• Asian Pacific Journal of Cancer Prevention
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• v.15 no.14
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• pp.5787-5791
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• 2014

Background: With increasing survival periods and diversification of treatment methods, treatment of critically ill cancer patients has become an important factor influencing patient prognosis. Patients with cancer are at high risk of infections and subsequent complications. This study investigated the incidence and factors contributing to the development of ventilator-associated pneumonia (VAP). Materials and Methods: This retrospective study investigated the incidence of VAP and factors leading to infection in patients admitted to the intensive care unit (ICU) of a cancer center from January 1, 2012 to December 31, 2013. Results: The incidence of VAP was 2.13 cases per 1,000 days of intubation, and 13 of 288 patients (4.5%) developed VAP. Lung cancer was the most common cancer associated with VAP (N=7, 53.9%), and longer hospital stays and intubation were associated with increased VAP incidence. In the group using a "ventilator bundle," the incidence was 1.14 cases per 1,000 days compared to 2.89 cases per 1,000 days without its use; however, this difference was not statistically significant (p=0.158). Age (${\geq}65$, OR=5.56, 95% confidence interval [CI]=1.29-23.95), surgery (OR=3.78, 95%CI=1.05-13.78), and tracheotomy (OR=4.46, 95%CI=1.00-19.85) were significant VAP risk factors. The most common causative organisms were methicillin-resistant Staphylococcus aureus (MRSA) and Pseudomonas aeruginosa (N=4, 30.8% each), followed by Acinetobacter baumannii and Candida albicans (N=2, 15.4% each). Conclusions: The incidence of pneumonia among critically ill cancer patients is highest in those with lung cancer, but lower than among non-cancer patients. The length of hospital stay and time on mechanical ventilation are important risk factors for development of VAP. Although not statistically significant, "ventilator bundle" care is an effective intervention that delays or reduces incidence of VAP. Major risk factors for VAP include age (${\geq}65$ years), surgery, and tracheostomy, while fungi, gram-negative bacteria, and multidrug-resistant organisms were identified as the major causative pathogens of VAP in this study.

• Clinical and Experimental Pediatrics
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• v.63 no.5
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• pp.184-188
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• 2020

Background: Many critically ill patients require transfer to a higher-level hospital for complex medical care. Despite the publication of the American Academy of Pediatrics guidelines for pediatric interhospital transportation services and the establishment of many pediatric transport programs, adverse events during pediatric transport still occur. Purpose: To determine the incidence of adverse events occurring during pediatric transport and explore their complications and risk factors. Methods: This prospective observational study explored the adverse events that occurred during the interhospital transport of all pediatric patients referred to the pediatric intensive care unit of Ramathibodi Hospital between March 2016 and June 2017. Results: There were 122 pediatric transports to the unit. Adverse events occurred in 25 cases (22%). Physiologic deterioration occurred in 15 patients (60%). Most issues (11 events) involved circulatory problems causing patient hypotension and poor tissue perfusion requiring fluid resuscitation or inotropic administration on arrival at the unit. Respiratory complications were the second most common cause (4 events). Equipment-related adverse events occurred in 5 patients (20%). The common causes were accidental extubation and endotracheal tube displacement. Five patients had both physiologic deterioration and equipment-related adverse events. Regarding transport personnel, the group without complications more often had a physician escort than the group with complications (92% vs. 76%; relative risk, 2.4; P=0.028). Conclusion: The incidence of adverse events occurring during the transport of critically ill pediatric patients was 22%. Most events involved physiological deterioration. Escort personnel maybe the key to preventing and appropriately monitoring complications occurring during transport.

• Journal of Clinical Nutrition
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• v.10 no.2
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• pp.51-55
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• 2018

