Evaluation of the predictive indices for candidemia in an adult intensive care unit

INTRODUCTION: To evaluate predictive indices for candidemia in an adult intensive care unit (ICU) and to propose a new index. METHODS: A prospective cohort study was conducted between January 2011 and December 2012. This study was performed in an ICU in a tertiary care hospital at a public university and included 114 patients staying in the adult ICU for at least 48 hours. The association of patient variables with candidemia was analyzed. RESULTS: There were 18 (15.8%) proven cases of candidemia and 96 (84.2%) cases without candidemia. Univariate analysis revealed the following risk factors: parenteral nutrition, severe sepsis, surgical procedure, dialysis, pancreatitis, acute renal failure, and an APACHE II score higher than 20. For the Candida score index, the odds ratio was 8.50 (95% CI, 2.57 to 28.09); the sensitivity, specificity, positive predictive value, and negative predictive value were 0.78, 0.71, 0.33, and 0.94, respectively. With respect to the clinical predictor index, the odds ratio was 9.45 (95%CI, 2.06 to 43.39); the sensitivity, specificity, positive predictive value, and negative predictive value were 0.89, 0.54, 0.27, and 0.96, respectively. The proposed candidemia index cutoff was 8.5; the sensitivity, specificity, positive predictive value, and negative predictive value were 0.77, 0.70, 0.33, and 0.94, respectively. CONCLUSIONS: The Candida score and clinical predictor index excluded candidemia satisfactorily. The effectiveness of the candidemia index was comparable to that of the Candida score.

Characterization of newborns with nonimmune hydrops fetalis admitted to a neonatal intensive care unit

PURPOSE: To determine the incidence and characteristics of nonimmune hydrops fetalis in the newborn population. METHOD: A retrospective study of the period between 1996 and 2000, including all newborns with a prenatal or early neonatal diagnosis of nonimmune hydrops fetalis, based on clinical history, physical examination, and laboratory evaluation. The following were analyzed: prenatal follow-up, delivery type, gender, birth weight, gestational age, presence of perinatal asphyxia, nutritional classification, etiopathic diagnosis, length of hospital stay, mortality, and age at death. RESULTS: A total of 47 newborns with hydrops fetalis (0.42% of live births), 18 (38.3%) with the immune form and 29 (61.7%) with the nonimmune form, were selected for study. The incidence of nonimmune hydrops fetalis was 1 per 414 neonates. Data was obtained from 21 newborns, with the following characteristics: 19 (90.5%) were suspected from prenatal diagnosis, 18 (85.7%) were born by cesarean delivery, 15 (71.4%) were female, and 10 (47.6%) were asphyxiated. The average weight was 2665.9 g, and the average gestational age was 35 3/7 weeks; 14 (66.6%) were preterm; 18 (85.0 %) appropriate delivery time; and 3 (14.3%) were large for gestational age. The etiopathic diagnosis was determined for 62%, which included cardiovascular (19.0%), infectious (9.5%), placental (4.8%), hematologic (4.7%), genitourinary (4.8%), and tumoral causes (4.8%), and there was a combination of causes in 9.5%. The etiology was classified as idiopathic in 38%. The length of hospital stay was 26.6 ± 23.6 days, and the mortality rate was 52.4%. CONCLUSIONS: The establishment of a suitable etiopathic diagnosis associated with prenatal detection of nonimmune hydrops fetalis can be an important step in reducing the neonatal mortality rate from this condition.

Prevalence rates of infection in intensive care units of a tertiary teaching hospital

