Critical Care Research and Practice最新文献

{"title":"Effect of Exogenous Melatonin Administration in Critically Ill Patients on Delirium and Sleep: A Randomized Controlled Trial.","authors":"Judith Bellapart,&nbsp;Vinesh Appadurai,&nbsp;Melissa Lassig-Smith,&nbsp;Janine Stuart,&nbsp;Christopher Zappala,&nbsp;Rob Boots","doi":"10.1155/2020/3951828","DOIUrl":"https://doi.org/10.1155/2020/3951828","url":null,"abstract":"<p><strong>Introduction: </strong>Sleep deprivation is a contributor for delirium in intensive care. Melatonin has been proposed as a pharmacological strategy to improve sleep, but studies have shown that the increase in plasma levels of melatonin do not correlate to a beneficial clinical effect; in addition, melatonin's short half-life may be a major limitation to achieving therapeutic levels. This study applies a previously published novel regimen of melatonin with proven sustained levels of melatonin during a 12 h period. In this study, the aim is to determine if such melatonin dosing positively influences on the sleep architecture and the incidence of delirium in intensive care.</p><p><strong>Methods: </strong>Single center, randomized control trial with consecutive recruitment over 5 years. Medical and surgical patients were in a recovery phase, all weaning from mechanical ventilation. Randomized allocation to placebo or enteral melatonin, using a previously described regimen (loading dose of 3 mg at 21 h, followed by 0.5 mg hourly maintenance dose until 03am through a nasogastric tube). Sleep recordings were performed using polysomnogram at baseline (prior to intervention) and the third night on melatonin (postintervention recording). Delirium was assessed using the Richmond Agitation and the Confusion Assessment Method Scales. Environmental light and noise levels were recorded using a luxmeter and sound meter.</p><p><strong>Results: </strong>80 patients were screened, but 33 were recruited. Sleep studies showed no statistical differences on arousal index or length of sleep. Baseline delirium scores showed no difference between groups when compared to postintervention scores. RASS scores were 1 in both groups at baseline, compared to zero (drug group) and 0.5 (placebo group) posttreatment. CAM scores were zero (drug group) and 1 (placebo group) at baseline, compared to zero (in both groups) postintervention.</p><p><strong>Conclusion: </strong>High levels of plasma melatonin during the overnight period of intensive care cohort patients did not improve sleep nor decreased the prevalence of delirium. This trial is registered with Anzctr.org.au/ACTRN12620000661976.aspx.</p>","PeriodicalId":46583,"journal":{"name":"Critical Care Research and Practice","volume":"2020 ","pages":"3951828"},"PeriodicalIF":1.7,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2020/3951828","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38465449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Subclinical Left Ventricular Systolic Dysfunction in Patients with Septic Shock Based on Sepsis-3 Definition: A Speckle-Tracking Echocardiography Study.","authors":"Pham Dang Hai,&nbsp;Le Lan Phuong,&nbsp;Nguyen Manh Dung,&nbsp;Le Thi Viet Hoa,&nbsp;Do Van Quyen,&nbsp;Nguyen Xuan Chinh,&nbsp;Vu Duy Minh,&nbsp;Pham Nguyen Son","doi":"10.1155/2020/6098654","DOIUrl":"https://doi.org/10.1155/2020/6098654","url":null,"abstract":"<p><strong>Introduction: </strong>Left ventricular dysfunction is quite common in septic shock. Speckle-tracking echocardiography (STE) is a novel, highly sensitive method for assessing left ventricular function, capable of detecting subclinical myocardial dysfunction, which is not identified with conventional echocardiography. We sought to evaluate subclinical left ventricular systolic function in patients with septic shock using speckle-tracking echocardiography.</p><p><strong>Methods: </strong>From May 2017 to December 2018, patients aged ≥18 years admitted to the intensive care unit with the diagnosis of sepsis and septic shock based on the sepsis-3 definition were included. Patients with other causes of cardiac dysfunction were excluded. Transthoracic echocardiography was performed for all the patients within 24 hours of diagnosis. Left ventricular systolic function was assessed using conventional echocardiography and speckle-tracking echocardiography.