Incidence of and risk factors for postoperative delirium in older adult patients undergoing noncardiac surgery: a prospective study.

BACKGROUND: To identify the incidence of, risk factors for, and outcomes associated with postoperative delirium (POD) in older adult patients who underwent noncardiac surgery. METHODS: This prospective study recruited patients aged ≥ 60 years who were scheduled to undergo noncardiac surgery at Siriraj Hospital (Bangkok, Thailand). Functional and cognitive statuses were assessed preoperatively using Barthel Index (BI) and the modified Informant Questionnaire on Cognitive Decline in the Elderly, respectively. POD was diagnosed based on the Diagnostic and Statistical Manual of Mental Disorders Fifth Edition criteria. Incidence of POD was reported. Univariate and multivariate analyses were used to identify risk factors for POD. RESULTS: Of the 249 included patients, 29 (11.6%) developed POD. Most patients (61.3%) developed delirium on postoperative day 1. Univariate analysis showed age ≥ 75 years, BI score ≤ 70, pre-existing dementia, preoperative use of opioid or benzodiazepine, preoperative infection, and hematocrit < 30% to be significantly associated with POD. Multivariate logistic analysis revealed pre-existing dementia (adjusted risk ratio [RR]: 3.95, 95% confidence interval [CI]: 1.91-8.17; p < 0.001) and age ≥ 75 years (adjusted RR: 2.54, 95% CI: 1.11-5.80; p = 0.027) to be independent risk factors for POD. Median length of hospital stay was 10 (range: 3-36) days for patients with POD versus 6 (range: 2-76) days for those without delirium (p < 0.001). CONCLUSIONS: POD remains a common surgical complication, with an incidence of 11.6%. Patients with pre-existing dementia and age ≥ 75 years are the most vulnerable high-risk group. A multidisciplinary team consisting of anesthesiologists and geriatricians should implement perioperative care to prevent and manage POD.

Postoperative delirium in critically ill surgical patients: incidence, risk factors, and predictive scores.

BACKGROUND: A common postoperative complication found among patients who are critically ill is delirium, which has a high mortality rate. A predictive model is needed to identify high-risk patients in order to apply strategies which will prevent and/or reduce adverse outcomes. OBJECTIVES: To identify the incidence of, and the risk factors for, postoperative delirium (POD) in surgical intensive care unit (SICU) patients, and to determine predictive scores for the development of POD. METHODS: This study enrolled adults aged over 18 years who had undergone an operation within the preceding week and who had been admitted to a SICU for a period that was expected to be longer than 24 h. The CAM - ICU score was used to determine the occurrence of delirium. RESULTS: Of the 250 patients enrolled, delirium was found in 61 (24.4%). The independent risk factors for delirium that were identified by a multivariate analysis comprised age, diabetes mellitus, severity of disease (SOFA score), perioperative use of benzodiazepine, and mechanical ventilation. A predictive score (age + (5 × SOFA) + (15 × Benzodiazepine use) + (20 × DM) + (20 × mechanical ventilation) + (20 × modified IQCODE > 3.42)) was created. The area under the receiver operating characteristic (ROC) curve (AUC) was 0.84 (95% CI: 0.786 to 0.897). The cut point of 125 demonstrated a sensitivity of 72.13% and a specificity of 80.95%, and the hospital mortality rate was significantly greater among the delirious than the non-delirious patients (25% vs. 6%, p < 0.01). CONCLUSIONS: POD was experienced postoperatively by a quarter of the surgical patients who were critically ill. A risk score utilizing 6 variables was able to predict which patients would develop POD. The identification of high-risk patients following SICU admission can provide a basis for intervention strategies to improve outcomes. TRIAL REGISTRATION: Thai Clinical Trials Registry TCTR20181204006 . Date registered on December 4, 2018. Retrospectively registered.

Correction to: Postoperative delirium in critically ill surgical patients: incidence, risk factors, and predictive scores.

Following publication of the original article [1], the authors reported a missing data on Table 1 in their paper. The original article [1] has been updated.

Prediction of massive transfusion in trauma patients in the surgical intensive care units (THAI-SICU study).