OBJECTIVE: To determine the prevalence rates of infections among intensive care unit patients, the predominant infecting organisms, and their resistance patterns. To identify the related factors for intensive care unit-acquired infection and mortality rates. DESIGN: A 1-day point-prevalence study. SETTING:A total of 19 intensive care units at the Hospital das Clínicas - University of São Paulo, School of Medicine (HC-FMUSP), a teaching and tertiary hospital, were eligible to participate in the study. PATIENTS: All patients over 16 years old occupying an intensive care unit bed over a 24-hour period. The 19 intensive care unit s provided 126 patient case reports. MAIN OUTCOME MEASURES: Rates of infection, antimicrobial use, microbiological isolates resistance patterns, potential related factors for intensive care unit-acquired infection, and death rates. RESULTS: A total of 126 patients were studied. Eighty-seven patients (69%) received antimicrobials on the day of study, 72 (57%) for treatment, and 15 (12%) for prophylaxis. Community-acquired infection occurred in 15 patients (20.8%), non- intensive care unit nosocomial infection in 24 (33.3%), and intensive care unit-acquired infection in 22 patients (30.6%). Eleven patients (15.3%) had no defined type. The most frequently reported infections were respiratory (58.5%). The most frequently isolated bacteria were Enterobacteriaceae (33.8%), Pseudomonas aeruginosa (26.4%), and Staphylococcus aureus (16.9%; [100% resistant to methicillin]). Multivariate regression analysis revealed 3 risk factors for intensive care unit-acquired infection: age > 60 years (p = 0.007), use of a nasogastric tube (p = 0.017), and postoperative status (p = 0.017). At the end of 4 weeks, overall mortality was 28.8%. Patients with infection had a mortality rate of 34.7%. There was no difference between mortality rates for infected and noninfected patients (p=0.088). CONCLUSION: The rate of nosocomial infection is high in intensive care unit patients, especially for respiratory infections. The predominant bacteria were Enterobacteriaceae, Pseudomonas aeruginosa, and Staphylococcus aureus (resistant organisms). Factors such as nasogastric intubation, postoperative status, and age ³60 years were significantly associated with infection. This study documents the clinical impression that prevalence rates of intensive care unit-acquired infections are high and suggests that preventive measures are important for reducing the occurrence of infection in critically ill patients.

Ethical aspects in the management of the terminally ill patient in the pediatric intensive care unit

OBJECTIVE: To identify the prevalence of management plans and decision-making processes for terminal care patients in pediatric intensive care units. METHODOLOGY: Evidence-based medicine was done by a systematic review using an electronic data base (LILACS, 1982 through 2000) and (MEDLINE, 1966 through 2000). The key words used are listed and age limits (0 to 18 years) were used. RESULTS: One hundred and eighty two articles were found and after selection according to the exclusion/inclusion criteria and objectives 17 relevant papers were identified. The most common decisions found were do-not-resuscitation orders and withdrawal or withholding life support care. The justifications for these were "imminent death" and "unsatisfatory quality of life". CONCLUSION: Care management was based on ethical principles aiming at improving benefits, avoiding harm, and when possible, respecting the autonomy of the terminally ill patient.

Predicting plateau pressure in intensive medicine for ventilated patients

Barotrauma is identified as one of the leading diseases in Ventilated Patients. This type of problem is most common in the Intensive Care Units. In order to prevent this problem the use of Data Mining (DM) can be useful for predicting their occurrence. The main goal is to predict the occurence of Barotrauma in order to support the health professionals taking necessary precautions. In a first step intensivists identified the Plateau Pressure values as a possible cause of Barotrauma. Through this study DM models (classification) where induced for predicting the Plateau Pressure class (>=30 cm

Step towards a patient timeline in intensive care units

In Intensive Medicine, the presentation of medical information is done in many ways, depending on the type of data collected and stored. The way in which the information is presented can make it difficult for intensivists to quickly understand the patient's condition. When there is the need to cross between several types of clinical data sources the situation is even worse. This research seeks to explore a new way of presenting information about patients, based on the timeframe in which events occur. By developing an interactive Patient Timeline, intensivists will have access to a new environment in real-time where they can consult the patient clinical history and the data collected until the moment. The medical history will be available from the moment in which patients is admitted in the ICU until discharge, allowing intensivist to examine data regarding vital signs, medication, exams, among others. This timeline also intends to, through the use of information and models produced by the INTCare system, combine several clinical data in order to help diagnose the future patients’ conditions. This platform will help intensivists to make more accurate decision. This paper presents the first approach of the solution designed

Intelligent decision support to predict patient barotrauma risk in intensive care units

The occurrence of Barotrauma is identified as a major concern for health professionals, since it can be fatal for patients. In order to support the decision process and to predict the risk of occurring barotrauma Data Mining models were induced. Based on this principle, the present study addresses the Data Mining process aiming to provide hourly probability of a patient has Barotrauma. The process of discovering implicit knowledge in data collected from Intensive Care Units patientswas achieved through the standard process Cross Industry Standard Process for Data Mining. With the goal of making predictions according to the classification approach they several DM techniques were selected: Decision Trees, Naive Bayes and Support Vector Machine. The study was focused on identifying the validity and viability to predict a composite variable. To predict the Barotrauma two classes were created: “risk” and “no risk”. Such target come from combining two variables: Plateau Pressure and PCO2. The best models presented a sensitivity between 96.19% and 100%. In terms of accuracy the values varied between 87.5% and 100%. This study and the achieved results demonstrated the feasibility of predicting the risk of a patient having Barotrauma by presenting the probability associated.

