John Cochran VA Medical Center

AUTORES: Daniel J Klionsky1745,1749*, Kotb Abdelmohsen840, Akihisa Abe1237, Md Joynal Abedin1762, Hagai Abeliovich425,
\nAbraham Acevedo Arozena789, Hiroaki Adachi1800, Christopher M Adams1669, Peter D Adams57, Khosrow Adeli1981,
\nPeter J Adhihetty1625, Sharon G Adler700, Galila Agam67, Rajesh Agarwal1587, Manish K Aghi1537, Maria Agnello1826,
\nPatrizia Agostinis664, Patricia V Aguilar1960, Julio Aguirre-Ghiso784,786, Edoardo M Airoldi89,422, Slimane Ait-Si-Ali1376,
\nTakahiko Akematsu2010, Emmanuel T Akporiaye1097, Mohamed Al-Rubeai1394, Guillermo M Albaiceta1294,
\nChris Albanese363, Diego Albani561, Matthew L Albert517, Jesus Aldudo128, Hana Alg€ul1164, Mehrdad Alirezaei1198,
\nIraide Alloza642,888, Alexandru Almasan206, Maylin Almonte-Beceril524, Emad S Alnemri1212, Covadonga Alonso544,
\nNihal Altan-Bonnet848, Dario C Altieri1205, Silvia Alvarez1497, Lydia Alvarez-Erviti1395, Sandro Alves107,
\nGiuseppina Amadoro860, Atsuo Amano930, Consuelo Amantini1554, Santiago Ambrosio1458, Ivano Amelio756,
\nAmal O Amer918, Mohamed Amessou2089, Angelika Amon726, Zhenyi An1538, Frank A Anania291, Stig U Andersen6,
\nUsha P Andley2079, Catherine K Andreadi1690, Nathalie Andrieu-Abadie502, Alberto Anel2027, David K Ann58,
\nShailendra Anoopkumar-Dukie388, Manuela Antonioli832,858, Hiroshi Aoki1791, Nadezda Apostolova2007,
\nSaveria Aquila1500, Katia Aquilano1876, Koichi Araki292, Eli Arama2098, Agustin Aranda456, Jun Araya591,
\nAlexandre Arcaro1472, Esperanza Arias26, Hirokazu Arimoto1225, Aileen R Ariosa1749, Jane L Armstrong1930,
\nThierry Arnould1773, Ivica Arsov2120, Katsuhiko Asanuma675, Valerie Askanas1924, Eric Asselin1867, Ryuichiro Atarashi794,
\nSally S Atherton369, Julie D Atkin713, Laura D Attardi1131, Patrick Auberger1787, Georg Auburger379, Laure Aurelian1727,
\nRiccardo Autelli1992, Laura Avagliano1029,1755, Maria Laura Avantaggiati364, Limor Avrahami1166, Suresh Awale1986,
\nNeelam Azad404, Tiziana Bachetti568, Jonathan M Backer28, Dong-Hun Bae1933, Jae-sung Bae677, Ok-Nam Bae409,
\nSoo Han Bae2117, Eric H Baehrecke1729, Seung-Hoon Baek17, Stephen Baghdiguian1368,
\nAgnieszka Bagniewska-Zadworna2, Hua Bai90, Jie Bai667, Xue-Yuan Bai1133, Yannick Bailly884,
\nKithiganahalli Narayanaswamy Balaji473, Walter Balduini2002, Andrea Ballabio316, Rena Balzan1711, Rajkumar Banerjee239,
\nG abor B anhegyi1052, Haijun Bao2109, Benoit Barbeau1363, Maria D Barrachina2007, Esther Barreiro467, Bonnie Bartel997,
\nAlberto Bartolom e222, Diane C Bassham550, Maria Teresa Bassi1046, Robert C Bast Jr1273, Alakananda Basu1798,
\nMaria Teresa Batista1578, Henri Batoko1336, Maurizio Battino970, Kyle Bauckman2085, Bradley L Baumgarner1909,
\nK Ulrich Bayer1594, Rupert Beale1553, Jean-Fran¸cois Beaulieu1360, George R. Beck Jr48,294, Christoph Becker336,