PURPOSE: After damage control surgery, trauma patients are transferred to intensive care units to restore the physiology. During this period, massive transfusion might be required for ongoing bleeding and coagulopathy. This research aimed to identify predictors of massive blood transfusion in the surgical intensive care units (SICUs). METHODS: This is an analysis of the THAI-SICU study which was a prospective cohort that was done in the 9-university-based SICUs in Thailand. The study included only patients admitted due to trauma mechanisms. Massive transfusion was defined as received ≥10 units of packed red blood cells on the first day of admission. Patient characteristics and physiologic data were analyzed to identify the potential factors. A multivariable regression was then performed to identify the significant model. RESULTS: Three hundred and seventy patients were enrolled. Sixteen patients (5%) received massive transfusion in the SICUs. The factors that significantly predicted massive transfusion were an initial sequential organ failure assessment (SOFA) ≥9 (risk difference (RD) 0.13, 95% confidence interval (CI): 0.03-0.22, p = 0.01); intra-operative blood loss ≥ 4900 mL (RD 0.33, 95% CI: 0.04-0.62, p = 0.02) and intra-operative blood transfusion ≥ 10 units (RD 0.45, 95% CI: 0.06 to 0.84, p = 0.02). The probability to have massive transfusion was 0.976 in patients who had these 3 factors. CONCLUSION: Massive blood transfusion in the SICUs occurred in 5%. An initial SOFA ≥9, intra-operative blood loss ≥4900 mL, and intra-operative blood transfusion ≥10 units were the significant factors to predict massive transfusion in the SICUs.

Characters of Nutrition Status and Energy-delivery Patterns of the University-based Surgical Intensive Care Units in Thailand (Multi-center THAI-SICU Study).

AIM: The authors aimed to describe nutrition status and energy-delivery characters in multi-center THAI-SICU study. MATERIAL AND METHODS: Eligible patients admitted in SICU were 1,686 after excluding 563 of 2,249 participants owing to very short stay or non-alive within 24 hours after admission and missing data. The study was a posthoc analysis and multicenter descriptive design. The analytic methods described categorical data in percentage and the continuous data in the median with interquartile range. Variables divided into baseline characteristics and nutrition data before SICU admission, and the pattern of energy delivery in SICU. Statistical significance accepted as a p-value less than 0.05. RESULTS: The average age was 64 (52-76) years with 57% male. The median of serum albumin level at admission (interquartile range, IQR) was 2.8 (2.2-3.4). There was 46 -47 percent of nutrition risk patient. Less than 10 percent of the patient had enteral (EN), parenteral (PN) or their combination before admission. History of weight loss and appetite loss was 27-31 percent. However, seventy percent of the patient could not define the duration of the symptom. EN was initiated early, but the tendency of full feeding was 7-10 days. At that period, supplemental PN was added around 30 percent of total calories. The composition of PN was quite low in these study which contains only 15-16 percent of total calories. The average energy delivery was 20 kcal/kg/day (the recommendation is 25-30 kcal/kg/day). CONCLUSION: The patient's nutrition status before SICU admission was at risk of 46-47% and weight loss and appetite loss might unreliable in ICU setting. EN is started early with gradually increase up to 7-10 days. The average total calories requirement is lower than a recommendation.

Agreement of Variables Selection and Program Development for Data Collection in Thai Intensive Care Unit by Delphi Method.

Objective: The objective of this study was to determine the data collection variables and program for Thai intensive care units (ICU) as well as to obtain agreement using the modified Delphi method. Material and Method: The variables for program development were modified from the THAI-SICU study case record form. The first open discussion on the prototype was performed in a program development workshop. After revision, the stakeholder agreement was performed by modified Delphi method on the final browser program. All the categorical variable details were scored by a rating scale at five levels. The agreement level was defined as the median score at of least four and the interquartile range (IQR) up to two. Results: During June to September 2015, a total of 20 questionnaires from invited intensive care unit (ICU) expert stakeholders were returned (11 from physicians or surgeons, and 9 from critical care nurses). All of the seven parts of the variable groups, including: 1) patient characteristics, 2) diagnosis, 3) adverse events, 4) detail of operation in surgical cases, 5) ICU intervention, 6) discharge, and 7) summarized report, were agreed upon as the preset criteria (Median ≥4 and IQR ≤2). Conclusion: The selected variables in seven parts of the variable group via browser system were widely agreed upon from stake holders in Thai ICUs.

