scholarly journals A non-linear optimisation method to extract summary statistics from Kaplan-Meier survival plots using the published P value

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Andrew F. Irvine ◽  
Sara Waise ◽  
Edward W. Green ◽  
Beth Stuart
Keyword(s):  
At Risk ◽  
Absolute Error ◽  
P Value ◽  
Summary Statistics ◽  
Time To Event ◽  
Natural Logarithm ◽  
Kaplan Meier ◽  
Non Linear ◽  
Linear Optimisation ◽  
Meta Analyses

Abstract Background Meta-analyses of studies evaluating survival (time-to-event) outcomes are a powerful technique to assess the strength of evidence for a given disease or treatment. However, these studies rely on the adequate reporting of summary statistics in the source articles to facilitate further analysis. Unfortunately, many studies, especially within the field of prognostic research do not report such statistics, making secondary analyses challenging. Consequently, methods have been developed to infer missing statistics from the commonly published Kaplan-Meier (KM) plots but are liable to error especially when the published number at risk is not included. Methods We therefore developed a method using non-linear optimisation (nlopt) that only requires the KM plot and the commonly published P value to better estimate the underlying censoring pattern. We use this information to then calculate the natural logarithm of the hazard ratio (ln (HR)) and its variance (var) ln (HR), statistics important for meta-analyses. Results We compared this method to the Parmar method which also does not require the number at risk to be published. In a validation set consisting of 13 KM studies, a statistically significant improvement in calculating ln (HR) when using an exact P value was obtained (mean absolute error 0.014 vs 0.077, P = 0.003). Thus, when the true HR has a value of 1.5, inference of the HR using the proposed method would set limits between 1.49/1.52, an improvement of the 1.39/1.62 limits obtained using the Parmar method. We also used Monte Carlo simulations to establish recommendations for the number and positioning of points required for the method. Conclusion The proposed non-linear optimisation method is an improvement on the existing method when only a KM plot and P value are included and as such will enhance the accuracy of meta-analyses performed for studies analysing time-to-event outcomes. The nlopt source code is available, as is a simple-to-use web implementation of the method.

scholarly journals High Leverage Practices in Special Education Synthesis Coding Protocol

2021 ◽  
Author(s):  
Gena Nelson
Keyword(s):  
Systematic Review ◽  
At Risk ◽  
Interrater Reliability ◽  
Study Participant ◽  
Summary Statistics ◽  
Summary Statistic ◽  
Basic Study ◽  
The Mean ◽  
Meta Analyses ◽  
Code Book

The purpose of document is to provide readers with the coding protocol that authors used to code 76 meta-analyses focused on students with or at-risk of disabilities. All of the included meta-analyses provided a summary statistic related to at least one of the High Leverage Practices (HLPs; McLeskey et al., 2017). ). The purpose of the systematic review of meta-analyses was to provide an initial investigation of the evidence supporting the effectiveness of the HLPs for students with, or at-risk for, a disability. This code book contains variable names, code options, and code definitions related to basic study information (i.e., authors, year of publication, journal), the details of each study, participant demographics, HLPs included in each study, and summary statistics. The mean interrater reliability across all codes using this protocol was 88% (range across categories = 84%–97%)

scholarly journals Potential bias in the indirect methods for extracting summary statistics in literature-based meta-analyses: an empirical evaluation

2013 ◽  
Author(s):  
Dima Y Abdallah
Keyword(s):  
Random Effects ◽  
Mean Difference ◽  
Rank Test ◽  
P Value ◽  
Summary Statistics ◽  
Potential Bias ◽  
Random Effects Models ◽  
Log Rank Test ◽  
Fixed And Random Effects ◽  
Meta Analyses

