1.A comparative study on the initial stability of different implants placed above the bone level using resonance frequency analysis.
In Ho KANG ; Chang Whe KIM ; Young Jun LIM ; Myung Joo KIM
The Journal of Advanced Prosthodontics 2011;3(4):190-195
PURPOSE: This study evaluated the initial stability of different implants placed above the bone level in different types of bone. MATERIALS AND METHODS: As described by Lekholm and Zarb, cortical layers of bovine bone specimens were trimmed to a thickness of 2 mm, 1 mm or totally removed to reproduce bone types II, III, and IV respectively. Three Implant system (Branemark System(R) Mk III TiUnite(TM), Straumann Standard Implant SLA(R), and Astra Tech Microthread(TM)-OsseoSpeed(TM)) were tested. Control group implants were placed in level with the bone, while test group implants were placed 1, 2, 3, and 4 mm above the bone level. Initial stability was evaluated by resonance frequency analysis. Data was statistically analyzed by one-way analysis of variance in confidence level of 95%. The effective implant length and the Implant Stability Quotient (ISQ) were compared using simple linear regression analysis. RESULTS: In the control group, there was a significant difference in the ISQ values of the 3 implants in bone types III and IV (P<.05). The ISQ values of each implant decreased with increased effective implant length in all types of bone. In type II bone, the decrease in ISQ value per 1-mm increase in effective implant length of the Branemark and Astra implants was less than that of the Straumann implant. In bone types III and IV, this value in the Astra implant was less than that in the other 2 implants. CONCLUSION: The initial stability was much affected by the implant design in bone types III, IV and the implant design such as the short pitch interval was beneficial to the initial stability of implants placed above the bone level.
Linear Models
2.Statistical notes for clinical researchers: simple linear regression 1 – basic concepts.
Restorative Dentistry & Endodontics 2018;43(2):e21-
No abstract available.
Linear Models*
3.Statistical notes for clinical researchers: simple linear regression 2 – evaluation of regression line.
Restorative Dentistry & Endodontics 2018;43(3):e34-
No abstract available.
Linear Models*
4.Statistical notes for clinical researchers: simple linear regression 3 – residual analysis
Restorative Dentistry & Endodontics 2019;44(1):e11-
No abstract available.
Linear Models
5.Effect of coloring agent on the color of zirconia.
Kwanghyun KIM ; Kwantae NOH ; Ahran PAE ; Yi Hyung WOO ; Hyeong Seob KIM
The Journal of Korean Academy of Prosthodontics 2017;55(1):18-25
PURPOSE: The aim of this study was to evaluate the effect of two types of coloring agents and the number of application on the color of zirconia. MATERIALS AND METHODS: Monolithic zirconia specimens (15.7 mm × 15.7 mm × 2.0 mm) (n = 33) was prepared and divided into 11 groups. Each experimental group was coded as a1-a5, w1-w5 according to the type of coloring agent and number of application. Specimens with no coloring agent applied were set as control group. The color difference of specimen was measured by using double-beam spectrophotometer, and calculated color difference (ΔE*(ab)), translucency parameter (TP). All data was analyzed with two-way ANOVA, multiple comparison Schéffe test, Pearson correlation and linear regression analysis. RESULTS: As the number of application increased, values of CIE L* was decreased, but values of CIE b* was increased in both coloring agents. However, there was no significant difference on values of translucency parameter. The color difference range of each group was 0.87 ΔE*(ab) to 9.43 ΔE*(ab). CONCLUSION: In this study, type of coloring agent and the number of application did not affect the color difference of zirconia.
Coloring Agents
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Linear Models
6.Overestimation of Vancomycin Clearance by the Linear Regression Formula in Rodvold's Report: Why?.
Infection and Chemotherapy 2014;46(1):62-63
No abstract available.
Linear Models*
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Vancomycin*
7.Analysis of binary classification repeated measurement data with GEE and GLMMs using SPSS software.
Shengli AN ; Yanhong ZHANG ; Zheng CHEN
Journal of Southern Medical University 2012;32(12):1777-1780
OBJECTIVETo analyze binary classification repeated measurement data with generalized estimating equations (GEE) and generalized linear mixed models (GLMMs) using SPSS19.0.
METHODSGEE and GLMMs models were tested using binary classification repeated measurement data sample using SPSS19.0.
RESULTS AND CONCLUSIONCompared with SAS, SPSS19.0 allowed convenient analysis of categorical repeated measurement data using GEE and GLMMs.
Linear Models ; Models, Statistical ; Software
8.Infrared thermographic analysis of temperature rise on the surface of buchanan plugger.