Self-Reporting of Medication Errors in Critically Ill Surgical Patients in the THAI-SICU Study.

Objective: The objective of this study was to collect the data of medication errors by the self-report of doctors and nurses in critically ill surgical patients. Material and Method: All data were collected from THAI-SICU database in nine medical schools in Thailand during a period of 22 months. The occurrence and medication error related factors were recorded. Results: From 4,652 admissions, there were only 10 cases of medication error. Of these, there were only 7 cases of complete self-report medication error, and all of them had no critical side effects. Most cases were of receiving wrong doses of medicine especially overdosing. The medicine preparers, administrators and the error detectors were mostly nurses. For immediate outcomes, two cases were reported of low blood pressure and one case was reported of lowering self-conscious. For longterm outcomes, there were two cases of prolonged ICU stays. Regarding the contributing factors, the most frequent problem found was communication. The most important factor minimizing incidents was to increase proper care. As to suggested corrective strategies, it was found that improved supervision was most needed. Conclusion: Reporting of medication errors by a self-report of doctors and nurses is low in this cohort, which might result from occurrences not being reported. The wrong dose is the most common occurrence and the communication is the most related factor.

The Association between Red Blood Cell Transfusion and Hospital Mortality in Critically Ill Surgical Patients: The Multi-center Thai University-Based Surgical Intensive Care Units Study (THAI-SICU Study).

Objective: Red blood cell transfusion (RBCT) is commonly prescribed to critically ill patients with anemia. Nevertheless, the benefits of RBCT in these patients, particularly critically ill surgical patients, are still controversial. The aim of this study is to explore the association between RBCT and hospital mortality in Thai critically ill surgical patients. Material and Method: This study was a part of the multi-center, prospective, observational study, which included adult patients admitted to the SICUs after surgery. Patients were categorized into transfusion and no transfusion groups according to whether they received RBCT during SICU stay or not. The multiple logistic regression analysis was performed to determine whether RBCT was an independent risk factor for hospital mortality. The patients were also matched between two groups based on the propensity score for RBCT requirement and were then compared. Results: There were 2,531 patients included in this study. The incidence of RBCT in SICU was 40.3%. Overall, there was no association between RBCT in SICU and hospital mortality (adjusted OR 1.33, 95% CI 0.83-2.11) except in the subgroup of patients with age of <65 years old (adjusted OR 1.99, 95% CI 1.03-3.84). However, when the amount of RBCT was more than 1,200 mL, it was independently associated with increased hospital mortality (adjusted OR 2.55, 95% CI 1.35-4.81). In the propensity-score matching cohort, there was no association between RBCT in SICU and hospital mortality (adjusted OR 1.56, 95% CI 0.88-2.77) except when the amount of RBCT was more than 600 mL (601-1,200 mL, adjusted OR 3.14, 95% CI 1.47-6.72 and >1,200 mL, adjusted OR 3.58, 95% CI 1.36-9.48). Conclusion: RBCT should be considered as a life-saving intervention but with potential risks of adverse events. Identifying patients who will likely gain benefit from RBCT and implementing the restrictive transfusion strategy may be the keys to improve outcomes.

Incidence and Risk Factors of Unplanned Extubation in Critically Ill Surgical Patients: The Multi-center Thai University-based Surgical Intensive Care Units Study (THAI-SICU Study).