Background: In literature-based meta-analyses of cancer prognostic studies, methods for extracting summary statistics from published reports have been extensively employed. However, no assessment of the magnitude of bias produced by these methods or comparison of their influence on fixed vs. random effects models have been published previously. Therefore, the purpose of this study is to empirically assess the degree of bias produced by the methods used for extracting summary statistics and examine potential effects on fixed and random effects models. Methods: Using published data from cancer prognostic studies, systematic differences between reported statistics and those obtained indirectly using log-rank test p-values and total number of events were tested using paired t tests and the log-rank test of survival-agreement plots. The degree of disagreement between estimates was quantified using an information-based disagreement measure, which was also used to examine levels of disagreement between expressions obtained from fixed and random effects models. Results: Thirty-four studies provided a total of 65 estimates of lnHR and its variance. There was a significant difference between the means of the indirect lnHRs and the reported values (mean difference = -0.272, t = -4.652, p-value <0.0001), as well as between the means of the two estimates of variances (mean difference = -0.115, t = -4.5556, p-value <0.0001). Survival agreement plots illustrated a bias towards under-estimation by the indirect method for both lnHR (log-rank p-value = 0.031) and its variance (log-rank p-value = 0.0432). The magnitude of disagreement between estimates of lnHR based on the information-based measure was 0.298 (95% CI: 0.234 – 0.361) and, for the variances it was 0.406 (95% CI: 0.339 – 0.470). As the disagreement between variances was higher than that between lnHR estimates, this increased the level of disagreement between lnHRs weighted by the inverse of their variances in fixed effect models. In addition, results indicated that random effects meta-analyses could be more prone to bias than fixed effects meta-analyses as, in addition to bias in estimates of lnHRs and their variances, levels of disagreement as high as 0.487 (95% CI: 0.416 – 0.552) and 0.568 (95% CI: 0.496 – 0.635) were produced due to between-studies variance calculations. Conclusions: Extracting summary statistics from published studies could introduce bias in literature-based meta-analyses and undermine the validity of the evidence. These findings emphasise the importance of reporting sufficient statistical information in research articles and warrant further research into the influence of potential bias on random effects models.

scholarly journals Potential bias in the indirect methods for extracting summary statistics in literature-based meta-analyses: an empirical evaluation

2013 ◽  
Author(s):  
Dima Y Abdallah
Keyword(s):  
Random Effects ◽  
Mean Difference ◽  
Rank Test ◽  
P Value ◽  
Summary Statistics ◽  
Potential Bias ◽  
Random Effects Models ◽  
Log Rank Test ◽  
Fixed And Random Effects ◽  
Meta Analyses

Background: In literature-based meta-analyses of cancer prognostic studies, methods for extracting summary statistics from published reports have been extensively employed. However, no assessment of the magnitude of bias produced by these methods or comparison of their influence on fixed vs. random effects models have been published previously. Therefore, the purpose of this study is to empirically assess the degree of bias produced by the methods used for extracting summary statistics and examine potential effects on fixed and random effects models. Methods: Using published data from cancer prognostic studies, systematic differences between reported statistics and those obtained indirectly using log-rank test p-values and total number of events were tested using paired t tests and the log-rank test of survival-agreement plots. The degree of disagreement between estimates was quantified using an information-based disagreement measure, which was also used to examine levels of disagreement between expressions obtained from fixed and random effects models. Results: Thirty-four studies provided a total of 65 estimates of lnHR and its variance. There was a significant difference between the means of the indirect lnHRs and the reported values (mean difference = -0.272, t = -4.652, p-value <0.0001), as well as between the means of the two estimates of variances (mean difference = -0.115, t = -4.5556, p-value <0.0001). Survival agreement plots illustrated a bias towards under-estimation by the indirect method for both lnHR (log-rank p-value = 0.031) and its variance (log-rank p-value = 0.0432). The magnitude of disagreement between estimates of lnHR based on the information-based measure was 0.298 (95% CI: 0.234 – 0.361) and, for the variances it was 0.406 (95% CI: 0.339 – 0.470). As the disagreement between variances was higher than that between lnHR estimates, this increased the level of disagreement between lnHRs weighted by the inverse of their variances in fixed effect models. In addition, results indicated that random effects meta-analyses could be more prone to bias than fixed effects meta-analyses as, in addition to bias in estimates of lnHRs and their variances, levels of disagreement as high as 0.487 (95% CI: 0.416 – 0.552) and 0.568 (95% CI: 0.496 – 0.635) were produced due to between-studies variance calculations. Conclusions: Extracting summary statistics from published studies could introduce bias in literature-based meta-analyses and undermine the validity of the evidence. These findings emphasise the importance of reporting sufficient statistical information in research articles and warrant further research into the influence of potential bias on random effects models.