\nJ David Beckham1595, Pierre-Andr e B edard749, Patrick J Bednarski301, Thomas J Begley1135, Christian Behl1419,
\nChristian Behrends757, Georg MN Behrens406, Kevin E Behrns1627, Eloy Bejarano26, Amine Belaid490,
\nFrancesca Belleudi1041, Giovanni B enard497, Guy Berchem706, Daniele Bergamaschi983, Matteo Bergami1401,
\nBen Berkhout1441, Laura Berliocchi714, Am elie Bernard1749, Monique Bernard1354, Francesca Bernassola1880,
\nAnne Bertolotti791, Amanda S Bess272, S ebastien Besteiro1351, Saverio Bettuzzi1828, Savita Bhalla913,
\nShalmoli Bhattacharyya973, Sujit K Bhutia838, Caroline Biagosch1159, Michele Wolfe Bianchi520,1378,1381,
\nMartine Biard-Piechaczyk210, Viktor Billes298, Claudia Bincoletto1314, Baris Bingol350, Sara W Bird1128, Marc Bitoun1112,
\nIvana Bjedov1258, Craig Blackstone843, Lionel Blanc1183, Guillermo A Blanco1496, Heidi Kiil Blomhoff1812,
\nEmilio Boada-Romero1297, Stefan B€ockler1464, Marianne Boes1423, Kathleen Boesze-Battaglia1835, Lawrence H Boise286,287,
\nAlessandra Bolino2063, Andrea Boman693, Paolo Bonaldo1823, Matteo Bordi897, J€urgen Bosch608, Luis M Botana1308,
\nJoelle Botti1375, German Bou1405, Marina Bouch e1038, Marion Bouchecareilh1331, Marie-Jos ee Boucher1901,
\nMichael E Boulton481, Sebastien G Bouret1926, Patricia Boya133, Micha€el Boyer-Guittaut1345, Peter V Bozhkov1141,
\nNathan Brady374, Vania MM Braga469, Claudio Brancolini1997, Gerhard H Braus353, Jos e M Bravo-San Pedro299,393,508,1374,
\nLisa A Brennan322, Emery H Bresnick2022, Patrick Brest490, Dave Bridges1939, Marie-Agn es Bringer124, Marisa Brini1822,
\nGlauber C Brito1311, Bertha Brodin631, Paul S Brookes1872, Eric J Brown352, Karen Brown1690, Hal E Broxmeyer480,
\nAlain Bruhat486,1339, Patricia Chakur Brum1893, John H Brumell446, Nicola Brunetti-Pierri315,1171,
\nRobert J Bryson-Richardson781, Shilpa Buch1777, Alastair M Buchan1819, Hikmet Budak1022, Dmitry V Bulavin118,505,1789,
\nScott J Bultman1792, Geert Bultynck665, Vladimir Bumbasirevic1470, Yan Burelle1356, Robert E Burke216,217,
\nMargit Burmeister1750, Peter B€utikofer1473, Laura Caberlotto1987, Ken Cadwell896, Monika Cahova112, Dongsheng Cai24,
\nJingjing Cai2099, Qian Cai1018, Sara Calatayud2007, Nadine Camougrand1343, Michelangelo Campanella1700,
\nGrant R Campbell1525, Matthew Campbell1249, Silvia Campello556,1876, Robin Candau1769, Isabella Caniggia1983,
\nLavinia Cantoni560, Lizhi Cao116, Allan B Caplan1656, Michele Caraglia1051, Claudio Cardinali1043, Sandra Morais Cardoso1579, Jennifer S Carew208, Laura A Carleton874, Cathleen R Carlin101, Silvia Carloni2002,
\nSven R Carlsson1267, Didac Carmona-Gutierrez1643, Leticia AM Carneiro312, Oliana Carnevali971, Serena Carra1318,
\nAlice Carrier120, Bernadette Carroll900, Caty Casas1324, Josefina Casas1116, Giuliana Cassinelli324, Perrine Castets1462,
\nSusana Castro-Obregon214, Gabriella Cavallini1841, Isabella Ceccherini568, Francesco Cecconi253,555,1884,
