scholarly journals STUDY OF INTRAABDOMINAL PRESSURE IN ACUTE PANCREATITIS AND ITS CORRELATION WITH DISEASE SEVERITY

2021 ◽  
pp. 1-3
Author(s):  
Nithin K B ◽  
Kaushalendra Kumar ◽  
B J Sharath Chandra
Keyword(s):  
Acute Pancreatitis ◽  
Correlation Coefficient ◽  
Linear Correlation ◽  
Pearson Correlation ◽  
Scoring Systems ◽  
Intraabdominal Pressure ◽  
Apache Ii Score ◽  
Abdominal Pressure ◽  
Pearson Correlation Coefficient ◽  
Positive Linear Correlation

INTRODUCTION: Acute pancreatitis is one of the commonly encountered surgical conditions in the emergency department. Prognostication is done by various biochemical assays and scoring systems. Intra abdominal pressure (IAP) measurement has strong potential use as a prognostication and interventional marker. In this study we aim to determine the association between the intra abdominal pressures and the severity, morbidity, mortality and the prognosis of the patient. METHODS: This study is prospective observational study. 100 patients diagnosed with acute pancreatitis were observed from the day of admission and followed up to the day of discharge. Intra abdominal pressure to be measured by the intravesical method.. RESULTS : There was significant linear correlation between raised intra abdominal pressure (IAP) and duration of hospitalization. In groups of patients who suffered complications, IAP was noted to be significantly higher, compared to the group of patients with no complications. (p <0.0001)There was a significant correlation of the baseline IAP (IAP at admission) with the MCTSI (pearson correlation coefficient = 0.534), APACHE II score (Pearson correlation coefficient = 0.511). IAP also showed positive linear correlation with ranson score (Pearson correlation coefficient = 0.383) CONCLUSION: IAP measurement is cheap, easy, and minimally invasive modality. It can be easily measured in catheterized patients. It is faster and easier than the existing scoring modalities and can reliably predict hospital stay, complications, and the prognosis in acute pancreatitis.

scholarly journals Modified Pearson Correlation Coefficient for Two-color Imaging in Spherocylindrical Cells

2018 ◽  
Author(s):  
Sonisilpa Mohapatra ◽  
James C. Weisshaar
Keyword(s):  
Correlation Coefficient ◽  
Linear Correlation ◽  
Pearson Correlation ◽  
Three Dimensional ◽  
Mean Value ◽  
Pearson Correlation Coefficient ◽  
Bacterial Cells ◽  
Cell Geometry ◽  
Cell Shapes ◽  
Special Case

AbstractThe revolution in fluorescence microscopy enables sub-diffraction-limit (“superresolution”) localization of hundreds or thousands of copies of two differently labeled proteins in the same live cell. In typical experiments, fluorescence from the entire three-dimensional (3D) cell body is projected along the z-axis of the microscope to form a 2D image at the camera plane. For imaging of two different species, here denoted “red” and “green”, a significant biological question is the extent to which the red and green spatial distributions are positively correlated, anti-correlated, or uncorrelated. A commonly used statistic for assessing the degree of linear correlation between two image matrices R and G is the Pearson Correlation Coefficient (PCC). PCC should vary from –1 (perfect anti-correlation) to 0 (no linear correlation) to +1 (perfect positive correlation). However, in the special case of spherocylindrical bacterial cells such as E. coli or B. subtilis, we show that the PCC fails both qualitatively and quantitatively. PCC returns the same +1 value for 2D projections of distributions that are either perfectly correlated in 3D or completely uncorrelated in 3D. The PCC also systematically underestimates the degree of anti-correlation between the projections of two perfectly anti-correlated 3D distributions. The problem is that the projection of a random spatial distribution within the 3D spherocylinder is non-random in 2D, whereas PCC compares every matrix element of R or G with the constant mean value R or G. We propose a modified Pearson Correlation Coefficient (MPCC) that corrects this problem for spherocylindrical cell geometry by using the proper reference matrix for comparison with R and G. Correct behavior of MPCC is confirmed for a variety of numerical simulations and on experimental distributions of HU and RNA polymerase in live E. coli cells. The MPCC concept should be generalizable to other cell shapes.