Penyelidikan KLB keracunan makanan acara ruwahan di desa Mulo, Gunung Kidul provinsi DIY

2018 ◽  
pp. 1
Author(s):  
Mur Prasetyaningrum ◽  
Z. Chomariyah ◽  
Trisno Agung Wibowo
Keyword(s):  
At Risk ◽  
Total Population ◽  
Total Coliform ◽  
Case Control ◽  
P Value ◽  
Common Source ◽  
Population At Risk ◽  
E Coli

Tujuan: Studi ini untuk mengetahui gambaran KLB keracunan pangan yang terjadi di desa Mulo menurut deskripsi epidemiologi, faktor risiko dan penyebab KLB keracunan makanan. Metode: Studi ini menggunakan studi analitik case control, dimana kasus adalah orang yang mengalami sakit pada tanggal 7 - 8 Mei 2017, tinggal di desa Mulo dan mengkonsumsi makanan olahan dari bapak S dan K. Instrument menggunakan kuesioner. Hasil: KLB terjadi di Desa Mulo RT 5 dan 6 dengan jumlah kasus sebanyak 18 orang dari total population at risk 112 orang dengan gejala utama diare (100%), mual (72,2%), demam (66,6%), pusing (66,6%) dan muntah (50%). Dari diagnosa banding menurut gejala, masa inkubasi dan agent penyebab keracunan, kecurigaan kontaminasi bakteri mengarah pada E. Coli (ETEC). Masa inkubasi 1-16 jam (rata-rata 9 jam) dan common source curve. Penyaji makanan ada dua (pak K dan pak S). Dari perhitungan AR, berdasarkan sumber makanan mengarah pada makanan dari pak S (AR=42,8%). Bedasarkan menu, perhitungan OR dan CI 95 % jenis makanan yang dicurigai sebagai penyebab KLB adalah urap/gudangan (OR=4,33; p value0,0071) dan sayur lombok (OR=6,31; p value 0,0071). Sampel yang didapatkan adalah sampel air bersih, feses, dan muntahan penderita, sampel makanan tidak didapatkan karena keterlambatan informasi dari masyarakat. Hasil laboratorium, Total Coliform sampel air bersih melebihi ambang batas, sampel feses dan muntahan mengandung bakteri Klebsiella pneumonia.Simpulan: Terdapat 3 (tiga) faktor yang diduga sebagai penyebab keracunan pada warga Desa Mulo yaitu air bersih untuk mengolah makanan tercemar bakteri patogen, pengolahan makanan tidak hygienis dan penyajian makanan pada suhu ruang lebih dari 1 jam.

scholarly journals Review of Outcomes after Diagnosis of Malignancy in Kidney Transplant Patients: UNOS Database

2021 ◽  
Vol 2 (3) ◽  
pp. 253-263
Author(s):  
Het Patel ◽  
Nikhil Agrawal ◽  
Voravech Nissaisorakarn ◽  
Ridhi Gupta ◽  
Francesca Cardarelli
Keyword(s):  
Kidney Transplant ◽  
Graft Failure ◽  
Event Analysis ◽  
Transplant Recipients ◽  
Kidney Transplant Recipients ◽  
Time To Event ◽  
Transplant Patients ◽  
Kaplan Meier ◽  
Lung Malignancy ◽  
Kidney Transplant Patients

Malignancy is the third major cause of death among transplant recipients. Patient and kidney transplant outcomes after the diagnosis of malignancy are not well described. We reviewed incidences and outcomes of colorectal, lung, PTLD, and renal malignancy after transplant among patients who received a transplant from January 2000 to December 2018 using the UNOS/OPTN database. Incidence of each malignancy was measured at 5 years and 10 years of transplant. The Kaplan–Meier curve was used for time-to-event analysis (graft and patient outcomes). Additionally, we sought to identify the causes of graft failure among these recipients. We found that 12,764 (5.5%) patients suffered malignancy, excluding squamous and basal cell skin carcinoma after transplant. During the first 5 years of transplant, incidence of colorectal, lung, PTLD, and renal malignancies was 2.99, 9.21, 15.61, and 8.55 per 10,000 person-years, respectively. Rates of graft failure were 10.3%, 7.6%, 19.9%, and 18.8%, respectively, among these patients at 5 years. Mortality rate was highest among patients who suffered lung malignancy (84%), followed by colorectal (61.5%), PTLD (49.1%), and renal (35.5%) at 5 years after diagnosis of malignancy. In conclusion, kidney transplant recipients diagnosed with lung malignancy have the lowest graft survival, compared to PTLD, colorectal, and renal malignancy. PTLD has the highest incidence rate in the first 5 years of transplant.