Objective: Unplanned extubation (UE) is one of the most troubling events in critically ill patients who require endotracheal intubation and mechanical ventilation. The aims of this study are to determine the incidence and to identify the risk factors associated with UE in critically ill surgical patients. Material and Method: This was a multi-center prospective observational cohort study, which included surgical patients admitted to nine university-based surgical intensive care units (SICUs) in Thailand between April 2011 and January 2013. UE was defined as deliberate extubation by patients (self-extubation) or accidental extubation during procedures or transportation. The incidence of UE was calculated, the adjusted logistic regression model was performed to determine the independent risk factors for UE and the outcomes were compared between those with planned extubation and UE. Results: 2,890 patients required endotracheal intubation and mechanical ventilation were included in the analysis. Of these, 54 patients experienced UE and, therefore, the incidence of UE was 1.9%. Five independent risk factors for UE were identified; congestive heart failure (adjusted odds ratio, OR, 3.48; 95% CI, 1.29-9.40), emergency surgery (adjusted OR, 2.18; 95% CI, 1.01-4.74), non-postoperative status (adjusted OR, 2.37; 95% CI, 1.05-5.37), sedation usage (adjusted OR, 3.19; 95% CI, 1.72-5.93) and delirium (adjusted OR, 3.61; 95% CI, 1.71-7.60). ICU length of stay (LOS) was significantly longer in patients with UE than those with planned extubation (adjusted coefficient, 2.76; 95% CI, 1.34-4.19). There was no significant difference between the two groups in terms of hospital LOS as well as ICU and 28-day mortality. Conclusion: The incidence of UE in critically ill surgical patients was 1.9%. Five independent risk factors for UE were: underlying congestive heart failure, emergency surgery, non-postoperative status, sedation usage, and delirium. Patients with UE had significantly longer ICU LOS than those with planned extubation.

The Differences of Nutrition Status, Energy Delivery and Outcomes between Metropolis and Regional University-Based Thai Surgical Intensive Care Units.

Objective: The objective of this study was to compare the differences of nutrition status, nutrition delivery, and the outcomes between the metropolis (MUH) and regional university based hospitals (RUH) in Thailand. Material and Method: The nutrition data were retrieved from the THAI-SICU database. A total of 1,686 patients (MUH 927 patients vs. RUH 759 patients) with completion of nutrition status and nutrition delivery data were included in this analysis. The enrolled patients from study centers located in Bangkok were defined as MUH, and the patients from Chiang Mai were defined as RUH. Patient characteristics, nutrition status using the subjective global assessment (SGA) and nutrition risk screening (NRS), nutrition delivery, and outcomes of treatment were recorded. The outcome associations were analyzed by a multivariable regression model. Results: At admission, there were significant differences of age, gender, body mass index, disease severity, albumin level, and diagnosis. RUH had significantly poorer nutritional status than MUH (RUH vs. MUH: SGA class B and C, 57.7% vs. 37.1%, p<0.001; NRS at risk, 56.3% vs. 38.4%, p<0.001). The tendency of total calories and enteral nutrition delivery per day of RUH was significantly lower than MUH especially in the first three weeks of hospitalization. Carbohydrates were the main resource for parenteral nutrition. Although there was no difference of protein delivery, MUH had a significantly higher prescription of fat emulsion especially in the 1st-2nd weeks. Even though there were higher occurrences of intensive care unit (ICU) mortality, 28-day mortality, sepsis occurrence, ICU length of stay (LOS), and hospital LOS in RUH, the multivariable analysis did not demonstrate the statistical value of these outcomes. Conclusion: RUH had a poorer nutritional status. MUH had more total caloric intake and enteral nutrition delivery per day especially during the first three weeks. However, the treatment outcomes showed no differences in multivariable analysis.

Outcomes of Nutrition Status Assessment by Bhumibol Nutrition Triage/Nutrition Triage (BNT/NT) in Multicenter THAI-SICU Study.

Objective: The objective of the study is to evaluate the nutrition assessment tool used by Bhumibol Nutrition Triage/Nutrition Triage (BNT/NT) for patient outcomes in a surgical intensive care unit (SICU). Material and Method: All data were retrieved from the THAI-SICU database. A total of 1,685 patients from three medical centers were participants in the nutrition project and were enrolled onto this study. The parameters needed for BNT/NT scoring were recorded including body mass index (BMI), weight change, energy delivery, age, and disease severity. The BNT/NT calculation was classified into 4 groups as BNT/NT I to IV. An adjusted odds ratio (OR) with 95% confidence interval (CI) of mortality and sepsis occurrence were reported. Results were classed as being statistically significant at p<0.05. Results: Regarding the nutrition assessment classification, the patients admitted to SICU were classified as BNT/NT class I48.6%, class II 30.0%, class III 9.3%, and class IV 12.1%. There were statistically significant differences between classes in terms of BMI, weight change, energy delivery and disease severity. In addition, the BNT/NT classification was also significantly associated with ICU mortality [OR (95% CI): 1.51 (1.25-1.83); p<0.001], 28 day mortality [1.47 (1.23-1.74); p<0.001], and sepsis occurrence [1.41 (1.25-1.60); p<0.001]. Conclusion: Most of the patients admitted to SICU had a low nutrition risk BNT/NT class I and II. The higher BNT/NT scores were associated with mortality and sepsis occurrence in SICU.