Relationship between Invasive and Non-Invasive Hemodynamic Measures in Experimental Pulmonary Hypertension

2020 ◽  
Vol 16 (1) ◽  
pp. 47-53
Author(s):  
Vicente Benavides-Córdoba ◽  
Mauricio Palacios Gómez
Keyword(s):  
Heart Rate ◽  
Pulmonary Hypertension ◽  
Ejection Fraction ◽  
Right Ventricle ◽  
Correlation Coefficient ◽  
Pearson Correlation ◽  
Systolic Pressure ◽  
Control Group ◽  
Pearson Correlation Coefficient ◽  
Non Invasive

Introduction: Animal models have been used to understand the pathophysiology of pulmonary hypertension, to describe the mechanisms of action and to evaluate promising active ingredients. The monocrotaline-induced pulmonary hypertension model is the most used animal model. In this model, invasive and non-invasive hemodynamic variables that resemble human measurements have been used. Aim: To define if non-invasive variables can predict hemodynamic measures in the monocrotaline-induced pulmonary hypertension model. Materials and Methods: Twenty 6-week old male Wistar rats weighing between 250-300g from the bioterium of the Universidad del Valle (Cali - Colombia) were used in order to establish that the relationships between invasive and non-invasive variables are sustained in different conditions (healthy, hypertrophy and treated). The animals were organized into three groups, a control group who was given 0.9% saline solution subcutaneously (sc), a group with pulmonary hypertension induced with a single subcutaneous dose of Monocrotaline 30 mg/kg, and a group with pulmonary hypertension with 30 mg/kg of monocrotaline treated with Sildenafil. Right ventricle ejection fraction, heart rate, right ventricle systolic pressure and the extent of hypertrophy were measured. The functional relation between any two variables was evaluated by the Pearson correlation coefficient. Results: It was found that all correlations were statistically significant (p <0.01). The strongest correlation was the inverse one between the RVEF and the Fulton index (r = -0.82). The Fulton index also had a strong correlation with the RVSP (r = 0.79). The Pearson correlation coefficient between the RVEF and the RVSP was -0.81, meaning that the higher the systolic pressure in the right ventricle, the lower the ejection fraction value. Heart rate was significantly correlated to the other three variables studied, although with relatively low correlation. Conclusion: The correlations obtained in this study indicate that the parameters evaluated in the research related to experimental pulmonary hypertension correlate adequately and that the measurements that are currently made are adequate and consistent with each other, that is, they have good predictive capacity.

scholarly journals Haemoconcentration as a predictor of severity in acute pancreatitis

2016 ◽  
Vol 4 (1) ◽  
pp. 3-7
Author(s):  
Tanka Prasad Bohara ◽  
Dimindra Karki ◽  
Anuj Parajuli ◽  
Shail Rupakheti ◽  
Mukund Raj Joshi
Keyword(s):  
Acute Pancreatitis ◽  
Pearson Correlation ◽  
Characteristic Curve ◽  
Scoring Systems ◽  
Cost Effective ◽  
Receiver Operator Characteristic Curve ◽  
First Episode ◽  
P Value ◽  
Receiver Operator Characteristic ◽  
Chi Square

Background: Acute pancreatitis is usually a mild and self-limiting disease. About 25 % of patients have severe episode with mortality up to 30%. Early identification of these patients has potential advantages of aggressive treatment at intensive care unit or transfer to higher centre. Several scoring systems are available to predict severity of acute pancreatitis but are cumbersome, take 24 to 48 hours and are dependent on tests that are not universally available. Haematocrit has been used as a predictor of severity of acute pancreatitis but some have doubted its role.Objectives: To study the significance of haematocrit in prediction of severity of acute pancreatitis.Methods: Patients admitted with first episode of acute pancreatitis from February 2014 to July 2014 were included. Haematocrit at admission and 24 hours of admission were compared with severity of acute pancreatitis. Mean, analysis of variance, chi square, pearson correlation and receiver operator characteristic curve were used for statistical analysis.Results: Thirty one patients were included in the study with 16 (51.61%) male and 15 (48.4%) female. Haematocrit at 24 hours of admission was higher in severe acute pancreatitis (P value 0.003). Both haematocrit at admission and at 24 hours had positive correlation with severity of acute pancreatitis (r: 0.387; P value 0.031 and r: 0.584; P value 0.001) respectively.Area under receiver operator characteristic curve for haematocrit at admission and 24 hours were 0.713 (P value 0.175, 95% CI 0.536 - 0.889) and 0.917 (P value 0.008, 95% CI 0.813 – 1.00) respectively.Conclusion: Haematocrit is a simple, cost effective and widely available test and can predict severity of acute pancreatitis.Journal of Kathmandu Medical College, Vol. 4(1) 2015, 3-7

scholarly journals Bed-Based Ballistocardiography: Dataset and Ability to Track Cardiovascular Parameters