</p><p><strong>Results: </strong>Patients with septic shock (<i>n</i> = 90) (study group) and 37 matched patients with sepsis but no septic shock (control group) were included. Left ventricular ejection fraction (LVEF) by conventional echocardiography showed no significant difference between two groups (58.2 ± 9.9 vs. 58.6 ± 8.3, <i>p</i>=0.804). The global longitudinal strain (GLS) by STE was significantly reduced in patients with septic shock compared with that in the control (-14.6 ± 3.3 vs. -17.1 ± 3.3, <i>p</i> < 0.001). Based on the cutoff value of GLS ≥ -15% for the definition of subclinical left ventricular systolic dysfunction, this dysfunction was detected in 50 patients with septic shock (55.6%) and in 6 patients in the control group (16.2%) (<i>p</i> < 0.05).</p><p><strong>Conclusions: </strong>Speckle-tracking echocardiography can detect early subclinical left ventricular systolic dysfunction via the left ventricular global longitudinal strain compared with conventional echocardiographic parameters in patients with septic shock.</p>","PeriodicalId":46583,"journal":{"name":"Critical Care Research and Practice","volume":"2020 ","pages":"6098654"},"PeriodicalIF":1.7,"publicationDate":"2020-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2020/6098654","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38453473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bioreactance-Based Noninvasive Fluid Responsiveness and Cardiac Output Monitoring: A Pilot Study in Patients with Aneurysmal Subarachnoid Hemorrhage and Literature Review.","authors":"Sanjeev Sivakumar,&nbsp;Christos Lazaridis","doi":"10.1155/2020/2748181","DOIUrl":"https://doi.org/10.1155/2020/2748181","url":null,"abstract":"<p><p>Management of volume status, arterial blood pressure, and cardiac output are core elements in approaching the patients with aneurysmal subarachnoid hemorrhage (SAH). For the prevention and treatment of delayed cerebral ischemia (DCI), euvolemia is advocated and caution is made towards the avoidance of hypervolemia. Induced hypertension and cardiac output augmentation are the mainstays of medical management during active DCI, whereas the older triple-H paradigm has fallen out of favor due to lack of demonstrable physiological or clinical benefits and serious concern for adverse effects such as pulmonary edema and multiorgan system dysfunction. Furthermore, insight into clinical hemodynamics of patients with SAH becomes salient when one considers the frequently associated cardiac and pulmonary manifestations of the disease such as SAH-associated cardiomyopathy and neurogenic pulmonary edema. In terms of fluid and volume targets, less attention has been paid to dynamic markers of fluid responsiveness despite the well-established, in the general critical care literature, superiority of these as compared to traditionally used static markers such as central venous pressure (CVP). Based on this literature and sound pathophysiologic reasoning, reliance on static markers (such as CVP) is unjustified when one attempts to assess strategies augmenting stroke volume (SV), arterial blood pressure, and oxygen delivery. There are several options for continuous bedside cardiorespiratory monitoring and optimization of SAH patients. We, here, review a noninvasive monitoring technique based on thoracic bioreactance and focusing on continuous cardiac output and fluid responsiveness markers.</p>","PeriodicalId":46583,"journal":{"name":"Critical Care Research and Practice","volume":"2020 ","pages":"2748181"},"PeriodicalIF":1.7,"publicationDate":"2020-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2020/2748181","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38453471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Validity of SOFA Score to Predict Mortality in Adult Patients with Cardiogenic Shock on Venoarterial Extracorporeal Membrane Oxygenation.","authors":"Mohamed Laimoud,&nbsp;Mosleh Alanazi","doi":"10.1155/2020/3129864","DOIUrl":"https://doi.org/10.1155/2020/3129864","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Venoarterial ECMO is increasingly used in resuscitation of adult patients with cardiogenic shock with variable mortality reports worldwide. Our objectives were to study the variables associated with hospital mortality in adult patients supported with VA-ECMO and to determine the validity of repeated assessments of those patients by the Sequential Organ Failure Assessment (SOFA) score for prediction of hospital mortality. We retrospectively studied adult patients admitted to the cardiac surgical critical care unit with cardiogenic shock supported with VA-ECMO from January 2015 to August 2019 in our tertiary care hospital.