Hazards and Intensive Care Unit Economic Burden of Cigarette Smoking on Critically Ill Surgical Patients: Analysis of the THAI-SICU Study.

Objective: Cigarette smoking is not only has detrimental effects on the respiratory system but also contributes to development of atherosclerosis and inflammatory vascular reactions. We hypothesized whether smoking is associated with increased risk of acute respiratory distress syndrome (ARDS), systemic inflammatory response syndrome (SIRS), sepsis, distant organ dysfunctions, and the increase of total cost of surgical intensive care unit (SICU) in critically ill surgical patients. Material and Method: We performed analysis using the THAI-SICU data, a prospective, observational, multicenter study in patients who admitted to SICU in nine university-based hospitals in Thailand. The patients were categorized into 3 groups based on their smoking histories, which were 1) never smoked, 2) former smoker, and 3) current smoker. The primary outcome was probability of ARDS and the secondary outcomes included incidences of SIRS, sepsis, distant organ dysfunction (included acute kidney injury (AKI) and acute myocardial infarction (AMI)), total SICU cost, and 28-day mortality Results: A total of 4,652 patients had complete data of smoking and were analyzed. The smoking status was never smoked (2,947 patients), former smokers (1,148 patients), and current smokers (557 patients). Compared to current smokers and former smokers, patients who had never smoked had significantly lower proportion of patients with chronic obstructive pulmonary disease (p<0.01) and had significantly higher PaO2/FiO2 ratio on SICU admission (p = 0.02). Compared to patients who had never smoked and former smokers, current smokers had significantly higher probability of ARDS (p = 0.003), higher incidence of SIRS (p = 0.006), and AKI (p<0.001), after adjustment for age, gender, APACHE II score, and patients' pre-existing diseases. We found that every 1-pack year of cigarette smoking increased risk of ARDS with a hazard ratio of 1.02 (95% CI 1.01-1.03, p = 0.001). There was no difference in incidence of sepsis, AMI, and 28-day mortality among three groups of patients. Current smokers had significantly higher SICU cost, followed by former smokers, and patients who had never smoked (p = 0.02). Conclusion: In critically ill surgical patients, we found dose-response association between smoking pack year and risk of ARDS. Compared to patients who had never smoked and former smokers, current smokers had significantly higher probability of ARDS, higher incidence of SIRS, AKI, and higher total SICU cost. Our findings demonstrated harm of cigarette smoking in critically ill surgical patients who admitted to SICU.

Prevalence and Impact of Overweight and Obesity in Critically Ill Surgical Patients: Analysis of THAI-SICU Study.

Objective: To investigate the prevalence of overweight and obesity, and their impacts in patients admitted to a surgical intensive care unit (SICU) in Thailand. Material and Method: We conducted an analysis using the THAI-SICU database. All 4,579 patients who had weight and height measured were classified into four groups using body mass index (BMI) based on the World Health Organization criteria, which were 1) underweight (BMI <18.5 kg/m2), 2) normal BMI (BMI 18.5-24.9 kg/m2), 3) overweight (BMI 25-29.9 kg/m2), and 4) obese (BMI >30 kg/m2) groups. Primary outcome was prevalence of overweight and obesity. Secondary outcomes were 28-day survival, and SICU outcomes between four patient groups. Results: There were 768 (16.8%) of underweight, 2,624 (57.3%) of normal BMI, 858 (18.7%) of overweight, and 329 (7.2%) of obese patients. Compared to other three patient groups, obese had the highest 28-day survival (log-rank, p<0.001), lowest incidence of systemic inflammatory response syndrome (SIRS) (underweight 41.1%, normal BMI 35.6%, overweight 34.5%, and obese 29.5%; p = 0.001), and lowest incidence of new infection (underweight 27.3%, normal BMI 23.3%, overweight 24.5%, and obese 20.4%; p = 0.047). After adjustment for related confounding factors, we found that every one unit increasing of BMI associated with lower risk of hospital mortality [odds ratio, OR, 0.97(95% confidence interval, CI, 0.94-0.99); p = 0.04], higher risk of acute respiratory distress syndrome (ARDS) [OR 1.06 (95% CI 1.03-1.08); p<0.001], and higher risk of intra-abdominal hypertension (IAH) [OR 1.06 (95% CI 1.03-1.09); p<0.001]. Conclusion: The prevalence of overweight and obesity in Thai critically ill surgical patients were 18.7% and 7.2%, respectively. Compared to patients with lower BMI, patients with higher BMI had significantly lower mortality but greater risk of ARDS and IAH.

