido ◽  
Francesco Bandello
Keyword(s):  
Intensive Care ◽  
High Risk ◽  
Intensive Care Units ◽  
Safety Assessment ◽  
Clinical Settings ◽  
Limited Time ◽  
Clinical Practices ◽  
Risk Of Death ◽  
Worldwide Population ◽  
The World

SARS-CoV-2 infection recently reached pandemic proportions, with high risk of death for the worldwide population. In this dramatic scenario, all the resources are addressed to the intensive care units for the assessment of the emergency. However, more attention should be paid with respect to the risk of viral diffusion among asymptomatic people. Italy is the second most involved country in the world, and we needed to gain a lot of experience in a very limited time. At least 1 m of distance among people is recommended; however, some clinical practices cannot allow this distance. In this context, we believe that the careful safety assessment of clinical settings, like ophthalmologic ones, may have a remarkable impact on the fight against SARS-CoV-2 spread.

scholarly journals Determinants of Fatal Outcome in Patients Admitted to Intensive Care Units With Influenza, European Union 2009–2017

2019 ◽  
Vol 6 (11) ◽  
Author(s):  
Cornelia Adlhoch ◽  
Joana Gomes Dias ◽  
Isabelle Bonmarin ◽  
Bruno Hubert ◽  
Amparo Larrauri ◽  
...  
Keyword(s):  
Public Health ◽  
European Union ◽  
Intensive Care ◽  
Intensive Care Units ◽  
Influenza A ◽  
Medical Condition ◽  
Fatal Outcome ◽  
Health Concern ◽  
Medical Conditions ◽  
Risk Of Death

Abstract Background Morbidity, severity, and mortality associated with annual influenza epidemics are of public health concern. We analyzed surveillance data on hospitalized laboratory-confirmed influenza cases admitted to intensive care units to identify common determinants for fatal outcome and inform and target public health prevention strategies, including risk communication. Methods We performed a descriptive analysis and used Poisson regression models with robust variance to estimate the association of age, sex, virus (sub)type, and underlying medical condition with fatal outcome using European Union data from 2009 to 2017. Results Of 13 368 cases included in the basic dataset, 2806 (21%) were fatal. Age ≥40 years and infection with influenza A virus were associated with fatal outcome. Of 5886 cases with known underlying medical conditions and virus A subtype included in a more detailed analysis, 1349 (23%) were fatal. Influenza virus A(H1N1)pdm09 or A(H3N2) infection, age ≥60 years, cancer, human immunodeficiency virus infection and/or other immune deficiency, and heart, kidney, and liver disease were associated with fatal outcome; the risk of death was lower for patients with chronic lung disease and for pregnant women. Conclusions This study re-emphasises the importance of preventing influenza in the elderly and tailoring strategies to risk groups with underlying medical conditions.

Long-term Survival in the Intensive Care Unit After Erythrocyte Blood Transfusion

2009 ◽  
Vol 18 (2) ◽  
pp. 124-131 ◽  
Author(s):  
Milo Engoren ◽  
Cynthia Arslanian-Engoren
Keyword(s):  
Intensive Care ◽  
Blood Transfusion ◽  
Confidence Interval ◽  
Intensive Care Units ◽  
Case Control ◽  
Apache Ii ◽  
Term Survival ◽  
Long Term Survival ◽  
Risk Of Death

Background Erythrocyte blood transfusions are commonly used in intensive care units, yet little is known about their effects on long-term survival. Objective To determine the effect of erythrocyte blood transfusion in intensive care units on long-term survival. Methods Retrospective analysis of a prospectively collected database of 2213 patients admitted January 27, 2001, to April 30, 2002, to the cardiac, burn, neurological-neurosurgical, and combined medical-surgical intensive care units in a tertiary care, university-affiliated, urban medical center. Further analysis was done on a case-control subgroup (n = 556) formed by matching scores on the Acute Physiology and Chronic Health Evaluation (APACHE) II and propensity scores. Results Although transfusion was univariably associated with increased risk of death at all 3 times (0–30, 31–180, and &gt;180 days after admission to the unit), multivariable adjustment with Cox modeling showed that transfusion had no association with mortality for the first 2 intervals (0–30 and 31–180 days), but was associated with a 25% lower risk of death (hazard ratio, 0.75; 95% confidence interval, 0.57–0.99; P = .04) in patients who survived at least 180 days after admission to the unit. In the case-control patients, after correction for APACHE II risk of death and propensity to receive a transfusion, transfusion had no association with mortality for the first 2 intervals, but was associated with 29% lowered risk of death (hazard ratio, 0.71; 95% confidence interval, 0.50–0.99; P=.046). Conclusion Blood transfusion was associated with a decreased risk of late (&gt;180 days) death in intensive care patients.

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