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 156
Author(s):  
Charles Carlson ◽  
Vanessa-Rose Turpin ◽  
Ahmad Suliman ◽  
Carl Ade ◽  
Steve Warren ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Stroke Volume ◽  
Systolic Blood Pressure ◽  
Correlation Coefficient ◽  
Pearson Correlation ◽  
Health Assessment ◽  
Initial Study ◽  
Pearson Correlation Coefficient ◽  
Medical Systems ◽  
Cardiovascular Parameters

Background: The goal of this work was to create a sharable dataset of heart-driven signals, including ballistocardiograms (BCGs) and time-aligned electrocardiograms (ECGs), photoplethysmograms (PPGs), and blood pressure waveforms. Methods: A custom, bed-based ballistocardiographic system is described in detail. Affiliated cardiopulmonary signals are acquired using a GE Datex CardioCap 5 patient monitor (which collects ECG and PPG data) and a Finapres Medical Systems Finometer PRO (which provides continuous reconstructed brachial artery pressure waveforms and derived cardiovascular parameters). Results: Data were collected from 40 participants, 4 of whom had been or were currently diagnosed with a heart condition at the time they enrolled in the study. An investigation revealed that features extracted from a BCG could be used to track changes in systolic blood pressure (Pearson correlation coefficient of 0.54 +/− 0.15), dP/dtmax (Pearson correlation coefficient of 0.51 +/− 0.18), and stroke volume (Pearson correlation coefficient of 0.54 +/− 0.17). Conclusion: A collection of synchronized, heart-driven signals, including BCGs, ECGs, PPGs, and blood pressure waveforms, was acquired and made publicly available. An initial study indicated that bed-based ballistocardiography can be used to track beat-to-beat changes in systolic blood pressure and stroke volume. Significance: To the best of the authors’ knowledge, no other database that includes time-aligned ECG, PPG, BCG, and continuous blood pressure data is available to the public. This dataset could be used by other researchers for algorithm testing and development in this fast-growing field of health assessment, without requiring these individuals to invest considerable time and resources into hardware development and data collection.

scholarly journals Assessment of the Dissimilarities of EDI and SPI Measures for Drought Determination in South Africa

Water ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 82
Author(s):  
Omolola M. Adisa ◽  
Muthoni Masinde ◽  
Joel O. Botai
Keyword(s):  
South Africa ◽  
South African ◽  
Correlation Coefficient ◽  
Pearson Correlation ◽  
Standardized Precipitation Index ◽  
Drought Monitoring ◽  
Drought Indices ◽  
Drought Severity ◽  
Pearson Correlation Coefficient ◽  
Drought Duration

This study examines the (dis)similarity of two commonly used indices Standardized Precipitation Index (SPI) computed over accumulation periods 1-month, 3-month, 6-month, and 12-month (hereafter SPI-1, SPI-3, SPI-6, and SPI-12, respectively) and Effective Drought Index (EDI). The analysis is based on two drought monitoring indicators (derived from SPI and EDI), namely, the Drought Duration (DD) and Drought Severity (DS) across the 93 South African Weather Service’s delineated rainfall districts over South Africa from 1980 to 2019. In the study, the Pearson correlation coefficient dissimilarity and periodogram dissimilarity estimates were used. The results indicate a positive correlation for the Pearson correlation coefficient dissimilarity and a positive value for periodogram of dissimilarity in both the DD and DS. With the Pearson correlation coefficient dissimilarity, the study demonstrates that the values of the SPI-1/EDI pair and the SPI-3/EDI pair exhibit the highest similar values for DD, while the SPI-6/EDI pair shows the highest similar values for DS. Moreover, dissimilarities are more obvious in SPI-12/EDI pair for DD and DS. When a periodogram of dissimilarity is used, the values of the SPI-1/EDI pair and SPI-6/EDI pair exhibit the highest similar values for DD, while SPI-1/EDI displayed the highest similar values for DS. Overall, the two measures show that the highest similarity is obtained in the SPI-1/EDI pair for DS. The results obtainable in this study contribute towards an in-depth knowledge of deviation between the EDI and SPI values for South Africa, depicting that these two drought indices values are replaceable in some rainfall districts of South Africa for drought monitoring and prediction, and this is a step towards the selection of the appropriate drought indices.

Should CD138 Immunohistochemistry be Standard Recommended Practice for Bone Marrow Evaluation of Plasma Cell Neoplasms?