Prevalence, Outcomes and Risk factors of Acute Kidney Injury in Surgical Intensive Care Unit: A Multi-Center Thai University-Based Surgical Intensive Care Units Study (THAI-SICU Study).

Objective: Acute kidney injury (AKI) is one of the most common problems in critically ill patients. AKI associates with poor outcome in ICU. The recognition of the prevalence and risk factors of AKI is important. This could lead to the prevention of AKI and improve patient's outcome. This study aims to identify the prevalence, outcomes and independent risk factors of AKI in Thai surgical intensive care units. Material and Method: We conducted the prospective cohort study from nine university-based SICUs. The patients were diagnosed AKI by Acute Kidney Injury Network (AKIN) classification. The types of RRT and outcomes including mortality were collected. The risk factors of AKI were identified. Results: A total cohort of 4,652 patients was included for the present study. AKI was diagnosed in 786 (16.89%) patients. The ICU mortality was higher in patients with AKI (29.90% vs. 5.48%, p-value <0.001). Among patients with AKI staging, we found that those with AKIN III had higher ICU mortality compared to patients with AKIN II and AKIN I respectively (47.66% vs. 26.67% vs. 14.69%, p-value <0.001). Patients with AKI had higher 28 day-mortality compared with those without AKI (37.53% vs. 8.98%, p-value <0.001). The independent risk factors of AKI were higher APACHE II scores (OR 1.04, 95% CI 1.01-1.06, p-value = 0.001), lower serum albumin (OR 0.82, 95% CI 0.70-0.97, p-value = 0.020), organ failures which were in the gastrointestinal system (OR 1.53, 95% CI 1.13-2.08, p-value = 0.007), cardiovascular system (OR 1.95, 95% CI 1.34-2.83, p-value <0.001), neurological system (OR 1.37, 95% CI 1.02-1.85, p-value = 0.038) and urinary system (OR 7.00, 95% CI 5.21-9.40, p-value <0.001). Conclusion: Acute kidney injury associates with poor outcomes including increased ICU and 28-day mortality. Independent risk factors of AKI in the present study were higher APACHE II scores, lower serum albumin and organ failures on admission.

The Impact of Delirium on Clinical Outcomes in Multi-Center Thai Surgical Intensive Care Units: A Prospective Cohort Study.

Objective: Delirium in intensive care units (ICU) increases risks in prolonged mechanical ventilation, hospitalization, and mortality rate. The purpose of this study is to determine if delirium in the surgical intensive care units (SICU) is an independent predictor of clinical outcomes during hospitalization. Material and Method: A multi-center, prospective cohort study was conducted between April 2011 and January 2013. All patients who were admitted to nine university-based SICU were enrolled. Delirium was diagnosed by using the Intensive Care Delirium Screening Checklists. The clinical outcomes of study included length of mechanical ventilation, length of hospital stay, ICU and 28 day mortality. Cox proportional hazard regression model was used to assess the effects of delirium on ICU and 28 day mortality. Results: A total of 4,652 patients were included. One hundred and sixty-three patients were diagnosed delirium (3.5%, 163 of 4,652). Patients who experienced delirium during ICU admission were significantly older (65.0+15.8 years versus 61.6+17.3 years, p = 0.013), had higher American Society of Anesthesiologists physical status (24.3% versus 12.2%, p<0.001), higher Acute Physiology and Chronic Health Evaluation II score (16 (12-23) versus 10 (7-15), p<0.001), and higher Sequential Organ Failure Assessment score (5 (2-8) versus 2 (1-5), p<0.001) compared to non-delirium. Delirious patients also had higher ventilator days (7 (4-17) versus 2 (1-4), p<0.001, longer length of hospital stay (22 (14-34) versus 15 (9-26), p<0.001) and higher ICU mortality (24% versus 9%, p<0.001), and 28-day mortality (28% versus 13%, p<0.001). Patients who developed delirium in the intensive care unit were associated with increased 28-day mortality (adjusted HR = 2.47, 95% CI: 1.13-5.41, p = 0.023). Conclusion: Delirium in an ICU was a major predictor of hospital mortality after adjusted for relevant covariates. Routine monitoring of delirium, early detection, and implementation of preventive strategy are recommended.