Pervasive patient timeline for intensive care units

This research work explores a new way of presenting and representing information about patients in critical care, which is the use of a timeline to display information. This is accomplished with the development of an interactive Pervasive Patient Timeline able to give to the intensivists an access in real-time to an environment containing patients clinical information from the moment in which the patients are admitted in the Intensive Care Unit (ICU) until their discharge This solution allows the intensivists to analyse data regarding vital signs, medication, exams, data mining predictions, among others. Due to the pervasive features, intensivists can have access to the timeline anywhere and anytime, allowing them to make decisions when they need to be made. This platform is patient-centred and is prepared to support the decision process allowing the intensivists to provide better care to patients due the inclusion of clinical forecasts.

Optimization techniques to detect early ventilation extubation in intensive care units

The decision support models in intensive care units are developed to support medical staff in their decision making process. However, the optimization of these models is particularly difficult to apply due to dynamic, complex and multidisciplinary nature. Thus, there is a constant research and development of new algorithms capable of extracting knowledge from large volumes of data, in order to obtain better predictive results than the current algorithms. To test the optimization techniques a case study with real data provided by INTCare project was explored. This data is concerning to extubation cases. In this dataset, several models like Evolutionary Fuzzy Rule Learning, Lazy Learning, Decision Trees and many others were analysed in order to detect early extubation. The hydrids Decision Trees Genetic Algorithm, Supervised Classifier System and KNNAdaptive obtained the most accurate rate 93.2%, 93.1%, 92.97% respectively, thus showing their feasibility to work in a real environment.

Real-Time decision support using data mining to predict blood pressure critical events in intensive medicine patients

Patient blood pressure is an important vital signal to the physicians take a decision and to better understand the patient condition. In Intensive Care Units is possible monitoring the blood pressure due the fact of the patient being in continuous monitoring through bedside monitors and the use of sensors. The intensivist only have access to vital signs values when they look to the monitor or consult the values hourly collected. Most important is the sequence of the values collected, i.e., a set of highest or lowest values can signify a critical event and bring future complications to a patient as is Hypotension or Hypertension. This complications can leverage a set of dangerous diseases and side-effects. The main goal of this work is to predict the probability of a patient has a blood pressure critical event in the next hours by combining a set of patient data collected in real-time and using Data Mining classification techniques. As output the models indicate the probability (%) of a patient has a Blood Pressure Critical Event in the next hour. The achieved results showed to be very promising, presenting sensitivity around of 95%.

Retrospective Study of the Survival of Patients who Underwent Cardiopulmonary Resuscitation in an Intensive Care Unit

OBJECTIVE: To evaluate clinical and evolutive characteristics of patients admitted in an intensive care unit after cardiopulmonary resuscitation, identifying prognostic survival factors.METHODS: A retrospective study of 136 patients admitted between 1995 and 1999 to an intensive care unit, evaluating clinical conditions, mechanisms and causes of cardiopulmonary arrest, and their relation to hospital mortality.RESULTS: A 76% mortality rate independent of age and sex was observed. Asystole was the most frequent mechanism of death, and seen in isolation pulmonary arrest was the least frequent. Cardiac failure, need for mechanical ventilation, cirrhosis and previous stroke were clinically significant (p<0.01) death factors.CONCLUSION: Prognostic factors supplement the doctor's decision as to whether or not a patient will benefit from cardiopulmonary resuscitation.

Detección de circovirus pocino tipo II en cerdos que presentan diarrea en criaderos intensivos. Detection of porcine circovirus type II in pigs that present diarrhea in intensive hatcheries.

