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Background: Aim of this study is to examine the efficacy of Physiological and operative severity score for the enumeration of mortality and morbidity (POSSUM) and Portsmouth predictor modification (P-POSSUM) equations in predicting morbidity and mortality in patients undergoing emergency laparotomy, to study the morbidity and mortality patterns in patients undergoing emergency laparotomy at Malla Reddy Institute of Medical Sciences, Hyderabad. Methods: The study was conducted for a period of 2 years from February 2018 to February 2020. 100 Patients undergoing emergency laparotomy were studied in the Department of General surgery MRIMS, Hyderabad. POSSUM and P-POSSUM scores are used to predict mortality and morbidity. The ratio of observed to expected deaths (O:E ratio) was calculated for each analysis. Results: The study included total 100 patients, 83 men and 17 women. Observed mortality rate was compared to mortality rate with POSSUM, the O:E ratio was 0.62, and there was no significant difference between the observed and predicted values (χ²=10.79, 9 degree of freedom (df) p=0.148). Observed morbidity rates were compared to morbidity rates predicted by POSSUM, there was no significant difference between the observed and predicted values (χ²=9.89, 9 df, p=0.195) and the overall O:E ratio was 0.91. P-POSSUM predicted mortality equally well when the linear method of analysis was used, with an O:E ratio of 0.65 and no significant difference between the observed and predicted values (χ²= 5.33, 9 df, p= 0.617).Conclusion: POSSUM and P-POSSUM scoring is an accurate predictor of mortality and morbidity following emergency laparotomy and is a valid means of assessing adequacy of care provided to the patient.
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Objective: Based on the same clinical laboratory automatic blood coagulation analyzer method comparison of different brands. Discuss different between blood coagulation analyzer test results are comparable or check whether the deviation of the results in the permitted range. Method:collecting 112 cases of fresh plasma specimens, using ACL ADVANCE and Sysmex CA7000 two kinds of blood coagulation analyzer, respectively prothrombin time (PT), activated partial prothrombin time (APTT), thrombin time (TT) and fibrinogen (FIB), and compare the results, to medical decision level of judging system error detection system for clinical result, and calculate the two blood coagulation instrument testing results of the correlation coefficient and linear regression equation. Results:the ACL ADVANCE and Sysmex CA7000 blood coagulation analyzer test of PT, APTT, TT and FIB result comparison, there were no statistically significant difference (t=0.974, t=0.649, t=0.765, t=1.163;P>0.05), the correlation coefficient respectively;Medical decision level of system error were less than half the total margin of error. Conclusion:to the ACL ADVANCE as standard test system, Sysmex CA7000 determination results have clinical acceptability, two blood coagulation test results with good correlation. Should be conducted on a regular basis in the same laboratory coagulation analyzer compares different experiments, to ensure the comparability of the same in the laboratory test results.
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PURPOSE: Biological parameters can be quantified using dynamic PET data with compartment modeling and Nonlinear Least Square (NLS) estimation. However, the generation of parametric images using the NLS is not appropriate because of the initial value problem and excessive computation time. In irreversible model, Patlak graphical analysis (PGA) has been commonly used as an alternative to the NLS method. In PGA, however, the start time (t*, time where linear phase starts) has to be determined. In this study, we suggest a new Multiple Linear Analysis for irreversible radiotracer (MLAIR) to estimate fluoride bone influx rate (Ki). METHODS: [18F]Fluoride dynamic PET scans was acquired for 60 min in three normal mini-pigs. The plasma input curve was derived using blood sampling from the femoral artery. Tissue time-activity curves were measured by drawing region of interests (ROIs) on the femur head, vertebra, and muscle. Parametric images of Ki were generated using MLAIR and PGA methods. RESULT: In ROI analysis, estimated Ki values using MLAIR and PGA method was slightly higher than those of NLS, but the results of MLAIR and PGA were equivalent. Patlak slopes (Ki) were changed with different t* in low uptake region. Compared with PGA, the quality of parametric image was considerably improved using new method. CONCLUSION: The results showed that the MLAIR was efficient and robust method for the generation of Ki parametric image from [18F]Fluoride PET. It will be also a good alternative to PGA for the radiotracers with irreversible three compartment model.