Incidence of and Risk Factors for Acute Respiratory Distress Syndrome in Patients Admitted to Surgical Intensive Care Units: The Multicenter Thai University- Based Surgical Intensive Care Unit (THAI-SICU) Study.

Objective: The incidence and outcomes of acute lung injury (ALI)/acute respiratory distress syndrome (ARDS) are unclear. We evaluated the cumulative incidence of, risk factors for, and outcomes of ALI/ARDS in surgical ICUs (SICUs). Material and Method: The multicenter Thai University-based Surgical Intensive Care Unit (THAI-SICU) study was a prospective, observational cohort study including nine university-based SICUs throughout Thailand from April 2011 to January 2013. All >18-year-old surgical patients who were admitted to general SICUs were recruited. The primary outcome was the incidence of ALI/ARDS. Results: In total, 4,652 patients were analyzed. ALI/ARDS new developed in 114 patients (2.5%). Patients with ALI/ARDS had higher APACHE II (20.0 vs. 11.4, respectively; p<0.001) and SOFA scores (7.3 vs. 3.1, respectively; p<0.001) and a higher incidence of past or current smoking (48% vs. 36%, respectively; p<0.001) than the non-ARDS patients. The 28-day mortality rate was significantly higher in patients with than without ALI/ARDS (50% vs. 12%; p<0.001). Higher APACHE II and SOFA scores and higher rates of current or past smoking were independent predictors of ALI/ARDS. Conclusion: The incidence of ALI/ARDS in the THAI-SICU study was low, but the mortality rate was high. Higher severity scores and smoking were associated with ALI/ARDS.

Cardiopulmonary monitoring in Thai ICUs (ICU-rESOURCE I Study).

OBJECTIVE: Cardiopulmonary monitoring (CPM) is rapidly progressing but data regarding CPM in Thai ICUs was unavailable. The objective of this study was to describe the situation, and gaps of CPM in Thai ICUs. MATERIAL AND METHOD: Data were retrieved from the ICU-RESOURCE I study database survey CPM was divided into two aspects of device and measurement methods. These were categorized by device availability grading (AG), device availability per bed (DPB) and numeric frequency grading scale (FGS). Device availability was compared between academic and non-academic ICUs. Gap analysis of DPB and FGS was performed. Statistical significant difference was defined as p-value < 0.05. RESULTS: One hundred and fifty-five ICUs across Thailand participated in this study. Academic ICUs had significantly more devices available in new equipment with p < 0.05 (Vigilio, PiCCO, NICOM, esophageal pressure monitoring, transcutaneous PO2, electrical impedance tomography of lung) as well as measurement methods (stroke volume variation [SVV], pulse pressure variation [PPC], central venous oxygen saturation [ScvO2], lung mechanics). Most of new and higher technological devices had low density and few were available in all of Thai ICUs. However, in gap analysis, although these new devices and measurement techniques were available in ICUs, they were not frequently utilized. CONCLUSION: New technology devices of CPM had more availability in ACAD than in non-ACAD ICUs. Formal continuous training in new measurement methods should be established for reducing the availability and utilization gap (Thai Clinical Trial Registry: TCTR-201200005).

Incidence and risk factors for ventilator-associated pneumonia in the surgical intensive care unit, Siriraj Hospital.