scholarly journals AB0337 TOFACITINIB MONOTHERAPY OR COMBINED WITH METHOTREXATE IN PATIENTS WITH RHEUMATOID ARTHRITIS SHOW SIMILAR RETENTION OVER FOUR YEARS. REPORT FROM RHUMADATA ®

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1467.1-1467
Author(s):  
D. Choquette ◽  
L. Bessette ◽  
L. Choquette Sauvageau ◽  
I. Ferdinand ◽  
B. Haraoui ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Disease Activity ◽  
Real World ◽  
Treatment Initiation ◽  
Retention Rate ◽  
Janus Kinase ◽  
P Value ◽  
Research Support ◽  
Medication Discontinuation ◽  
Kaplan Meier

Background:Since the introduction of biologic agents around the turn of the century, the scientific evidence shows that the majority of agents, independent of the therapeutic target, have a better outcome when used in combination with methotrexate (MTX). In 2014, tofacitinib (TOFA), an agent targeting Janus kinase 1 and 3, has reached the Canadian market with data showing that the combination with MTX may not be necessary [1,2].Objectives:To evaluate the efficacy and retention rate of TOFA in real-world patients with rheumatoid arthritis (RA).Methods:Two cohorts of patients prescribed TOFA was created. The first cohort was formed of patients who were receiving MTX concomitantly with TOFA (COMBO) and the other of patients using TOFA in monotherapy (MONO). MONO patients either never use MTX or were prescribed MTX post-TOFA initiation for at most 20% of the time they were on TOFA. COMBO patients received MTX at the time of TOFA initiation or were prescribed MTX post-TOFA initiation for at least 80% of the time. For all those patients, baseline demographic data definitions. Disease activity score and HAQ-DI were compared from the initiation of TOFA to the last visit. Time to medication discontinuation was extracted, and survival was estimated using Kaplan-Meier calculation for MONO and COMBO cohorts.Results:Overall, 194 patients were selected. Most were women (83%) on average younger than the men (men: 62.6 ± 11.0 years vs. women: 56.9 ± 12.1 years, p-value=0.0130). The patient’s assessments of global disease activity, pain and fatigue were respectively 5.0 ± 2.7, 5.2 ± 2.9, 5.1 ± 3.1 in the COMBO group and 6.2 ± 2.5, 6.5 ± 2.6, 6.3 ± 2.8 in the MONO group all differences being significant across groups. HAQ-DI at treatment initiation was 1.3 ± 0.7 and 1.5 ± 0.7 in the COMBO and MONO groups, respectively, p-value=0.0858. Similarly, the SDAI score at treatment initiation was 23.9 ± 9.4 and 25.2 ± 11.5, p-value=0.5546. Average changes in SDAI were -13.4 ± 15.5 (COMBO) and -8.9 ± 13.5 (MONO), p-value=0.1515, and changes in HAQ -0.21 ± 0.63 and -0.26 ± 0.74, p-value 0.6112. At treatment initiation, DAS28(4)ESR were 4.4 ± 1.4 (COMBO) and 4.6 ± 1.3 (MONO), p-value 0.5815, with respective average changes of -1.06 ± 2.07 and -0.70 ± 1.96, p-value=0.2852. The Kaplan-Meier analysis demonstrated that the COMBO and MONO retention curves were not statistically different (log-rank p-value=0.9318).Conclusion:Sustainability of TOFA in MONO or COMBO are not statistically different as are the changes in DAS28(4)ESR and SDAI. Despite this result, some patients may still benefit from combination with MTX.References:[1]Product Monograph - XELJANZ ® (tofacitinib) tablets for oral administration Initial U.S. Approval: 2012.[2] Reed GW, Gerber RA, Shan Y, et al. Real-World Comparative Effectiveness of Tofacitinib and Tumor Necrosis Factor Inhibitors as Monotherapy and Combination Therapy for Treatment of Rheumatoid Arthritis [published online ahead of print, 2019 Nov 9].Rheumatol Ther. 2019;6(4):573–586. doi:10.1007/s40744-019-00177-4.Disclosure of Interests:Denis Choquette Grant/research support from: Rhumadata is supported by grants from Pfizer, Amgen, Abbvie, Gylead, BMS, Novartis, Sandoz, eli Lilly,, Consultant of: Pfizer, Amgen, Abbvie, Gylead, BMS, Novartis, Sandoz, eli Lilly,, Speakers bureau: Pfizer, Amgen, Abbvie, Gylead, BMS, Novartis, Sandoz, eli Lilly,, Louis Bessette Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, Roche, Sanofi, UCB Pharma, Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, Roche, Sanofi, UCB Pharma, Speakers bureau: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, Sanofi, Loïc Choquette Sauvageau: None declared, Isabelle Ferdinand Consultant of: Pfizer, Abbvie, Amgen, Novartis, Speakers bureau: Pfizer, Amgen, Boulos Haraoui Grant/research support from: Abbvie, Amgen, Pfizer, UCB, Grant/research support from: AbbVie, Amgen, BMS, Janssen, Pfizer, Roche, and UCB, Consultant of: Abbvie, Amgen, Lilly, Pfizer, Sandoz, UCB, Consultant of: AbbVie, Amgen, BMS, Celgene, Eli Lilly, Janssen, Merck, Pfizer, Roche, and UCB, Speakers bureau: Pfizer, Speakers bureau: Amgen, BMS, Janssen, Pfizer, and UCB, Frédéric Massicotte Consultant of: Abbvie, Janssen, Lilly, Pfizer, Speakers bureau: Janssen, Jean-Pierre Pelletier Shareholder of: ArthroLab Inc., Grant/research support from: TRB Chemedica, Speakers bureau: TRB Chemedica and Mylan, Jean-Pierre Raynauld Consultant of: ArthroLab Inc., Marie-Anaïs Rémillard Consultant of: Abbvie, Amgen, Eli Lilly, Novartis, Pfizer, Sandoz, Paid instructor for: Abbvie, Amgen, Eli Lilly, Novartis, Pfizer, Sandoz, Speakers bureau: Abbvie, Amgen, Eli Lilly, Novartis, Pfizer, Sandoz, Diane Sauvageau: None declared, Édith Villeneuve Consultant of: Abbvie, Amgen, BMS, Celgene, Pfizer, Roche, Sanofi-Genzyme,UCB, Paid instructor for: Abbvie, Speakers bureau: AbbVie, BMS, Pfizer, Roche, Louis Coupal: None declared