\nArthur I Cederbaum459, Valent ın Ce~na199,1281, Simone Cenci1323,2064, Claudia Cerella444, Davide Cervia1996,
\nSilvia Cetrullo1478, Hassan Chaachouay2028, Han-Jung Chae187, Andrei S Chagin634, Chee-Yin Chai626,628,
\nGopal Chakrabarti1502, Georgios Chamilos1601, Edmond YW Chan1142, Matthew TV Chan181, Dhyan Chandra1003,
\nPallavi Chandra548, Chih-Peng Chang818, Raymond Chuen-Chung Chang1653, Ta Yuan Chang345, John C Chatham1434,
\nSaurabh Chatterjee1910, Santosh Chauhan527, Yongsheng Che62, Michael E Cheetham1263, Rajkumar Cheluvappa1783,
\nChun-Jung Chen1153, Gang Chen598,1676, Guang-Chao Chen9, Guoqiang Chen1078, Hongzhuan Chen1077, Jeff W Chen1514,
\nJian-Kang Chen370,371, Min Chen249, Mingzhou Chen2104, Peiwen Chen1823, Qi Chen1674, Quan Chen172,
\nShang-Der Chen138, Si Chen325, Steve S-L Chen10, Wei Chen2125, Wei-Jung Chen829, Wen Qiang Chen979, Wenli Chen1113,
\nXiangmei Chen1133, Yau-Hung Chen1157, Ye-Guang Chen1250, Yin Chen1447, Yingyu Chen953,955, Yongshun Chen2135,
\nYu-Jen Chen712, Yue-Qin Chen1145, Yujie Chen1208, Zhen Chen339, Zhong Chen2123, Alan Cheng1702,
\nChristopher HK Cheng184, Hua Cheng1728, Heesun Cheong814, Sara Cherry1836, Jason Chesney1703,
\nChun Hei Antonio Cheung817, Eric Chevet1359, Hsiang Cheng Chi140, Sung-Gil Chi656, Fulvio Chiacchiera308,
\nHui-Ling Chiang958, Roberto Chiarelli1826, Mario Chiariello235,567,577, Marcello Chieppa835, Lih-Shen Chin290,
\nMario Chiong1285, Gigi NC Chiu878, Dong-Hyung Cho676, Ssang-Goo Cho650, William C Cho982, Yong-Yeon Cho105,
\nYoung-Seok Cho1064, Augustine MK Choi2095, Eui-Ju Choi656, Eun-Kyoung Choi387,400,685, Jayoung Choi1563,
\nMary E Choi2093, Seung-Il Choi2116, Tsui-Fen Chou412, Salem Chouaib395, Divaker Choubey1574, Vinay Choubey1936,
\nKuan-Chih Chow822, Kamal Chowdhury730, Charleen T Chu1856, Tsung-Hsien Chuang827, Taehoon Chun657,
\nHyewon Chung652, Taijoon Chung978, Yuen-Li Chung1194, Yong-Joon Chwae18, Valentina Cianfanelli254,
\nRoberto Ciarcia1775, Iwona A Ciechomska886, Maria Rosa Ciriolo1876, Mara Cirone1042, Sofie Claerhout1694,
\nMichael J Clague1698, Joan Cl aria1457, Peter GH Clarke1687, Robert Clarke361, Emilio Clementi1045,1398, C edric Cleyrat1781,
\nMiriam Cnop1366, Eliana M Coccia574, Tiziana Cocco1459, Patrice Codogno1375, J€orn Coers271, Ezra EW Cohen1533,
\nDavid Colecchia235,567,577, Luisa Coletto25, N uria S Coll123, Emma Colucci-Guyon516, Sergio Comincini1829,
\nMaria Condello578, Katherine L Cook2073, Graham H Coombs1929, Cynthia D Cooper2076, J Mark Cooper1395,
\nIsabelle Coppens601, Maria Tiziana Corasaniti1387, Marco Corazzari485,1884, Ramon Corbalan1566,
\nElisabeth Corcelle-Termeau251, Mario D Cordero1899, Cristina Corral-Ramos1289, Olga Corti507,1109, Andrea Cossarizza1767,
\nPaola Costelli1993, Safia Costes1518, Susan L Cotman721, Ana Coto-Montes946, Sandra Cottet566,1688, Eduardo Couve1301,