BACKGROUND: Ventilator-associated pneumonia (VAP) is a serious illness with substantial morbidity and mortality resulting in increased costs of hospital care. Even though bundles of care to prevent VAP have been established, the incidence has not been shown to have improved. OBJECTIVE: To determine the incidence and risk factors of VAP in the general surgical intensive care unit, Siriraj Hospital (SICU). MATERIAL AND METHOD: During the period from June 1st, 2010 to June 30th, 2011, 228 adult patients admitted to the general SICU were recruited. All patients required ventilator support for more than 48 hours. Data were collected by reviewing patient medical records and the retrieval of information from the Nosocomial Infection Control, Siriraj Hospital. RESULTS: A total of 21 patients (9.21%) were diagnosed with VAP or an incidence of 8.21 cases/1,000 ventilator days. The onset of VAP was late in the majority of patients. The most common pathogens were A. baumannii (66%) followed by P. aeuruginosa (19%). Multiple logistic regression analyses showed that the numbers of central venous catheter placements, intubations and surgeries and the use of muscle relaxants and steroids were independent risk factors for VAP Median duration of ventilator and ICU lengths of stay were longer in the VAP group (25 vs. 6 days, 25 vs. 7 days, respectively; all p < 0.0001). In addition, the hospital mortality rates were significantly higher in the VAP group (33.33% vs. 12.07%; p = 0.008). CONCLUSION: The incidence of VAP was high in the SICU. VAP bundles including weaning protocols and airway care should be implemented.

Incidence of red blood cell transfusion in mechanically ventilated surgical patients at Siriraj Hospital.

BACKGROUND: Anemia is commonly encountering surgical critically ill patients. The incidence of red blood cell (RBC) transfusion and transfusion trigger in this population has not been previously reported in a large tertiary care center in Thailand OBJECTIVE: To describe the incidence of RBC transfusion and transfusion trigger and to determine the factors and outcomes associated with RBC transfusion. MATERIAL AND METHOD: Data of 288 adult surgical patients requiring mechanical ventilation for > 24 hours was retrospectively reviewed Patient characteristic, outcomes, and transfusion data were collected. RESULTS: The incidence ofRBC transfusion was 83.0% (95% confidence interval (CI) 78.0-87.0%). The mean hemoglobin level before RBC transfusion was 8.7 +/- 1.2 g/dL. Patients who received RBC transfusion had significantly higher morbidity and mortality when compared with those who did not. Independent factors associated with RBC transfusion were low body weight, high Sequential Organ Failure Assessment (SOFA) score, and low hemoglobin level on admission (adjusted odds ratio 0.97, 1.19, and 0.60. respectively). CONCLUSION: In critically ill adult surgical patients, the incidence of RBC transfusion and transfusion trigger remained within high threshold Large randomized controlled studies are warranted to confirm potential benefit of RBC transfusion in surgical critically ill patients.

A multi-center Thai university-based surgical intensive care units study (THAI-SICU study): methodology and ICU characteristics.

OBJECTIVE: Although there were two large intra-operative observational studies on Thai surgical patients (THAI and THAI-AIMS), there has been no available study on critically ill surgical patients regarding their adverse events and outcomes. A THAI-Surgical Intensive Care Unit (SICU) study has been established for monitoring the occurrence of these adverse events and outcomes in the SICU. The objective of this report is to describe the methodology of the THAI-SICU study and participating SICUs' characteristics as well as the early recruitment results on patients enrolled in the present study. MATERIAL AND METHOD: The present study is designed as a multi-center, prospective, observational study. This report describes the method of case record form development and summarizes their collected parameters as well as the adverse event surveillance variables. All of nine SICU characteristics are described regarding their management systems, physicians' and nurses' work patterns. The final group of enrolled patients is reported. RESULTS: A total of nine university-based SICUs were included in the present study. All participating hospitals are residency training centers. Four of the SICUs, fulltime directors are anesthesiologists. Only one hospital's SICU is directed by a surgeon. Two SICUs were closed ICUs, three were mandatory consulting units, one was an elective consultation unit and the remaining three ICUs had no directors. Most of the participating SICUs had heterogeneity of surgical specialty patients. Six SICUs had regular resident rotations and only two of the SICUs had critical care fellowship training. There were significant differences regarding the nursing workload among the ICUs. The patient to registered nurse ratio ranged from 0.9-2.0. After a total of 19.7 months of a recruitment period, the total number of patient admissions was 6,548 (1,894 patients were excluded). A total cohort of 4,654 patients was included for further analytical processes. CONCLUSION: There were differences in ICU management systems, physician and specialist coverage, nurse burdens, nurse sparing, and types of patients admitted in the university based SICUs. This presentation is the pioneer multi-center study on Thai SICUs in which adverse events and outcomes are reported.