Sung A CHOI ; Sun Ho KIM ; Yun Chan HWANG ; Chang YOUN ; Byung Ju OH ; Bo Young CHOI ; Woo Nam JUHNG ; Sun Wa JEONG ; In Nam HWANG ; Won Mann OH
Journal of Korean Academy of Conservative Dentistry 2002;27(4):370-381
This study was performed to evaluate the temperature rise on various position of the Buchanan plugger, the peak temperature of plugger's type and the temperature change by its touching time of heat control spring. The heat carrier system 'System B'(Model 1005, Analytic Technologies, USA) and the Buchanan's pluggers of F, FM, M and ML sizes are used for this study. The temperature was set to 200degrees C which Dr. Buchanan's "continuous wave of condensation" technique recommended on digital display and the power level on it was set to 10. In order to apply heat on the Buchanan's pluggers, the heat control spring was touched for 1, 2, 3, 4 and 5 seconds respectively. The temperature rise on the surface of the pluggers were measured at 0.5 mm intervals from tip to 20 mm length of shank using the infrared thermography (Radiation Thermometer-IR Temper, NEC San-ei Instruments, Ltd, Japan) and TH31-702 Data capture software program (NEC San-ei Instruments, Ltd, Japan). Data were analyzed using a one way ANOVA followed by Duncan's multiple range test and linear regression test. The results as follows. 1. The position at which temperature peaked was approximately at 0.5 mm to 1.5 mm far from the tip of Buchanan's pluggers (p<0.001). The temperature was constantly decreased toward the shank from the tip of it (p<0.001). 2. When the pluggers were heated over 5 seconds, the peak temperature by time of measurement revealed from 253.3+/-10.5degrees C to 192.1+/-3.3degrees C in a touch for 1 sec, from 218.6+/-5.0degrees C to 179.5+/-4.2degrees C in a touch for 2 sec, from 197.5+/-3.0degrees C to 167.6+/-3.7degrees C in a touch for 3 sec, from 183.7+/-2.5degrees C to 159.8+/-3.6degrees C in a touch for 4 sec and from 164.9+/-2.0degrees C to 158.4+/-1.8degrees C in a touch for 5 sec. A touch for 1 sec showed the highest peak temperature, followed by, in descending order, 2 sec, 3 sec, 4 sec. A touch for 5 sec showed the lowest peak temperature (p<0.001). 3. A each type of pluggers showed different peak temperatures. The peak temperature was the highest in F type and followed by, in descending order, M type, ML type. FM type revealed the lowest peak temperature (p<0.001). The results of this study indicated that pluggers are designed to concentrate heat at around its tip, its actual temperature does not correlate well with the temperature which Buchanan's "continuous wave of condensation" technique recommend, and finally a quick touch of heat control spring for 1sec reveals the highest temperature rise.
Hot Temperature
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Linear Models
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Thermography
9.The Communication Styles and Nursing Service Satisfaction of Clinical Research Nurses Perceived by Clinical Subjects.
Journal of Korean Academic Society of Nursing Education 2016;22(4):559-566
PURPOSE: This study aimed to examine the communication styles and nursing service satisfaction of clinical research nurses perceived by clinical subjects. METHODS: The data were collected with self-administrated questionnaires after receiving consents from 200 clinical trial subjects. The data were analysed with descriptive statistics, t-test, ANOVA, Pearson's correlation coefficients and stepwise multiple regression analysis using SPSS 21.0 statistic program. RESULTS: Clinical subjects perceived that clinical research nurses used the informative, affective, and non-authoritative communication styles. The study identified factors influencing the nursing service satisfaction, and they were the informative communication styles (β=.34, p<.001) and affective communication styles (β=.35, p<.001, R2=37%) by multiple linear regression. CONCLUSION: If educational programs on communication are developed to help clinical research nurses use the informative and affective communication styles according to the characteristics of subjects and applied to the field of practice, they will be able to increase the nursing service satisfaction and contribute to the higher quality of clinical trials.
Linear Models
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Nursing Services*
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Nursing*
10.Development of a Poikilocyte Measuring Method Using Image Analysis Software.
Jong Moon CHOI ; Woong Soo LEE
Laboratory Medicine Online 2013;3(1):6-14
BACKGROUND: To achieve consistency in poikilocytes grading in peripheral blood cell examinations, we made an image-based differential count (IDC) software to measure the degree of abnormalities in individual red blood cells (RBCs) and relative fractions of poikilocytes. METHODS: Thirty peripheral blood samples were analyzed. Smear slides were examined on a microscope with charge-coupled device (CCD) camera. To verify this program, we compared the IDC results with the results of manual differential counting (MDC). Relative fractions of schistocytes, echinocytes, and elliptocytes were measured by IDC and MDC. The error rate of IDC was measured by confirming the final processed images of IDC. Correlations of IDC and MDC results were compared using linear regression analysis and the time required for each test was measured. For presentation of the mathematical decision criteria of poikilocytes, IDC algorithms for recognizing schistocytes, echinocytes, and elliptocytes were made using simple geometrical or mathematical formulas. RESULTS: The error rate of IDC was 2.8%. For analysis of 1,000 RBCs, MDC took 7.3 minutes and IDC took 2.7 minutes. Linear regression coefficients were 0.776 (P<0.001) for schistocytes, 0.895 (P<0.001) for echinocytes, and 1.001 (P<0.001) for elliptocytes. CONCLUSIONS: It was possible to define poikilocytes with geometrical or mathematical formulas using image analysis programs. The IDC program would be helpful for consistent grading of poikilocytes.
Blood Cells
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Erythrocytes
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Linear Models