W.R. Jarnagin
Kettering University
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Publication
Featured researches published by W.R. Jarnagin.
Hpb | 2014
Raphael L.C. Araujo; Ami M. Karkar; P.J. Allen; Mithat Gonen; Joanne F. Chou; Murray F. Brennan; Leslie H. Blumgart; M.I. D'Angelica; R.P. DeMatteo; Daniel G. Coit; Yuman Fong; W.R. Jarnagin
OBJECTIVESnThe timing of major elective operations is a potentially important but rarely examined outcome variable. This study examined elective pancreaticoduodenectomy (PD) timing as a perioperative outcome variable.nnnMETHODSnConsecutive patients submitted to PD were identified. Determinants of 90-day morbidity (prospectively graded and tracked), anastomotic leak or fistula, and mortality, including operation start time (time of day), day of week and month, were assessed in univariate and multivariate analyses. Operation start time was analysed as a continuous and a categorical variable.nnnRESULTSnOf the 819 patients identified, 405 (49.5%) experienced one or more complications (total number of events = 684); 90-day mortality was 3.5%. On multivariate analysis, predictors of any morbidity included male gender (P = 0.009) and estimated blood loss (P = 0.017). Male gender (P = 0.002), benign diagnosis (P = 0.002), presence of comorbidities (P = 0.002), American Society of Anesthesiologists (ASA) score (P = 0.025), larger tumour size (P = 0.013) and positive resection margin status (P = 0.005) were associated with the occurrence of anastomotic leak or fistula. Cardiac and pulmonary comorbidities were the only variables associated with 90-day mortality. Variables pertaining to procedure scheduling were not associated with perioperative morbidity or mortality. Operation start time was not significant when analysed as a continuous or a categorical variable, or when stratified by surgeon.nnnCONCLUSIONSnPerioperative outcome after PD is determined by patient, disease and operative factors and does not appear to be influenced by procedure timing.
Hpb | 2015
Camilo Correa‐Gallego; Somali Gavane; Ravinder Grewal; Andrea Cercek; David S. Klimstra; Alexandra N. Gewirtz; T. Peter Kingham; Yuman Fong; R.P. DeMatteo; P.J. Allen; W.R. Jarnagin; Nancy Kemeny; M.I. D'Angelica
BACKGROUNDnThe prognostic and predictive abilities of 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) coupled with conventional computed tomography (CT) have not been studied in patients with unresectable colorectal liver metastases (uCRLM) treated with combined hepatic arterial infusion (HAI) and systemic chemotherapy.nnnOBJECTIVESnThe ability of PET-CT metabolic response parameters to predict conversion to resectability and oncologic outcome in this setting was evaluated.nnnMETHODSnThirty-eight patients undergoing serial PET-CT as part of a Phase II trial of HAI and systemic chemotherapy for uCRLM were included. Metabolic response was determined as the percentage change in standard uptake value (SUV) and total lesion glycolysis (TLG). Conversion to resection, overall survival (OS), progression-free survival (PFS) and recurrence-free survival were evaluated using standard statistics.nnnRESULTSnVolumetric response sufficient to facilitate resection was seen in 53% of patients after a median of 5 months of therapy. Median follow-up was 38 months (range: 32-52 months). Median OS was not reached [95% confidence interval (CI) 32 months-unknown] and 3-year OS was 54% (range: 33-71%). Median PFS was 13 months (95% CI 6-21 months) and 3 year PFS was 10% (range: 3-20%). Neither baseline values nor the percentage change in any of the metabolic parameters evaluated correlated with conversion to resection, survival variables or hepatic recurrence on Cox regression analysis.nnnCONCLUSIONSnPre- and post-treatment PET-related metabolic parameters do not predict conversion to resection or oncologic outcome in patients with uCRLM treated with HAI and systemic chemotherapy. Metabolic parameters should not be used to monitor response or to determine prognosis in these patients.
Hpb | 2003
M.I. D'Angelica; W.R. Jarnagin; Leslie H. Blumgart
Hpb | 2018
J.W. Kunstman; D.A. Goldman; Mithat Gonen; Vinod P. Balachandran; R.P. DeMatteo; M.I. D'Angelica; W.R. Jarnagin; T.P. Kingham; P.J. Allen
Hpb | 2018
R.R. Narayan; J.M. Creasy; C. Kandoth; D.A. Goldman; Mithat Gonen; P.J. Allen; Vinod P. Balachandran; M.I. D'Angelica; R.P. DeMatteo; J.A. Drebin; T.P. Kingham; Gokce Askan; David S. Klimstra; Olca Basturk; J.M. Butte; I. Endo; W.R. Jarnagin
Hpb | 2018
C.P. Zambirinis; Joanne F. Chou; Mithat Gonen; Amber L. Simpson; Vinod P. Balachandran; T.P. Kingham; M.I. D'Angelica; Jeffrey A. Drebin; P.J. Allen; W.R. Jarnagin
Hpb | 2018
R.R. Narayan; M.L. Babicky; D.A. Goldman; Mithat Gonen; P.J. Allen; Vinod P. Balachandran; M.I. D'Angelica; R.P. DeMatteo; Jeffrey A. Drebin; W.R. Jarnagin; T.P. Kingham
Hpb | 2018
M.L. Babicky; Richard K. G. Do; W.R. Jarnagin; P.J. Allen; R.P. DeMatteo; Jeffrey A. Drebin; Vinod P. Balachandran; T.P. Kingham; Karen T. Brown; M.I. D'Angelica
Hpb | 2018
Thomas Boerner; C.P. Zambirinis; Johan Gagnière; Joanne F. Chou; Mithat Gonen; Peter Kingham; P.J. Allen; Jeffrey A. Drebin; W.R. Jarnagin; Michael I. D’Angelica
Hpb | 2018
Linda M. Pak; Johan Gagnière; P.J. Allen; Vinod P. Balachandran; M.I. D'Angelica; R.P. DeMatteo; W.R. Jarnagin; Amber L. Simpson; T.P. Kingham