\nLori R Covey1015, L Ashley Cowart762, Jeffery S Cox1536, Fraser P Coxon1427, Carolyn B Coyne1846, Mark S Cragg1919,
\nRolf J Craven1679, Tiziana Crepaldi1995, Jose L Crespo1300, Alfredo Criollo1285, Valeria Crippa558, Maria Teresa Cruz1576,
\nAna Maria Cuervo26, Jose M Cuezva1277, Taixing Cui1907, Pedro R Cutillas987, Mark J Czaja27, Maria F Czyzyk-Krzeska1572,
\nRuben K Dagda2068, Uta Dahmen1404, Chunsun Dai800, Wenjie Dai1187, Yun Dai2059, Kevin N Dalby1940,
\nLuisa Dalla Valle1822, Guillaume Dalmasso1340, Marcello D’Amelio557, Markus Damme188, Arlette Darfeuille-Michaud1340,
\nCatherine Dargemont950, Victor M Darley-Usmar1433, Srinivasan Dasarathy205, Biplab Dasgupta202, Srikanta Dash1254,
\nCrispin R Dass242, Hazel Marie Davey8, Lester M Davids1560, David D avila227, Roger J Davis1731, Ted M Dawson604,
\nValina L Dawson606, Paula Daza1898, Jackie de Belleroche470, Paul de Figueiredo1180,1182,
\nRegina Celia Bressan Queiroz de Figueiredo135, Jos e de la Fuente1023, Luisa De Martino1775,
\nAntonella De Matteis1171, Guido RY De Meyer1443, Angelo De Milito631, Mauro De Santi2002,

autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

BACKGROUND: Data used for evaluating quality of medical care need to be of high reliability to ensure valid quality assessment and benchmarking. The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) has continually emphasized the collection of highly reliable clinical data through its program infrastructure. STUDY DESIGN: We provide a detailed description of the various mechanisms used in ACS NSQIP to assure collection of high quality data, including training of data collectors (surgical clinical reviewers) and ongoing audits of data reliability. For the 2005 through 2008 calendar years, inter-rater reliability was calculated overall and for individual variables using percentages of agreement between the data collector and the auditor. Variables with > 5% disagreement are flagged for educational efforts to improve accurate collection. Cohen's kappa was estimated for selected variables from the 2007 audit year. RESULTS: Inter-rater reliability audits show that overall disagreement rates on variables have fallen from 3.15% in 2005 (the first year of public enrollment in ACS NSQIP) to 1.56% in 2008. In addition, disagreement levels for individual variables have continually improved, with 26 individual variables demonstrating > 5% disagreement in 2005, to only 2 such variables in 2008. Estimated kappa values suggest substantial or almost perfect agreement for most variables. CONCLUSIONS: The ACS NSQIP has implemented training and audit procedures for its hospital participants that are highly effective in collecting robust data. Audit results show that data have been reliable since the program's inception and that reliability has improved every year.