2020 ◽  
Vol 154 (Supplement_1) ◽  
pp. S110-S110
Author(s):  
A Vijayanarayanan ◽  
K Inamdar ◽  
M Menon ◽  
P Kuriakose
Keyword(s):  
Bone Marrow ◽  
Plasma Cell ◽  
Linear Correlation ◽  
Plasma Cells ◽  
Pearson Correlation ◽  
Protein Electrophoresis ◽  
Pearson Correlation Coefficient ◽  
Cell Percentage ◽  
Significant Linear Correlation ◽  
Plasma Cell Neoplasms

Abstract Introduction/Objective Myeloma diagnosis by a pathologist requires 10% plasma cells (PC) or a biopsy proven plasmacytoma in addition to myeloma defining events. PC% &gt; 60% is a biomarker of malignancy under this definition. WHO allows for assesment of plasma cell percentage either by aspirate count or by CD138 immunohistochemistry (IHC). There is lack of consensus on aspirate smear adequacy for PC% estimation. Uneven distribution of plasma cells, hemodilution and/or patchy infiltration can lead to gross underestimation. We compared PC% by aspirate count and CD138 IHC and established corelation with serum protein electrophoresis (SPEP) values. Methods 67 myeloma cases were included after excluding cases with suboptimal or inadequate aspirate smears. Two hematopathologists evaluated the diagnostic marrow (therapy naive) for PC% by aspirate count and CD138 IHC on biopsy/clot section. Corresponding SPEP and Free light chain (FLC) values were obtained. Correlation coefficent was calculated using Pearson correlation coefficient (GraphPad Prism). Results The Ig subtypes included IgG (41/67) and IgA (17/67). 12 cases had available FLC values. Both average and median PC% by CD138 IHC was considerably higher (50%, 52%) compared to aspirate count (29%, 21%). However, PC% by aspirate smear count and CD138 IHC demonstrated a significant linear correlation (r=0.71, p60% by CD138 (and not by aspirate count). Conclusion CD138 IHC based PC% is consistently higher, nevertheless, statistically significant linear corelation is observed between aspirate count PC% and CD138 IHC. A significant linear correlation is observed between CD138 IHC and SPEP (IgG and IgA), however, no such correlation is observed with aspirate count. More cases were diagnosed as myeloma (11%) and higher propotion of cases (35%) had biomarker of malignancy i.e. PC% &gt;60% by CD138 IHC. Based on these findings, we propose estimation of PC% by CD138 immunostain be a recommended standard practice for better clinicopathologic and biologic correlation.

Use of Multiple Visits to Increase Blood Pressure Tracking Correlations in Childhood

PEDIATRICS ◽  
1991 ◽  
Vol 87 (5) ◽  
pp. 708-711
Author(s):  
Matthew W. Gillman ◽  
Bernard Rosner ◽  
Denis A. Evans ◽  
Laurel A. Smith ◽  
James O. Taylor ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Diastolic Blood Pressure ◽  
Correlation Coefficient ◽  
Diastolic Pressure ◽  
Pearson Correlation ◽  
Systolic Pressure ◽  
Pearson Correlation Coefficient ◽  
Increase Blood Pressure ◽  
Multiple Visit

Previous studies of childhood blood pressure have shown tracking correlations, which estimate the magnitude of association between initial and subsequent measurements, to be lower than corresponding adult values. Inasmuch as this disparity could arise from failing to account for a larger week-to-week variability in children, blood pressure was measured for 4 successive years, on four weekly visits in each year, and with three measurements at each visit, using a random-zero sphygmomanometer, in a cohort of 333 schoolchildren aged 8 through 15 at entry. Ninety percent of subjects had measurements in 1 or more years of follow-up. For all follow-up periods (1, 2, and 3 years from baseline), the Pearson correlation coefficient (r) for both systolic and diastolic blood pressure rose substantially with the number of weekly visits used to calculate each subject's yearly blood pressure (P &lt; .0001). For systolic pressure, the 3-year r values for 1, 2, 3, and 4 visits were .45, .55, .64, and .69, respectively. For diastolic pressure (Korotkoff phase 4), the corresponding values were .28, .41, .47, and .54. These higher multiple-visit estimates of tracking approximate published adult values and raise the possibility that prediction of adult blood pressure from childhood measurements may be improved by averaging readings from multiple weekly visits.

Algorithm for Eliminating Mismatched Points Based on Pearson Correlation Coefficient

2021 ◽  
Vol 58 (8) ◽  
pp. 0810025
Author(s):  
李硕 Li Shuo ◽  
韩迎东 Han Yingdong ◽  
王双 Wang Shuang ◽  
刘琨 Liu Kun ◽  
江俊峰 Jiang Junfeng ◽  
...  
Keyword(s):  
Correlation Coefficient ◽  
Pearson Correlation ◽  
Pearson Correlation Coefficient
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