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;One hundred and six patients supported with VA-ECMO were included in our study with in-hospital mortality of 56.6%. The mean age of studied patients was 40.2 ± 14.4 years, and the patients were mostly males (69.8%) with a mean BMI of 26.5 ± 7 without statistically significant differences between survivors and nonsurvivors. Presence of CKD, chronic atrial fibrillation, and cardiac surgeries was significantly more frequent in the nonsurvivors group. The nonsurvivors had more frequent AKI (&lt;i&gt;p&lt;/i&gt; &lt; 0.001), more haemodialysis use (&lt;i&gt;p&lt;/i&gt; &lt; 0.001), more gastrointestinal bleeding (&lt;i&gt;p&lt;/i&gt; = 0.039), more ICH (&lt;i&gt;p&lt;/i&gt; = 0.006), and fewer ICU days (&lt;i&gt;p&lt;/i&gt; = 0.002) compared to the survivors group. The mean peak blood lactate level was 11 ± 3 vs 16.7 ± 3.3, &lt;i&gt;p&lt;/i&gt; &lt; 0.001, and the mean lactate level after 24 hours of ECMO initiation was 2.2 ± 0.9 vs 7.9 ± 5.7, &lt;i&gt;p&lt;/i&gt; &lt; 0.001, in the survivors and nonsurvivors, respectively. Initial SOFA score ≥13 measured upon ICU admission had a 85% sensitivity and 73.9% specificity for predicting hospital mortality [AUROC = 0.862, 95% CI: 0.791-0.932; &lt;i&gt;p&lt;/i&gt; &lt; 0.001] with 81% PPV, 79.1% NPV, and 80.2% accuracy while SOFA score ≥13 at day 3 had 100% sensitivity and 91.3% specificity for predicting mortality with 93.8% PPV, 100% NPV, and 96.2% accuracy [AUROC = 0.995, 95% CI: 0.986-1; &lt;i&gt;p&lt;/i&gt; &lt; 0.001]. The ∆1 SOFA (3-1) ≥2 had 95% sensitivity and 93.5% specificity for predicting hospital mortality [AUROC = 0.958, 95% CI: 0.913-1; &lt;i&gt;p&lt;/i&gt; &lt; 0.001] with 95% PPV, 93.5% NPV, and 94.3% accuracy. SOFA score ≥15 at day 5 had 98% sensitivity and 100% specificity for predicting mortality with 99% accuracy [AUROC = 0.994, 95% CI: 0.982-1; &lt;i&gt;p&lt;/i&gt; &lt; 0.001]. The ∆2 SOFA (5-1) ≥2 had 90% sensitivity and 97.8% specificity for predicting hospital mortality [AUROC = 0.958, 95% CI: 0.909-1; &lt;i&gt;p&lt;/i&gt; &lt; 0.001] with 97.8% PPV, 90% NPV, and 94.8% accuracy. Multivariable regression analysis revealed that increasing ∆1 SOFA score (OR = 2.506, 95% CI: 1.681-3.735, &lt;i&gt;p&lt;/i&gt; &lt; 0.001) and increasing blood lactate level (OR = 1.388, 95% CI: 1.015-1.898, &lt;i&gt;p&lt;/i&gt; = 0.04) were significantly associated with hospital mortality after VA-ECMO support for adults with cardiogenic shock.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;The use of VA-ECMO in adult patients with ","PeriodicalId":46583,"journal":{"name":"Critical Care Research and Practice","volume":"2020 ","pages":"3129864"},"PeriodicalIF":1.7,"publicationDate":"2020-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2020/3129864","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38409452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Maximal Glycemic Difference, the Possible Strongest Glycemic Variability Parameter to Predict Mortality in ICU Patients.","authors":"Thanaphruet Issarawattana,&nbsp;Rungsun Bhurayanontachai","doi":"10.1155/2020/5071509","DOIUrl":"https://doi.org/10.1155/2020/5071509","url":null,"abstract":"<p><strong>Background: </strong>This retrospective study aimed to determine the correlation of blood glucose and glycemic variability with mortality and to identify the strongest glycemic variability parameter for predicting mortality in critically ill patients.</p><p><strong>Methods: </strong>A total of 528 patients admitted to the medical intensive care unit were included in this study. Blood glucose levels during the first 24 hours of admission were recorded and calculated to determine the glycemic variability. Significant glycemic variability parameters, including the standard deviation, coefficient of variation, maximal blood glucose difference, and J-index, were subsequently compared between intensive care unit survivors and nonsurvivors. A binary logistic regression was performed to identify independent factors associated with mortality. To determine the strongest glycemic variability parameter to predict mortality, the area under the receiver operating characteristic of each glycemic variability parameter was determined, and a pairwise comparison was performed.</p><p><strong>Results: </strong>Among the 528 patients, 17.8% (96/528) were nonsurvivors. Both survivor and nonsurvivor groups were clinically comparable. However, nonsurvivors had significantly higher median APACHE-II scores (23 [21, 27] vs. 18 [14, 22]; <i>p</i> < 0.01) and a higher mechanical ventilator support rate (97.4% vs. 74.9%; <i>p</i> < 0.01). The mean blood glucose level and significant glycemic variability parameters were higher in nonsurvivors than in survivors. The maximal blood glucose difference yielded a similar power to the coefficient of variation (<i>p</i> = 0.21) but was significantly stronger than the standard deviation (<i>p</i> = 0.005) and J-index (<i>p</i> = 0.006).