Subject(s)
Femoral Artery , Femur Head , Fluorides , Plasma , Positron-Emission Tomography , SpineABSTRACT
@# Electroencephalogram non-linear analysis is one of the methods to study brain electric signal complexity and the mutual connection of signals based on the non-linearity principle and method. It can provide condition such as the neural networks function, contact information, the changing trajectory cerebrum function activity. It can be used for nerve spirit disease studying, the depth anaesthetize monitor ,the sleep studies in modern medicine, it breaks the ice in traditional Chinese medicine just now. The application of electroencephalogram non-linear analysis has open up an exhibition further to cerebrum's research.
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CADIA(Computer-assisted densitometric image analysis) method is used to analyze bone density changes around the implants. The usefullness and reproducibility of the method was assessed. We tried to find out if there is any possibility to quantitiate and qualitify peri-implant bone density change as time passes. And we concluded that this newly developed linear analysis is efficient for analyzing peri-implant bone density change non-invasively. In this study, 2152 machined Branemark fixtures installed from 1994 to 2002 in the department of Periodontics, Dental hospital of College of Dentistry, Yonsei University were included. Of these fixtures 22 radiographically analyzable failed fixtures were used as experimental group, and 22 successful implants placed in the same patient were used as control group. 1. 57 out of 1635 machined Branemark standard and Mk II implants system failed, the survival rate was 96.5%. And 11 out of 517 machined Branemark Mk III and Mk IV implants system failed, the survival rate was 97.9%. Total survival rate was 96.8%. 2. 22 failed implants were used for the analysis, 10 of which failed before prosthetic treatment due to infection and overheating. 12 failed due to overload after prosthetic treatment, 63.6% of which failed during the early phase of functional loading, i.e. before 1 year of loading. 3. Bone density change values around coronal region of the failed implants were -6.54 +/- 6.35, middle region were -3.53 +/- 5.78, apical region were -0.75 +/- 10.33, resulting in average of -3.71 +/- 8.03. 4. Bone density change values around coronal region of the successful implants were 4.25 +/- 4.66, middle region were 6.33 +/- 5.02, apical region were 9.89 +/-4.67, resulting in average of 6.27 +/- 5.29. 5. There was a statistically significant difference between two groups (p<0.01). In conclusion, the linear analysis method using computer-assisted densitometric image analysis could be a useful method for the analysis of implants, and could be used for future implant researchs.
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Humans , Bone Density , Dentistry , Periodontics , Survival RateABSTRACT
INTRODUCTION: Detrended fluctuation analysis (DFA) is used as a way of studying nonlinearity of EEG. In this study, DFA is applied on sleep EEG of normal subjects to look into its nonlinearity in terms of EEG channels and sleep stages. METHOD: Twelve healthy young subjects (age: 23.8+/-2.5 years old, male:female=7:5) have undergone nocturnal polysomnography (nPSG). EEG from nPSG was classified in terms of its channels and sleep stages and was analyzed by DFA. Scaling exponents (SEs) yielded by DFA were compared using linear mixed model analysis. RESULTS: Scaling exponents (SEs) of sleep EEG were distributed around 1 showing long term temporal correlation and self-similarity. SE of C3 channel was bigger than that of O1 channel. As sleep stage progressed from stage 1 to slow wave sleep, SE increased accordingly. SE of stage REM sleep did not show significant difference when compared with that of stage 1 sleep. CONCLUSION: SEs of Normal sleep EEG showed nonlinear characteristic with scale-free fluctuation, long-range temporal correlation, self-similarity and self-organized criticality. SE from DFA differentiated sleep stages and EEG channels. It can be a useful tool in the research with sleep EEG.