Purpose: This study was conducted to assess how extreme obesity affects 30-day mortality in this patient group. Methods: A total of 802 patients who underwent emergency gastrointestinal surgery from January 2007 to December 2017 were retrospectively reviewed. Patients were divided into three groups according to their body mass index (BMI): group 1, normal weight (BMI: $18.5{\sim}22.9kg/m^2$); group 2, overweight (BMI: $23.0{\sim}29.9kg/m^2$ ); and group 3, obesity ($BMI{\geq}30kg/m^2$). Patients with a BMI under 18.5 were excluded from the analysis. Chi-squared test, Fisher's exact test, Kaplan-Meier survival analysis, and the log-rank test were used to assess and compare 30-day mortality rates between groups. Results: The mortality rates of group 1, group 2, and group 3 were 11.3%, 9.0%, and 26.9%, respectively (P<0.017). The mortality rate did not differ significantly between group 1 and 2 (11.3% vs. 9.0%; P=0.341), but group 1 and 2 showed better survival rates than group 3 (11.3% vs. 26.9%; P=0.028, 9.0% vs. 26.9%; P=0.011). Kaplan-Meier survival analysis revealed that group 3 had higher mortality than the other two groups (P=0.001). Conclusion: Obesity ($BMI{\geq}30kg/m^2$) was one of the risk factors influencing critically ill patients who underwent emergency surgery.

• Journal of Korean Academy of Nursing
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• v.22 no.4
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• pp.589-603
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• 1992

This study investigated a process to estimate the need for nursing staff on the basis of a patient elassification system and the required care needs and activities. The investigation was carried out in the following four steps. Step 1. Patients were classified according to the amount of nursing care need on each shift as class I (mildly ill), class II (mederately ill), class III (acutely ill), and class IV (critically ill). Step 2. Measurement of the direct nursing care hours needed for each patient class, and measurement of indirect nursing care hourse and personal time of the nursing staff. Step 3. Calculation of he total nursing workload in a nursing unit. Step 4. Estimation of the nursing staff needed. The investigation was carried out from July 17th to 30th, during 24hours every other day. The subjects were the patients and the nursing staff on two units of Seoul National University Hospital, Korea. Some of the results from the investigation are as follows : 1) Distribution of patient classification On the neuro surgical (N.S.), the distribution was class I, 22 patient, 3, class II, 27 patients, class III, 26 patients, and class IV, 25 patients, For the orthopedic surgical unit(0.5.), it was class I, 43 patients, class II, 43 patients, class III, patients, and class IV, 3 patients. 2) Direct nursing care hours per day On the N.S. unit, 3.2 hours of direct nursing care were needed for class I, 3.9 hours for class II, 5.1 hours of class III, and 6.2 hours for class IV patients, while 2.0 hours for class I, 2.5 hours for class II, 3.5 hours for class III, 5.0 hours class IV patients were needed on the 0.5. units. 3) Analysis of direct nursing care activities Activities were classified into assessment and observation(47%), medication(38.7%), communiontion(5.1%), exercise(2.4%), elimination and irrigation(1.3%), treatmemt(1.1%), hygiene(0.8%), nutrition(0.8%), and hot and cold compress(0.1%). 4) Average hours of indirect nursing care per day. On the N.S. unit 4.2 hours, and on the O.S. unit, 3.5 hours of RN indirect care was needed. 5) The average personal time used by the of nursing staff was 17 minutes for both RNs and nursing assistants in the N.S. unit, and 32 minutes for both RNs and nursing assistants in the O.S. unit. 6) Estimation of nursing staff needed on two specialized units of a university hospital For the N.S. nursing unit of 43 beds, 31 nursing staff would be indicated. For the 0.5. nursing unit of the same number of beds, 19 nursing staff would be indicated.

• Journal of Korean Academy of Nursing
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• v.20 no.1
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• pp.16-37
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• 1990