</p><p><strong>Conclusions: </strong>Glycemic variability was independently associated with intensive care unit mortality. Higher glycemic variability was identified in the nonsurvivor group regardless of preexisting diabetes mellitus. The maximal blood glucose difference and coefficient of variation of the blood glucose were the two strongest parameters for predicting intensive care unit mortality in this study.</p>","PeriodicalId":46583,"journal":{"name":"Critical Care Research and Practice","volume":"2020 ","pages":"5071509"},"PeriodicalIF":1.7,"publicationDate":"2020-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2020/5071509","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38363742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Development of Critical Care Medicine in China: From SARS to COVID-19 Pandemic.","authors":"Haiyan Yin, Shan Wang, Youfeng Zhu, Rui Zhang, Xiaoling Ye, Jianrui Wei, Peter C Hou","doi":"10.1155/2020/3956732","DOIUrl":"10.1155/2020/3956732","url":null,"abstract":"<p><strong>Background: </strong>Critical care medicine is a branch of medical science that deals with the characteristics and regularity of life-threatening processes initiated by any injury or disease and, accordingly, relevant treatment for patients with critical illness. Conceptions of critical care medicine in China stemmed in the early 1970s. Ever since the establishment of the first intensive care unit (ICU) along with the increasingly incomparable role of ICU in medical practices, critical care medicine has become an indispensable part of the Chinese medical and health system. Currently, critical care medicine as a secondary clinical discipline and a well-constructed science is in sustainable development on the way towards systematization and standardization.</p><p><strong>Methods: </strong>The gross domestic product (GDP) and population data were obtained from the National Bureau of Statistics. The number of ICUs, ICU beds, and hospital beds and other data regarding ICU staffing and facility resources were obtained from the Yearbook of Health in the People's Republic of China and National Bureau of Statistics. The mortality rates of SARS and COVID-19 and the number of health workers aiding Hubei amid COVID-19 pandemic were obtained from the National Health Commission. <i>Findings</i>. Critical care medicine in mainland China has made significant strides: both quantity and quality are progressing at a fast pace after SARS in 2003. Although there exist some disparities in healthcare personnel and medical resources, they have not hindered the country from mobilizing its healthcare workers and resources against a public health emergency.</p>","PeriodicalId":46583,"journal":{"name":"Critical Care Research and Practice","volume":"2020 ","pages":"3956732"},"PeriodicalIF":1.7,"publicationDate":"2020-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7421094/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38408811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Knowledge, Attitude, and Associated Factors towards Physical Assessment among Nurses Working in Intensive Care Units: A Multicenter Cross-Sectional Study.","authors":"Bikis Liyew, Ambaye Dejen Tilahun, Tilahun Kassew","doi":"10.1155/2020/9145105","DOIUrl":"10.1155/2020/9145105","url":null,"abstract":"<p><strong>Introduction: </strong>Nurses working in the intensive care unit play an essential role in detecting patients at risk of deterioration through ongoing assessment and action in response to changing health status.</p><p><strong>Objectives: </strong>To assess knowledge, attitude, and associated factors towards physical assessment on critically ill patients among nurses working in the intensive care unit at Amhara regional state referral hospitals, Northwest Ethiopia, 2019. The research hypothesis: there is poor physical assessment knowledge, poor physical assessment attitude, and there are factors that are likely to affect nurses' knowledge and attitude towards physical assessment providing this care to critically ill patients at Amhara regional state referral hospitals, Northwest Ethiopia, 2019.