Abstract— Traditionally total knee and hip arthroplasty surgeries requires long duartion of hospital stay. More duration of stay has its own disadvantages. So it was tried to developed an accelerated clinical pathway for patients undergoing total knee arthroplasty (TKA) and total hip arthroplasty (THA) who are considered healthy enough for early discharge. Between March 2013 – April2014, 89 TKA and 116 THA were performed to different patients at a single institution by a single orthopedic surgeon. 71 (31 TKA, 40 THA) met the inclusion criteria for the study. All patients received 2 grams of tranexamic acid and 750 mg cefuroxime sodium intravenously at 30 minutes prior to surgery. A multi-modal protocol for perioperative pain management was used for all patients. Out of total 71 patients (12 males, 59 females) with a mean age of 59 years (range, 24-79 years). The mean length of hospital stay was 27,3 hours (range, 15-60 hours). The mean duration of surgery was 92 minutes (range, 75-128 minutes) for TKA, 72 minutes (range, 48-81 minutes) for THA. Combined spinal epidural anesthesia was performed in 55 patients (77%) and general anesthesia in 16 patients (23%). Of the total 71 patients, 51 (71,8%) were discharged within 23 hours after surgery. Only 11(15.5%) were re-addmitted because of minor complains. These results of this study demonstrated that early discharge does not result in significant complications related to the outpatient procedure in selected patients up to three months postoperatively.
Keywords: Outpatient, Total Hip Arthroplasty, Total Knee Arthroplasty, Anesthesia.
Determination of patterns in the EEG signals during relaxation through music using Bayesian Networks
Abstract—Today it is known that the brain waves behave during relaxation through music, however, it is not yet known whether there is a pattern of dependencies between different EEG frequencies during those processes. Brain oscillations are often underestimated as compared to slower oscillations. Mean power spectra of scalp EEG signals exhibit distinct peaks emerging from the general decrease in power with increasing frequency, suggesting the existence of characteristic dependence oscillatory modes in cortical field potentials. The interactions between peaks in different frequency bands, within and between cortical EEG sources, are not well understood. The reviewed evidence supports the theory that relaxation through music can lead to behavioral and neuron chemical changes with benefic effects. This study was to address this concept by focusing on Bayesian Networks (BN) to describe the relationship between the EEG frequencies during relaxation through music. It was obtained a model with 97.7% to accuracy, in which shows the relations between each EEG signals. The dependency probability distribution was calculated, according to the signal amplitude behavior. Music changes the behavior of the low frequency signals, synchronizing them inversely proportional. Delta and theta interactions over Alpha promote increase Alpha 1 powers in relaxation through music. This event is accompanied by synchronized interaction of low-sequence signals, from Beta 1 to Gamma. Alpha 2 remains an independent variable. Further studies are needed to understand the differences between music and their subsequent effects on behavior. However, Bayesian Networks has been show to an excellent tool of EEG signal Analysis.
Key word: Bayesian Networks, Brain, Machine learning, Data mining.
Abstract- To estimate the variation in the major risk factors for cardiovascular disease (Hemoglobin HGB; mean corpuscular volume MCV; Mean corpuscular hemoglobin concentration MCHC; Fe and Folic acid), we try preventing according coronary heart disease risk factors observed in elderly men and women in the region of Setif – Algeria. Participants.100 men and women aged 26 to 86 years for whom the physiological parameters were recorded. These parameters are risk factors for cardiovascular disease. The expected analysis was estimated using an artificial intelligence model including the principles of fuzzy logic. Risk factors are inputs of the system and the incidence of coronary heart disease is output. The observed data recorded from Analysis Central Laboratory of Setif university hospital – Algeria. Factors that promote coronary heart disease are inaccurate and uncertain. The effect of these factors varies from person to person. Their consideration as fuzzy variables is perfectly adequate. A database is established. Fuzzy inference rules are highlighted according to the recorded values. An algorithmic application is established making it possible to read instantly the number likely the person with a coronary disease just by the random introduction of the variables at the input of the system.
Keywords: Coronary diseases, Risk factors, Artificial intelligence, Fuzzy logic.
Abstract—Empyema is an uncommon complication of childhood pneumonia. Although mortality rates in pediatric empyema are very low, empyema causes significant morbidity including substantial health care costs and burden of care. A descriptive observational study was conducted on 40 Empyema Thoracis in 0-12 years aged. Empyema was diagnosed as per “GOLDEN CRITERIA. Clinical profile including signs and symptoms was recorded with biosocial profile. Blood and Plural fluid examinations were also done. Microbiology and histo-pathological examinations were also done. Data collected were analysed, qualitative data were expressed in percentage and quantitative data were expressed in mean ± SD. Mean age of children was 5.01 years with slight female predominance (M:F = 2:3). Mean haemoglobine was 9.45 g/dl, Total leucocytes count (TLC) 17,293 with platelet counts 2.69 lakhs. PH of blood and plural fluid was 7.39 and 6.98 respectively. Cough was the most common complain (in 72%) followed by fever, breathlessness and chest pain. Likewise tackypnea was the most common sign elicited followed by pallor conjunctiva and cervical lymphadenopathy. On examination trachea was shifted either on right or left side in 52% cases, Creptations were observed in 72.5% of cases and Ronchi were observed in one (2.5%) case. Dullness on percussion, decrease air entry and decreased vocal resonance was observed in all the cases. Gram positive cocci and Gram negative bacilli were observed in 25% and 2.5% cases respectively. Out of these micro-organism, Streptococci, Staphylococci and Klebsela Pneumonae were found in 7.5%, 12.5% and 2.55 of cases respectively. Acute inflammation was found in 7.5%, chronic inflammation was found in 7% whereas Koch’s was found in 18% of cases in histology.
Key word: Children, Empyema Thoracis, Clinico-Etiological Profile.
Abstract— Polycystic ovary syndrome (PCOS) is the most common endocrine disorder in women. Evidences shows variable finding regarding it’s effect on pregnancy outcomes. This present study was conducted to determine whether maternal polycystic ovary syndrome (PCOS) is associated with adverse pregnancy outcomes in antenatal period. Prospective observational study, carried out in the department of Obstetrics and Gynecology, Indraprastha Apollo Hospitals, New Delhi, including 64 women with PCOS and 64 normal pregnant women between January 2013 and November 2014. It was found that Gestational diabetes mellitus (GDM) was significantly more frequent in the PCOS group than in the control group (p value = 0.009; OR=2.698 (1.213-6.001), this difference was not found statistically significant. Pregnancy induced hypertension (PIH) was also found significantly more frequent in the PCOS group than in the control group (p value=0.014; OR=3.41 (1.176-9.885). Miscarriage rate was not significantly different among two groups. So it can be concluded that women affected by PCOS carry an increased risk of adverse pregnancy outcomes specially GDM and PIH.
Key word: Polycystic ovary syndrome (PCOS), ANC Complications, GDM, PIH.
Abstract—Diabetes is a disease of development involving multisystem so intend to affect quality of life of patients in many ways i.e. Physical, Mental, Social and environmental. So this study was conducted on 250 Diabetes Mellitus patients to study their physical quality of life and its associating factors. It was found that 9.6% of diabetes patients had poor physical quality of life in this study. This physical quality of life is associated with education and socio-economic status of patient but not with age, sex and occupation. Physical quality of life was observed more poor in either illiterates or in secondary educated patients than their other counterparts. Likewise physical quality of life was observed more poor in Class III and IV than Class I, Class II and Class V.
Keywords— Diabetes Mellitus, Physical Quality of Life.