Reporting Quality in Math Meta-Analyses for Students with or at Risk of Disabilities

2021 ◽  
pp. 001440292110508
Author(s):  
Gena Nelson ◽  
Soyoung Park ◽  
Tasia Brafford ◽  
Nicole A. Heller ◽  
Angela R. Crawford ◽  
...  
Keyword(s):  
At Risk ◽  
Students With Disabilities ◽  
Reporting Quality ◽  
Quality Of Reporting ◽  
Mathematics Interventions ◽  
Screening Process ◽  
Mathematics Intervention ◽  
Meta Analyses ◽  
Abstract Screening

Researchers and practitioners alike often look to meta-analyses to identify effective practices to use with students with disabilities. The number of meta-analyses in special education has also expanded in recent years. The purpose of this systematic review is to evaluate the quality of reporting in meta-analyses focused on mathematics interventions for students with or at risk of disabilities. We applied 53 quality indicators (QIs) across eight categories based on recommendations from Talbott et al. to 22 mathematics intervention meta-analyses published between 2000 and 2020. Overall, the meta-analyses met 61% of QIs and results indicated that meta-analyses most frequently met QIs related to providing a clear purpose (95%) and data analysis plan (77%), whereas meta-analyses typically met fewer QIs related to describing participants (39%) and explaining the abstract screening process (48%). We discuss the variation in quality indicator scores within and across the quality categories and provide recommendations for future researchers.

Abstract 13: Sex Differences in Mortality Among Patients With Covid-19 Related Stroke

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Farhaan S Vahidy ◽  
Jennifer Meeks ◽  
Alan Pan ◽  
Thomas Potter ◽  
Osman Khan ◽  
...  
Keyword(s):  
Sex Differences ◽  
Sensitivity Analyses ◽  
Rank Test ◽  
P Value ◽  
Matched Sample ◽  
Healthcare Organizations ◽  
Time To Death ◽  
Kaplan Meier ◽  
Laboratory Confirmation ◽  
Icd 10