Se propone detectar la presencia del agente etiológico circovirus porcino (CVP) en cerdos con diarrea. El cual se considera un patógeno emergente importante asociado a diferentes sindromes y enfermedades porcinas. Se comunicó a nivel internacional en 1997 y en Argentina fue descripto en el 2003 en animales de cria extensiva, aunque se encuentra en los diferentes sistemas de producción. Su presencia causa grandes pérdidas económicas, ya que muchas veces no tiene una sintomatología clínica, sino que se manifiesta subclinicamente. En la provincia de Córdoba no se han realizado estudios sistemáticos para determinar la presencia de circovirus. Además, en animales que presentan diarrea no se ha realizado un relevamiento de la presencia del CVP y su asociación con el cuadro clínico. Diversos investigadores estan viendo la necesidad de incluir al CVP a la hora de pensar en los diagnósticos etiológicos, en aquellos que no solo presentan índices productivos ineficientes sino también que no responden a la terapia antimicrobiana. Es agente causal del Sindrome de Desmedro Posdestete y podria favorecer la acción de otros agentes patógenos que actuarían tanto en Sistema Respirastorio como en Sistema Digestivo. La complejidad del trabajo radica en demostrar lo antes mencionado a traves de las lesiones a observar en los tejidos y la determinación de la presencia del agente. La ejecución de este estudio sería un importante aporte a la producción porcina, en donde este agente produce importantes pérdidas económicas. La metodología, así como los resultados obtenidos serán útiles en la formación de recursos humanos aplicados a la investigación y transferidos directamente a la docencia. Hipotesis: Establecer la presencia del CVP en cerdos con signos clinicos de enteropatías Objetivos: Determinar en cortes histopatológicos de intestino y ganglio mesentério, lesiones compatibles con CVP; Determinar por inmunohistoquímica la presencia del antígeno CVP en las muestras. Identificar las células en las que se encuentre el antígeno. Materiales y método: Muestreo a campo y toma de muestra. En diferentes establecimientos porcinos, de aquellos animales que presenten el cuadro clínico de diarrea, serán elegidos 3 animales aleatoriamente para sacrificio y realización de la técnica de necropsia. Se tomarán muestras de intestino delgado y ganglio mesentérico que serán fijadas en formol; la técnica histopatológica y su lectura tendrán fin de encontrar lesiones compatibles con circovirus porcino tipo II; Realización de la técnica de inmunohistoquímica con anticuerpo monoclonal, para la detección del CVP en los tejidos; Interpretación de resultados; Publicación de los resultados.

Impact of Intensive Physiotherapy on Cognitive Function after Coronary Artery Bypass Graft Surgery

Background: Coronary artery bypass graft (CABG) is a standard surgical option for patients with diffuse and significant arterial plaque. This procedure, however, is not free of postoperative complications, especially pulmonary and cognitive disorders. Objective: This study aimed at comparing the impact of two different physiotherapy treatment approaches on pulmonary and cognitive function of patients undergoing CABG. Methods: Neuropsychological and pulmonary function tests were applied, prior to and following CABG, to 39 patients randomized into two groups as follows: Group 1 (control) - 20 patients underwent one physiotherapy session daily; and Group 2 (intensive physiotherapy) - 19 patients underwent three physiotherapy sessions daily during the recovery phase at the hospital. Non-paired and paired Student t tests were used to compare continuous variables. Variables without normal distribution were compared between groups by using Mann-Whitney test, and, within the same group at different times, by using Wilcoxon test. The chi-square test assessed differences of categorical variables. Statistical tests with a p value ≤ 0.05 were considered significant. Results: Changes in pulmonary function were not significantly different between the groups. However, while Group 2 patients showed no decline in their neurocognitive function, Group 1 patients showed a decline in their cognitive functions (P ≤ 0.01). Conclusion: Those results highlight the importance of physiotherapy after CABG and support the implementation of multiple sessions per day, providing patients with better psychosocial conditions and less morbidity.

Minimal-invasive provenance integration into data-intensive systems

Magdeburg, Univ., Fak. für Informatik, Diss., 2014

Hilltop terrace sites of Oaxaca, Mexico : intensive surface survey at Guirâun, El Palmillo and the Mitla Fortress / Gary M. Feinman and Linda M. Nicholas.

n.s. no.37(2004)