A cost analysis for hospitalized patients was carried out based upon Patient Classification System(PCS) in order to determine an appropriate nursing fee. The data were collected from 21 nursing units of three teaching hospitals from April 1 to June 30, 1989. first, all of the 22,056 inpatients were classified into mildly ill(Class Ⅰ), moderately ill(Class Ⅱ), acutely ill(Class Ⅲ), and critically ill(Class Ⅳ) by the PCS which had been carefully developed to be suitable for the Korean nursing units. Second. PCS cost accounting was applied to the above data. The distribution of inpatients, nursing costs, and nursing productivity were as follows : 1) Patient distribution ranged from 45% to class Ⅰ, 36% to class Ⅱ, 15% to class Ⅲ, and 4% to class Ⅳ, the proportion of class Ⅳ in ‘H’ Hospital was greater than that of the other two hospitals. 2) The proportion of Class Ⅲ and Ⅳ in the medical nursing units was greater than that of surgical nursing units. 3) The number of inpatients was greatest on Tuesdays, and least on Sundays. 4) The average nursing cost per hour was W 3,164 for ‘S’ hospital, W 3,511 for ‘H’ hospital and W 4,824 for ‘K’ hospital. The average nursing cost per patient per day was W 14,126 for ‘S’ Hospital, W 15,842 for ‘H’ hospital and W 21,525 for ‘K’ hospital. 5) The average nursing cost calculated by the PCS was W 13,232 for class Ⅰ, W 18,478 for class Ⅱ, W 23,000 for class Ⅲ, and W 25,469 for class Ⅳ. 6) The average nursing cost for the medical and surgical nursing units was W 13,180 and W 13,303 respetively for class Ⅰ, W 18,248 and W 18,707 for class Ⅱ, W 22,303 and W 23,696 for class Ⅲ, and W 24,331 and W 26,606 for class Ⅳ. 7) The nursing costs were composed of 85% for wages and fringe benefits, 3% for material supplies and 12% for overhead. The proportion of wages and fringe benefits among the three Hospitals ranged from 75%, 92% and 98% for the ‘S’, ‘H’, ‘K’ hospitals respectively These findings explain why the average nursing cost of ‘K’ hospital was higher than the others. 8) According to a multi- regression analysis, wages and fringe benefits, material supplies, and overhead had an equal influence on determining the nursing cost while the nursing hours had less influence. 9) The productivity of the medical nursing units were higher than the surgical nursing units, productivity of the D(TS) - nursing units was the lowest while the K(Med) - nursing unit was the highest in 'S' hospital. In ‘H’ hospital, productivity was related to the number of inpatients rather than to the characteristics of the nursing units. The ‘K’ hospital showed the same trend as ‘S’ hospital, that the productivity of the medical nursing unit was higher than the surgical nursing unit. The productivity of ‘S’ hospital was evaluated the highest followed by ‘H’ hospital and ‘K’ hospital. Future research on nursing costs should be extended to the other special nursing areas such as pediatric and psychiatric nursing units, and to ICU or operating rooms. Further, the PCS tool should be carefully evaluated for its appropriateness to all levels of institutions(primary, secondary, tertiary). This study took account only of the quantity of nursing services when developing the PCS tool for evaluating the productivity of nursing units. Future research should also consider the quality of nursing services including the appropriateness of nursing activities.

• Journal of Korean Public Health Nursing
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• v.27 no.2
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• pp.338-356
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• 2013

Purpose: This study critically reviewed nursing research psychotropic drugs that has been published in Korean journals. Another aim of this study was to identify trends in nursing research on psychotropic drugs and make suggestions for further study in Korea. Methods: Data were collected from degree theses and original articles on psychotropic drugs published in Korean journals from 1992 to 2013. Thirty-four articles were analyzed of which at least one nursing author participated in the study. Search keywords were "psychotropic drug" and "mentally ill patient & medication". Results: For the research design, quasi-experimental study was 58.8%, descriptive study was 17.7%, descriptive correlational study was 8.8%, qualitative study was 8.8% and model development research was 5.9%. Variables measured were knowledge of medication & symptom management, knowledge of disease, side effects, drug attitude, medication pattern, diet & activity, quality of life, and self-care. Conclusion: Despite recent increased interest in psychiatric medication, research on psychotropic drugs remains very limited, particularly regarding findings from a nurse's perspective. More research project should be designed to develop programs for the treatment of side effects from a nursing view-point.

• The Journal of Korean Oriental Chronic Disease
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• v.10 no.1
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• pp.39-45
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• 2005

Objectives It is the case study of a critically ill patient with cerebral infarction and acute edematous change at femur due to a hematoma, of whom taken care with herb medicine according to the diagnosis of SCM(Sasang Constitutional Medicine). Methods The syndrome of the patient was diagnosed as a superficial disease of Taeumin. So after the on-set of the femoral edema, Jowiseungchung-tang added Castanea mollissima(Gunyul) and Maladera castanea(Jejo) was used. And we checked the change of the circumferencial size her thigh and followed up the sonography. Results and conclusions The therapy was significantly effective, and the edema was rapidly absorbed. The circumferential size was 83cm at on-set time, but got smaller to 57cm almost same to the healthy side of her thigh, and there was no more hematoma or systemic hemorrhagic sign on the body.