In Brief Background/Objective: The National Surgical Quality Improvement Program (NSQIP) has demonstrated quality improvement in the VA and pilot study of 14 academic institutions. The objective was to show that American College of Surgeons (ACS)-NSQIP helps all enrolled hospitals. Methods: ACS-NSQIP data was used to evaluate improvement in hospitals longitudinally over 3 years (2005–2007). Improvement was defined as reduction in risk-adjusted “Observed/Expected” (O/E) ratios between periods with risk adjustment held constant. Multivariable logistic regression-based adjustment was performed and included indicators for procedure groups. Additionally, morbidity counts were modeled using a negative binomial model, to estimate the number of avoided complications. Results: Multiple perspectives reflected improvement over time. In the analysis of 118 hospitals (2006–2007), 66% of hospitals improved risk-adjusted mortality (mean O/E improvement: 0.174; P < 0.05) and 82% improved risk adjusted complication rates (mean improvement: 0.114; P < 0.05). Correlations between starting O/E and improvement (0.834 for mortality, 0.652 for morbidity), as well as relative risk, revealed that initially worse-performing hospitals had more likelihood of improvement. Nonetheless, well-performing hospitals also improved. Modeling morbidity counts, 183 hospitals (2007), avoided ∼9598 potential complications: ∼52/hospital. Due to sampling this may represent only 1 of 5 to 1of 10 of the true total. Improvement reflected aggregate performance across all types of hospitals (academic/community, urban/rural). Changes in patient risk over time had important contributions to the effect. Conclusions: ACS-NSQIP indicates that surgical outcomes improve across all participating hospitals in the private sector. Improvement is reflected for both poor- and well-performing facilities. NSQIP hospitals appear to be avoiding substantial numbers of complications- improving care, and reducing costs. Changes in risk over time merit further study. Several analytic perspectives reflect quality improvement over time by hospitals in the American College of Surgeons National Surgical Quality Improvement Program. Poor-performing hospitals appear most likely to improve, but improvement is seen across all institutions, reflecting substantial numbers of complications avoided. Changes in patient risk appear to make contributions to the effect.

IMPORTANCE: Financial penalties for readmission have been expanded beyond medical conditions to include surgical procedures. Hospitals are working to reduce readmissions; however, little is known about the reasons for surgical readmission. OBJECTIVE: To characterize the reasons, timing, and factors associated with unplanned postoperative readmissions. DESIGN, SETTING, AND PARTICIPANTS: Patients undergoing surgery at one of 346 continuously enrolled US hospitals participating in the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) between January 1, 2012, and December 31, 2012, had clinically abstracted information examined. Readmission rates and reasons (ascertained by clinical data abstractors at each hospital) were assessed for all surgical procedures and for 6 representative operations: bariatric procedures, colectomy or proctectomy, hysterectomy, total hip or knee arthroplasty, ventral hernia repair, and lower extremity vascular bypass. MAIN OUTCOMES AND MEASURES: Unplanned 30-day readmission and reason for readmission. RESULTS: The unplanned readmission rate for the 498,875 operations was 5.7%. For the individual procedures, the readmission rate ranged from 3.8% for hysterectomy to 14.9% for lower extremity vascular bypass. The most common reason for unplanned readmission was surgical site infection (SSI) overall (19.5%) and also after colectomy or proctectomy (25.8%), ventral hernia repair (26.5%), hysterectomy (28.8%), arthroplasty (18.8%), and lower extremity vascular bypass (36.4%). Obstruction or ileus was the most common reason for readmission after bariatric surgery (24.5%) and the second most common reason overall (10.3%), after colectomy or proctectomy (18.1%), ventral hernia repair (16.7%), and hysterectomy (13.4%). Only 2.3% of patients were readmitted for the same complication they had experienced during their index hospitalization. Only 3.3% of patients readmitted for SSIs had experienced an SSI during their index hospitalization. There was no time pattern for readmission, and early (≤7 days postdischarge) and late (>7 days postdischarge) readmissions were associated with the same 3 most common reasons: SSI, ileus or obstruction, and bleeding. Patient comorbidities, index surgical admission complications, non-home discharge (hazard ratio [HR], 1.40 [95% CI, 1.35-1.46]), teaching hospital status (HR, 1.14 [95% CI 1.07-1.21]), and higher surgical volume (HR, 1.15 [95% CI, 1.07-1.25]) were associated with a higher risk of hospital readmission. CONCLUSIONS AND RELEVANCE: Readmissions after surgery were associated with new postdischarge complications related to the procedure and not exacerbation of prior index hospitalization complications, suggesting that readmissions after surgery are a measure of postdischarge complications. These data should be considered when developing quality indicators and any policies penalizing hospitals for surgical readmission.