</p><p><strong>Methods: </strong>Institution-based cross-sectional study was conducted among 299 nurses from March to September 2019. A convenience sampling method was used. Data were entered by using Epi Info 7.2.2 and analyzed by using STATA 14. The result was computed by descriptive statistics and to explore predictors of knowledge, and attitude linear regression analysis models were fitted, and the adjusted unstandardized beta (<i>β</i>) coefficient at 95% CI was used. A <i>p</i>-value <0.05 was considered significant. Result and conclusion: the knowledge mean scores were 9.93 ± 2.99 [95% CI (9.59, 10.31)]. The proportion of nurse's knowledge who score above the mean was 167 (55.9%) [95% CI (50.2, 61.5)] and below the mean 132 (44.1%) [95% CI (38.5, 49.8)]. Attitude means scores were 36.85 ± 6.21 [(36.16, 37.51)]. The proportions of nurse's attitudes who score above the mean were 158 (52.8%) [95% CI (47.5, 58.5)] and below the mean 141 (47.2) [95% CI (41.5, 52.5)]. Regarding predictor variables, being male [<i>β</i> = 0.84, 95% CI (0.16, 1.52)] and taken training [<i>β</i> = 1.85, 95% CI (1.14, 2.56)] were factors positively associated with knowledge, whereas has taken training [<i>β</i> = 4.13, 95% CI (2.82, 5.44)], total years of experience [<i>β</i> = 0.59, 95% CI (0.25, 0.93)], and knowledge [<i>β</i> = 0.92, 95% CI (0.0.72, 1.12)] were factors positively associated with attitude towards physical assessment.</p><p><strong>Conclusion: </strong>Based on the result of this study, the knowledge and attitude towards physical assessment regarding critically ill patients among nurses working in intensive care units were good. Hence, training, educational support services, and awareness are recommended to encourage nurse's knowledge and attitude towards physical assessment.</p>","PeriodicalId":46583,"journal":{"name":"Critical Care Research and Practice","volume":"2020 ","pages":"9145105"},"PeriodicalIF":1.7,"publicationDate":"2020-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7436285/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38313254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intravenous Fluid of Choice in Major Abdominal Surgery: A Systematic Review.","authors":"Seechad Noonpradej,&nbsp;Osaree Akaraborworn","doi":"10.1155/2020/2170828","DOIUrl":"https://doi.org/10.1155/2020/2170828","url":null,"abstract":"<p><strong>Background: </strong>Intravenous fluid therapy plays a role in maintaining the hemodynamic status for tissue perfusion and electrolyte hemostasis during surgery. Recent trials in critically ill patients reported serious side effects of some types of fluids. Since the most suitable type of fluid is debatable, a consensus in perioperative patients has not been reached.</p><p><strong>Method: </strong>We performed a systematic review of randomized control trials (RCTs) that compared two or more types of fluids in major abdominal surgery. The outcomes were related to bleeding, hemodynamic status, length of hospital stay, and complications, such as kidney injury, electrolyte abnormality, major cardiac adverse event, nausea, vomiting, and mortality. A literature search was performed using Medline and EMBASE up to December 2019. The data were pooled to investigate the effect of fluid on macrocirculation and intravascular volume effect.</p><p><strong>Results: </strong>Forty-three RCTs were included. Eighteen fluids were compared: nine were crystalloids and nine were colloids. The results were categorized into macrocirculation and intravascular volume effect, microcirculation, anti-inflammatory parameters, vascular permeability, renal function (colloids), renal function and electrolytes (crystalloids), coagulation and bleeding, return of bowel function, and postoperative nausea vomiting (PONV). We found that no specific type of fluid led to mortality and every type of colloid was equivalent in volume expansion and did not cause kidney injury. However, hydroxyethyl starch and dextran may lead to increased bleeding. Normal saline can cause kidney injury which can lead to renal replacement therapy, and dextrose fluid can decrease PONV.</p><p><strong>Conclusion: </strong>In our opinion, it is safe to give a balanced crystalloid as the maintenance fluid and give a colloid, such as HES130/0.4, 4% gelatin, or human albumin, as a volume expander.</p>","PeriodicalId":46583,"journal":{"name":"Critical Care Research and Practice","volume":"2020 ","pages":"2170828"},"PeriodicalIF":1.7,"publicationDate":"2020-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2020/2170828","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38300561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mortality Predictors and Associated Factors in Patients in the Intensive Care Unit: A Cross-Sectional Study.","authors":"Fernanda G de M Soares Pinheiro,&nbsp;Eduesley Santana Santos,&nbsp;Íkaro Daniel de C Barreto,&nbsp;Carleara Weiss,&nbsp;Andreia C Vaez,&nbsp;Jussiely C Oliveira,&nbsp;Matheus S Melo,&nbsp;Francilene A Silva","doi":"10.1155/2020/1483827","DOIUrl":"10.1155/2020/1483827","url":null,"abstract":"<p><strong>Background: </strong>Mortality in the intensive care unit (ICU) has been associated to an array of risk factors. Identification of risk factors potentially contribute to predict and reduce mortality rates in the ICU. The objectives of the study were to determine the prevalence and the factors associated with the mortality and to analyze the survival.