• Journal of Korean Neurosurgical Society
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• v.66 no.2
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• pp.113-120
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• 2023

Artificial intelligence (AI) is a field of computer science that equips machines with human-like intelligence and enables them to learn, reason, and solve problems when presented with data in various formats. Neurosurgery is often at the forefront of innovative and disruptive technologies, which have similarly altered the course of acute and chronic diseases. In diagnostic imaging, such as X-rays, computed tomography, and magnetic resonance imaging, AI is used to analyze images. The use of robots in the field of neurosurgery is also increasing. In neurointensive care units, AI is used to analyze data and provide care to critically ill patients. Moreover, AI can be used to predict a patient's prognosis. Several AI applications have already been introduced in the field of neurosurgery, and many more are expected in the near future. Ultimately, it is our responsibility to keep pace with this evolution to provide meaningful outcomes and personalize each patient's care. Rather than blindly relying on AI in the future, neurosurgeons should gain a thorough understanding of it and use it to enhance their patient care.

• Tuberculosis and Respiratory Diseases
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• v.54 no.3
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• pp.311-319
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• 2003

Background : Previous studies have suggested that a B-type natriuretic peptide(BNP) test can provide important information on diagnosis, as well as predicting the severity and prognosis of heart failure. Myocardial dysfunction is often observed in critically ill noncardiac patients admitted to the Intensive Care Unit, and the prognosis of the myocardial dysfunction needs to be determined. This study evaluated the predictability of BNP on the prognosis of critically ill noncardiac patients. Methods : 32 ICU patients, who were hospitalized from June to October 2002 and in whom the BNP test was evaluated, were enrolled in this study. The exclusion criteria included the conditions that could increase the BNP levels irrespective of the severity, such as congestive heart failure, atrial fibrillation, ischemic heart disease, and renal insufficiencies. A triage B-Type Natriuretic Peptide test with a RIA-kit was used for the fluorescence immunoassay of BNP test. In addition, the acute physiology and the chronic health evaluation (APACHE) II score and mortality were recorded. Results : There were 16 males and 16 females enrolled in this study. The mean age was 59 years old. The mean BNP levels between the ICU patients and control were significantly different ($186.7{\pm}274.1$ pg/mL vs. $19.9{\pm}21.3$ pg/mL, p=0.033). Among the ICU patients, there were 14(44----) patients with BNP levels above 100 pg/mL. The APACHE II score was $16.5{\pm}7.6$. In addition, there were 11 mortalities reported. The correlation between the BNP and APACHE II score, between the BNP and mortality were significant (r=0.443, p=0.011 & r=0.530, p=0.002). The mean BNP levels between the dead and alive groups were significantly different ($384.1{\pm}401.7$ pg/mL vs. $83.2{\pm}55.8$ pg/mL p=0.033). However, the $PaO_2/FiO_2$ did not significantly correlate with the BNP level. Conclusion : This study evaluated the BNP level was elevated in critically ill, noncardiac patients. The BNP level could be a useful, noninvasive tool for predicting the prognosis of the critically ill, noncardiac patients.

• Journal of Neurocritical Care
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• v.11 no.2
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• pp.63-70
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• 2018

Management of mechanical ventilation is essential for patients with neuro-critical illnesses who may also have impairment of airways, lungs, respiratory muscles, and respiratory drive. However, balancing the approach to mechanical ventilation in the intensive care unit (ICU) with the need to prevent additional lung and brain injury, is challenging to intensivists. Lung protective ventilation strategies should be modified and applied to neuro-critically ill patients to maintain normocapnia and proper positive end expiratory pressure in the setting of neurological closed monitoring. Understanding the various parameters and graphic waveforms of the mechanical ventilator can provide information about the respiratory target, including appropriate tidal volume, airway pressure, and synchrony between patient and ventilator, especially in patients with neurological dysfunction due to irregularity of spontaneous respiration. Several types of asynchrony occur during mechanical ventilation, including trigger, flow, and termination asynchrony. This review aims to present the basic interpretation of mechanical ventilator waveforms and utilization of waveforms in various clinical situations in the neuro-ICU.