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Air Leakage
The Experts below are selected from a list of 321 Experts worldwide ranked by ideXlab platform
Walter Klepetko – One of the best experts on this subject based on the ideXlab platform.
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efficacy and safety of tachosil versus standard treatment of Air Leakage after pulmonary lobectomy
European Journal of Cardio-Thoracic Surgery, 2010Co-Authors: Gabriel Mihai Marta, Francesco Facciolo, Lars Ladegaard, Hendrik Dienemann, Attila Csekeo, Federico Rea, Sebastian Dango, Lorenzo Spaggiari, Vilhelm Tetens, Walter KlepetkoAbstract:Objectives:AlveolarAir Leakageremains a serious problemin lung surgery, beingassociatedwith increased postoperative morbidity, prolonged hospital stay and greater health-care costs. The aim of this study was to evaluate the sealing efficacy and safety of the surgical patch, TachoSil W , inlungsurgery.Methods:Patientsundergoingelectivepulmonarylobectomywhohad grade1 or 2Air Leakage(evaluatedbythewatersubmersion test) after primary stapling and limited suturing were randomised at 12 European centres to open-label treatment with TachoSil W or standard surgicaltreatment(resuturing, staplingor nofurthertreatmentat thesurgeons’discretion).Randomisationwas performedduringsurgeryusinga centralisedinteractive voice response system. Durationof postoperative Air Leakage (primary end point), reductionof intra-operative Air Leakage intensity (secondary end point) and adverse events (AEs), including postoperative complications, were assessed. Results: A total of 486 patients were screened and 299 received trial treatment (intent-to-treat (ITT) population: TachoSil W , n = 148; standard treatment, n = 151). TachoSil W resulted in a reduction in the duration of postoperative Air Leakage (p = 0.030). Patients in the TachoSil W group also experienced a greater reduction in intra-operative Air Leakage intensity (p = 0.042). Median time until chest drain removal was 4 days with TachoSil W and 5 days in the standard group (p = 0.054). There was no difference between groups in hospital length of stay. AEs were generally similar in both groups, including postoperative complications. Conclusions: TachoSil W was superior to standard surgical treatment in reducing both postoperative Air Leakage duration and intra-operative Air Leakage intensity in patients undergoing elective pulmonary lobectomy.
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efficacy and safety of topical application of human fibrinogen thrombin coated collagen patch tachocomb for treatment of Air Leakage after standard lobectomy
European Journal of Cardio-Thoracic Surgery, 2004Co-Authors: Gyorgy Lang, Gabriel Mihai Marta, Attila Csekeo, Georgios Stamatis, Ludwig Lampl, Leif Hagman, Michael Rolf Mueller, Walter KlepetkoAbstract:Objective: Persisting Air Leakage after pulmonary resection remains a significant problem. The aim of the study was to evaluate the incidence of Air Leakage after standard lobectomy and test the efficacy and safety of TachoComb (TC). Methods: A total of 189 patients undergoing lobectomy were enrolled in a multi-centre, open, randomised, and prospective study to test the efficacy and safety of TachoComb (TC) for Air Leakage treatment. Air Leakage was assessed by water submersion test, and scored as grades 0 if no, 1 if countable, 2 if a stream of and 3 if coalescent bubbles have been observed. Any sites with grade 3 Air Leakage received further stapling or limited suturing until grade 0, 1 or 2 was obtained. Treatment of Air Leakage was done with TC or suturing according to randomisation. Air Leakage was assessed by further submersion tests. Postoperative Air Leakage was assessed using the Pleur-Evac system. Results: Overall incidence of Air Leakage 48 ^ 6h after surgery was 34% for TC and 37% for standard treatment ðP ¼ 0:76Þ: The reduction of intra-operative Air leak intensity in the subgroup with grades 1 ‐2 was significantly higher for the TC group ðP ¼ 0:015Þ: Postoperative Air Leakage intensity in the subgroup with Air Leakage grades 1 ‐ 2 was lower for TC than standard treatment ðP ¼ 0:047Þ: The mean duration of postoperative Air Leakage in the subgroup with grades 1 ‐ 2 was shorter for the TC group than for standard treatment, i.e. 1.9 ^ 1.4 vs. 2.7 ^ 2.2 days ðP ¼ 0:015Þ: Conclusions: TC could be proven as well-tolerated and safe. In the subgroup of patients with established Air Leakage, TC showed superior potential in reduction of intra-operative Air Leakage as well as in reduction of intensity and duration of postoperative Air Leakage. q 2003 Elsevier B.V. All rights reserved.
Wanyu R. Chan – One of the best experts on this subject based on the ideXlab platform.