Subject(s)
Electroencephalography , Polysomnography , Sleep Stages , Sleep, REMABSTRACT
OBJECTIVE: The objective of this study is to estimate gestational age by using FHR parameters after linear and nonlinear analysis of FHR data. Linear spectral decomposition has a limit to describe and analyze the nonlinear and complex physiological nature. Random processing and chaotic analysis assist to quantify some patterned energies, interaction of the physiological system in body system, which the constancy is preserved, and complexity of physical cardiovascular system. But there are no great development of new device which notify fetal age. METHODS: From March 1995 to December 2000, 2,548 cases who received NST during antenatal visit were included in this study. Among these cases, 1000 cases were sampled randomly. We divided this cases into a study and a control group, 500 cases for model building set and the other 500 cases for validation set. Each FHR parameters such as baseline FHR, variability (AMP, MMR), acceleration & deceleration (15 bpm-15 seconds), loss of signal, the number of fetal movement were analysed by using our own computerized HYFM-I, II software system. The linear and non-linear analysis of FHR were done after extracting approximate entropy (ApEn) value. Finally, we performed regression analysis and extract an equation for estimation of gestational weeks using bootstrap method. RESULTS: We extract a following equation using above study method: Log(GA)=5.870-0.051(Sloss*)-0.065(Mean FHR*)+0.049(Mean FHR*)2-0.058(FM*)+0.048(AMP*)2+0.121(A1515*)-0.031(A1515*)2+0.036(ApEn*)2. CONCLUSIONS: Accurate dating of pregnancy, namely gestational week is very important for antenatal diagnosis in the field of perinatal medicine. This study will propose scientific research results which are useful for studying normal and morbid generating physiological fetal condition. We extract an appropriate equation for estimation of gestational weeks only using FHR parameters. We hope to compare our result with other authors' results in the near future.
Subject(s)
Female , Pregnancy , Acceleration , Cardiovascular System , Deceleration , Entropy , Fetal Heart , Fetal Movement , Gestational Age , Heart Rate, Fetal , Hope , Prenatal DiagnosisABSTRACT
OBJECTIVE: The objective of this study is to estimate gestational age by using FHR parameters after linear and nonlinear analysis of FHR data. Linear spectral decomposition has a limit to describe and analyze the nonlinear and complex physiological nature. Random processing and chaotic analysis assist to quantify some patterned energies, interaction of the physiological system in body system, which the constancy is preserved, and complexity of physical cardiovascular system. But there are no great development of new device which notify fetal age. METHODS: From March 1995 to December 2000, 2,548 cases who received NST during antenatal visit were included in this study. Among these cases, 1000 cases were sampled randomly. We divided this cases into a study and a control group, 500 cases for model building set and the other 500 cases for validation set. Each FHR parameters such as baseline FHR, variability (AMP, MMR), acceleration & deceleration (15 bpm-15 seconds), loss of signal, the number of fetal movement were analysed by using our own computerized HYFM-I, II software system. The linear and non-linear analysis of FHR were done after extracting approximate entropy (ApEn) value. Finally, we performed regression analysis and extract an equation for estimation of gestational weeks using bootstrap method. RESULTS: We extract a following equation using above study method: Log(GA)=5.870-0.051(Sloss*)-0.065(Mean FHR*)+0.049(Mean FHR*)2-0.058(FM*)+0.048(AMP*)2+0.121(A1515*)-0.031(A1515*)2+0.036(ApEn*)2. CONCLUSIONS: Accurate dating of pregnancy, namely gestational week is very important for antenatal diagnosis in the field of perinatal medicine. This study will propose scientific research results which are useful for studying normal and morbid generating physiological fetal condition. We extract an appropriate equation for estimation of gestational weeks only using FHR parameters. We hope to compare our result with other authors' results in the near future.
Subject(s)
Female , Pregnancy , Acceleration , Cardiovascular System , Deceleration , Entropy , Fetal Heart , Fetal Movement , Gestational Age , Heart Rate, Fetal , Hope , Prenatal DiagnosisABSTRACT
OBJECTIVES: In order to search for new parameters for the evaluation of the adequacy of electroconvulsive therapy (ECT) the authors performed a non-linear analysis of electroencepha-logram(EEG)recorded during the course of electroconvulsive therapy(ECT)in a single female patient with depression. METHODS: Digitized EEG recordings from two ECT sessions spaced one week were analyzed at five different stages; pretreatment stable, postanesthetic-preictal, ictal, postictal suppression and posttreatment stable stages. RESULTS: Our analysis showed that 1)EEG signals had low dimensional (below 10 dimensions) deterministic characteristics 2) although EEG was nonstationary signal, non-linear parameters could reliably differentiate between various stages we examined. 3)the deterministic property of ictal EEG increased according to the progression of sessions and 4)the primary Lyapunov exponent(PLE)and correlation dimension of pre- and post-treatment stable stage EEG increased according to the progression of sessions. CONCLUSION: In this single case study, results of various non-linear analyses suggested that non-linear variables extracted from EEG recordings during ECT may have utilities as tools for the quantitative evaluation of ECT.