Introduction: Overall poor COVID-19 outcomes have been reported among males. We evaluated sex differences in mortality among patients with stroke related to COVID-19. Methods: Utilizing pooled deidentified data from 30 healthcare organizations, we identified COVID-19 patients via ICD-10 diagnosis or documented laboratory confirmation of SARS-CoV-2 RNA or antibodies. Patients with ICD-10 diagnoses of ischemic stroke or intracerebral hemorrhage within 30 days before or after the COVID-19 event were flagged. Male and female patients were propensity score (PS) matched on other demographic and comorbidity variables. Risk Ratio (RR) and 95% Confidence Interval (CI) for association between sex and 90-day mortality is reported. Kaplan-Meier analyses with log rank test (LRT) were conducted for time-to-death. As a sensitivity analysis, we only included a smaller sub-set with first instance of IS or ICH ± 30-days of COVID-19 diagnosis. Results: Among 149,410 COVID-19 patients, 1,618 (1.1%) had a stroke diagnosis ± 30-days of confirmed COVID-19. Of whom, 1,609 patients (847 males and 762 females) were included in primary analyses. Females were older (67.7 vs. 65.7 years) and were more likely to be of black race (34.1% vs. 27.6%). Females had a significantly higher proportion of chronic pulmonary disease (38.8% vs. 28.8%) and obesity (34.2% vs. 24.8%); whereas males had higher proportion of alcohol abuse (8.5% vs. 3.8%). A 1:1 PS algorithm yielded an optimally matched sample of 634 males and females each, balanced on all covariates. In the matched sample, 11.7% of females and 15.8% of males experienced 90-day mortality; RR (CI): 1.35 (1.02 - 1.78), LRT p value 0.04. Higher risk of 90-day mortality among males with COVID-19 and stroke was maintained in the sensitivity analyses, RR (CI): 1.47 (1.06 - 2.00), LRT p value = 0.03 (graphic). Conclusion: Future studies examining the socio-demographic and biological mechanisms for poor stroke outcomes among males with COVID-19 are needed.

Abstract 235: Ischemia-Reperfusion Injury Decreases Myocardial Hydration Potential Without Changing Flow Resistance in the Interstitial Matrix

2012 ◽  
Vol 111 (suppl_1) ◽  
Author(s):  
Maria P McGee ◽  
Michael Morykwas ◽  
James Jordan ◽  
Louis Argenta
Keyword(s):  
At Risk ◽  
Flow Resistance ◽  
Ischemia Reperfusion Injury ◽  
Ex Vivo ◽  
Ischemia Reperfusion ◽  
P Value ◽  
Mechanical Forces ◽  
Interstitial Flow ◽  
Elastic Recoil ◽  
Fluid Accumulation

Interstitial edema is an early response to myocardial ischemia, leading to fibrosis and remodeling in several heart failure conditions. We aimed to clarify whether osmotic, frictional, or mechanical forces drive fluid accumulation. Equilibrium and dynamic interstitial hydration parameters were determined, compared, and analyzed using osmotic stress approaches in explants from ischemic and nonischemic myocardial regions of pig heart. They were isolated after injury induced by ligating 3-4 branches of the left anterior descending coronary artery, for 85 min followed by 3 hours’ reperfusion. Their volume changed (Δ V max ) linearly with colloidosmotic pressure in both ischemic and nonischemic areas, yielding interstitial compliance values of 1.04 ± 0.09 and 1.08 ± 0.05 µl/g/ mmHg , which do not differ significantly, and hydration potentials from the abscissa intercepts at Δ V max = 0, of -121.4 ± 28 and -14.7 ± 7.6 mmHg, which do (mean ± SE, n = 5 , P-value = 0.001). These hydration potential differences manifest ex-vivo influx rates 8.5 ± 2.7- fold slower in ischemic than nonischemic myocardium. Surprisingly, interstitial flow resistance values derived from net-flow rates at an imposed pressure difference of 216 mmHg were 0.23 ± 0.08 and 0.19 ± 0.01 µl -1 . g. min and did not differ significantly between the areas. The similarity in interstitial compliance and fluid resistance indicates that the more negative hydration potential and faster efflux rates in at-risk regions after reperfusion are due to increased hydrostatic pressure rather than decreased osmotic or frictional forces. Tissue distends due to interstitial fluid accumulation against matrix mechanical forces, including elastic recoil of the collagen elastin mesh and fibroblast action, consistent with impaired drainage and persistent diastolic-like conditions during reperfusion of at-risk areas in vivo . These results indicate changes in pressure gradient magnitude and may have clinical and therapeutic implications; for example, reversal of paracrine interstitial flows during early remodeling

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