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analysis of Air Leakage measurements from residential diagnostics database
, 2014Co-Authors: Wanyu R. ChanAbstract:Analysis of Air Leakage Measurements from Residential Diagnostics Database W.R. Chan, J. Joh, M.H. Sherman Environmental Energy Technologies Division August 2012
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Analysis of U.S. residential Air Leakage database
Lawrence Berkeley National Laboratory, 2003Co-Authors: Wanyu R. Chan, Phillip N. Price, Michael D. Sohn, Ashok J. GadgilAbstract:Analysis of U.S. Residential Air Leakage Database Wanyu R. Chan ∗ , Phillip N. Price, Michael D. Sohn, Ashok J. Gadgil Indoor Environment Department Lawrence Berkeley National Laboratory One Cyclotron Road Berkeley, California 94720-8132 Corresponding author (Mail Stop: 90R3058; Tel: 510-495-2459; Fax: 510-486-6658; E-mail: wchan@lbl.gov) July 2003 LBNL Report Number 53367 ABSTRACT The Air Leakage of a building envelope can be determined from fan pressurization measurements with a blower door. More than 70,000 Air Leakage measurements have been compiled into a database. In addition to Air Leakage, the database includes other important characteristics of the dwellings tested, such as floor area, year built, and location. There are also data for some houses on the presence of heating ducts, and floor/basement construction type. The purpose of this work is to identify house characteristics that can be used to predict Air Leakage. We found that the distribution of Leakage normalized with floor area of the house is roughly lognormal. Year built and floor area are the two most significant factors to consider when predicting Air Leakage: older and smaller houses tend to have higher normalized Leakage areas compared to newer and larger ones. Results from multiple linear regression of normalized Leakage with respect to these two factors are presented for three types of houses: low-income, energy-efficient, and conventional. We demonstrate a method of using the regression model in conjunction with housing characteristics published by the US Census Bureau to derive a distribution that describes the Air Leakage of the single-family detached housing stock. Comparison of our estimates with published datasets of Air exchange rates suggests that the regression model generates accurate estimates of Air Leakage distribution. Keywords: Air Leakage, Blower door, Fan pressurization measurements, Infiltration
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Analysis of U.S. residential Air Leakage database
, 2003Co-Authors: Wanyu R. Chan, Phillip N. Price, Michael D. Sohn, Ashok J. GadgilAbstract:The Air Leakage of a building envelope can be determined from fan pressurization measurements with a blower door. More than 70,000 Air Leakage measurements have been compiled into a database. In addition to Air Leakage, the database includes other important characteristics of the dwellings tested, such as floor area, year built, and location. There are also data for some houses on the presence of heating ducts, and floor/basement construction type. The purpose of this work is to identify house characteristics that can be used to predict Air Leakage. We found that the distribution of Leakage normalized with floor area of the house is roughly lognormal. Year built and floor area are the two most significant factors to consider when predicting Air Leakage: older and smaller houses tend to have higher normalized Leakage areas compared to newer and larger ones. Results from multiple linear regression of normalized Leakage with respect to these two factors are presented for three types of houses: low-income, energy-efficient, and conventional. We demonstrate a method of using the regression model in conjunction with housing characteristics published by the US Census Bureau to derive a distribution that describes the Air Leakage of the single-family detached housing stock. Comparison of our estimates with published datasets of Air exchange rates suggests that the regression model generates accurate estimates of Air Leakage distribution.
Ashok J. Gadgil – One of the best experts on this subject based on the ideXlab platform.
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Analysis of U.S. residential Air Leakage database
Lawrence Berkeley National Laboratory, 2003Co-Authors: Wanyu R. Chan, Phillip N. Price, Michael D. Sohn, Ashok J. GadgilAbstract:Analysis of U.S. Residential Air Leakage Database Wanyu R. Chan ∗ , Phillip N. Price, Michael D. Sohn, Ashok J. Gadgil Indoor Environment Department Lawrence Berkeley National Laboratory One Cyclotron Road Berkeley, California 94720-8132 Corresponding author (Mail Stop: 90R3058; Tel: 510-495-2459; Fax: 510-486-6658; E-mail: wchan@lbl.gov) July 2003 LBNL Report Number 53367 ABSTRACT The Air Leakage of a building envelope can be determined from fan pressurization measurements with a blower door. More than 70,000 Air Leakage measurements have been compiled into a database. In addition to Air Leakage, the database includes other important characteristics of the dwellings tested, such as floor area, year built, and location. There are also data for some houses on the presence of heating ducts, and floor/basement construction type. The purpose of this work is to identify house characteristics that can be used to predict Air Leakage. We found that the distribution of Leakage normalized with floor area of the house is roughly lognormal. Year built and floor area are the two most significant factors to consider when predicting Air Leakage: older and smaller houses tend to have higher normalized Leakage areas compared to newer and larger ones. Results from multiple linear regression of normalized Leakage with respect to these two factors are presented for three types of houses: low-income, energy-efficient, and conventional. We demonstrate a method of using the regression model in conjunction with housing characteristics published by the US Census Bureau to derive a distribution that describes the Air Leakage of the single-family detached housing stock. Comparison of our estimates with published datasets of Air exchange rates suggests that the regression model generates accurate estimates of Air Leakage distribution. Keywords: Air Leakage, Blower door, Fan pressurization measurements, Infiltration
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Analysis of U.S. residential Air Leakage database
, 2003Co-Authors: Wanyu R. Chan, Phillip N. Price, Michael D. Sohn, Ashok J. GadgilAbstract:The Air Leakage of a building envelope can be determined from fan pressurization measurements with a blower door. More than 70,000 Air Leakage measurements have been compiled into a database. In addition to Air Leakage, the database includes other important characteristics of the dwellings tested, such as floor area, year built, and location. There are also data for some houses on the presence of heating ducts, and floor/basement construction type. The purpose of this work is to identify house characteristics that can be used to predict Air Leakage. We found that the distribution of Leakage normalized with floor area of the house is roughly lognormal. Year built and floor area are the two most significant factors to consider when predicting Air Leakage: older and smaller houses tend to have higher normalized Leakage areas compared to newer and larger ones. Results from multiple linear regression of normalized Leakage with respect to these two factors are presented for three types of houses: low-income, energy-efficient, and conventional. We demonstrate a method of using the regression model in conjunction with housing characteristics published by the US Census Bureau to derive a distribution that describes the Air Leakage of the single-family detached housing stock. Comparison of our estimates with published datasets of Air exchange rates suggests that the regression model generates accurate estimates of Air Leakage distribution.