</p><p><strong>Method: </strong>A cross-sectional study conducted in two clinical and surgical ICU in the state of Sergipe, northeastern Brazil. We enrolled 316 patients with at least 48 h of hospitalization, minimum age of 18 years old, sedated or weaned, with RASS ≥ -3, between July 2017 and April 2018. We categorized data in (1) age and gender, (2) clinical condition, and (3) prevalence of delirium. Data from enrolled patients were collected from enrollment until death or ICU discharge. Patients' outcomes were categorized in (1) death and (2) nondeath (discharge).</p><p><strong>Results: </strong>Twenty-one percent of participants died. Age (53 ± 17 years <i>vs</i>. 45 ± 18 years, <i>p</i> < 0.01), electrolyte disturbance (30.3% <i>vs</i> 18.1%, <i>p</i>=0.029), glycemic index (33.3% <i>vs</i> 18.2%, <i>p</i>=0.008), tube feeding (83.3% vs 67.1%, <i>p</i>=0.01), mechanical ventilation (50% <i>vs</i> 35.7%, <i>p</i>=0.035), sedation with fentanyl (24.2 <i>vs</i> 13.6, <i>p</i>=0.035), use of insulin (33.8% <i>vs</i> 21.7%, <i>p</i>=0.042), and higher Charlson score (2.61 <i>vs</i> 2.17, <i>p</i>=0.041) were significantly associated with death on the adjusted model. However, the regression model indicated that patients admitted from the emergency (HR = 0.40, <i>p</i>=0.006) and glycemic index alterations (HR = 1.68, <i>p</i>=0.047) were associated with mortality. There was no statistically significant difference (<i>p</i>=0.540) in survival between patients with and without delirium, based on the survival analysis and length of hospitalization.</p><p><strong>Conclusion: </strong>The prevalence of death was 21%, and age, electrolyte disturbance, glycemic index, tube feeding, mechanical ventilation, sedation with fentanyl, use of insulin, and higher Charlson score were associated with mortality.</p>","PeriodicalId":46583,"journal":{"name":"Critical Care Research and Practice","volume":"2020 ","pages":"1483827"},"PeriodicalIF":1.7,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2020/1483827","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38269530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Incidence, Risk Factors, and Outcome of Acute Kidney Injury in the Intensive Care Unit: A Single-Center Study from Jordan.","authors":"Ashraf O Oweis,&nbsp;Sameeha A Alshelleh,&nbsp;Suleiman M Momany,&nbsp;Shaher M Samrah,&nbsp;Basheer Y Khassawneh,&nbsp;Musa A K Al Ali","doi":"10.1155/2020/8753764","DOIUrl":"https://doi.org/10.1155/2020/8753764","url":null,"abstract":"<p><strong>Background: </strong>Acute kidney injury (AKI) is a common serious problem affecting critically ill patients in intensive care unit (ICU). It increases their morbidity, mortality, length of ICU stay, and long-term risk of chronic kidney disease (CKD).</p><p><strong>Methods: </strong>A retrospective study was carried out in a tertiary hospital in Jordan. Medical records of patients admitted to the medical ICU between 2013 and 2015 were reviewed. We aimed to identify the incidence, risk factors, and outcomes of AKI. Acute kidney injury network (AKIN) classification was used to define and stage AKI.</p><p><strong>Results: </strong>2530 patients were admitted to medical ICU, and the incidence of AKI was 31.6%, mainly in stage 1 (59.4%). In multivariate analysis, increasing age (odds ratio (OR) = 1.2 (95% CI 1.1-1.3), <i>P</i> = 0.0001) and higher APACHE II score (OR = 1.5 (95% CI 1.2-1.7), <i>P</i> = 0.001) were predictors of AKI, with 20.4% of patients started on hemodialysis. At the time of discharge, 58% of patients with AKI died compared to 51.3% of patients without AKI (<i>P</i> = 0.05). 88% of patients with AKIN 3 died by the time of discharge compared to patients with AKIN 2 and 1 (75.3% and 61.2% respectively, <i>P</i> = 0.001).</p><p><strong>Conclusion: </strong>AKI is common in ICU patients, and it increases mortality and morbidity. Close attention for earlier detection and addressing risk factors for AKI is needed to decrease incidence, complications, and mortality.</p>","PeriodicalId":46583,"journal":{"name":"Critical Care Research and Practice","volume":"2020 ","pages":"8753764"},"PeriodicalIF":1.7,"publicationDate":"2020-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2020/8753764","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39564129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}