BACKGROUND: In myocardial ischemia, induction of autophagy via the AMP-induced protein kinase pathway is protective, whereas reperfusion stimulates autophagy with BECLIN-1 upregulation and is implicated in causing cell death. We examined flux through the macroautophagy pathway as a determinant of the discrepant outcomes in cardiomyocyte cell death in this setting. METHODS AND RESULTS: Reversible left anterior descending coronary artery ligation was performed in mice with cardiomyocyte-restricted expression of green fluorescent protein-tagged microtubule-associated protein light chain-3 to induce ischemia (120 minutes) or ischemia/reperfusion (30-90 minutes) with saline or chloroquine pretreatment (n=4 per group). Autophagosome clearance, assessed as the ratio of punctate light chain-3 abundance in saline to chloroquine-treated samples, was markedly impaired with ischemia/reperfusion compared with sham controls. Reoxygenation increased cell death in neonatal rat cardiomyocytes compared with hypoxia alone, markedly increased autophagosomes but not autolysosomes (assessed as punctate dual fluorescent mCherry-green fluorescent protein tandem-tagged light chain-3 expression), and impaired clearance of polyglutamine aggregates, indicating impaired autophagic flux. The resultant autophagosome accumulation was associated with increased reactive oxygen species and mitochondrial permeabilization, leading to cell death, which was attenuated by cyclosporine A pretreatment. Hypoxia-reoxygenation injury was accompanied by reactive oxygen species-mediated BECLIN-1 upregulation and a reduction in lysosome-associated membrane protein-2, a critical determinant of autophagosome-lysosome fusion. Restoration of lysosome-associated membrane protein-2 levels synergizes with partial BECLIN-1 knockdown to restore autophagosome processing and to attenuate cell death after hypoxia-reoxygenation. CONCLUSION: Ischemia/reperfusion injury impairs autophagosome clearance mediated in part by reactive oxygen species-induced decline in lysosome-associated membrane protein-2 and upregulation of BECLIN-1, contributing to increased cardiomyocyte death.

OBJECTIVE: To establish the frequency, pattern and location of cervical lymph node metastases from palpable medullary thyroid carcinoma (MTC). Recommendations are made regarding the extent of surgery for this tumor. SUMMARY BACKGROUND DATA: Medullary thyroid carcinoma is a tumor of neuroendocrine origin that does not concentrate iodine. Surgical extirpation of the thyroid tumor and cervical node metastases is the only potentially curative therapeutic option. Patterns of node metastases in the neck and guidelines for the extent of dissection for palpable MTC are not well established. METHODS: Seventy-three patients underwent thyroidectomy for palpable MTC with immediate or delayed central and bilateral functional neck dissections. The number and location of lymph node metastases in the central (levels VI and VII) and bilateral (levels II to V) nodal groups were noted and were correlated with the size and location of the primary thyroid tumor. Intraoperative assessment of nodal status by palpation and inspection by the surgeon was correlated with results of histologic examination. RESULTS: Patients with unilateral intrathyroid tumors had lymph node metastases in 81% of central node dissections, 81% of ipsilateral functional (levels II to V) dissections, and 44% of contralateral functional (levels II to V) dissections. In patients with bilateral intrathyroid tumors, nodal metastases were present in 78% of central node dissections, 71% of functional (levels II to V) node dissections ipsilateral to the largest intrathyroid tumor, and 49% of functional (levels II to V) node dissections contralateral to the largest thyroid tumor. The sensitivity of the surgeon's intraoperative assessment for nodal metastases was 64%, and the specificity was 71%. CONCLUSION: In this series, >75% of patients with palpable MTC had associated nodal metastases, which often were not apparent to the surgeon. Routine central and bilateral functional neck dissections should be considered in all patients with palpable MTC.

BACKGROUND: Surgical decision-making and informed patient consent both benefit from having accurate information about risk. But currently available risk estimating systems have one or more limitations associated with lack of specificity to operation type, size of sample (reliability), range of outcomes predicted, and appreciation of hospital effects. STUDY DESIGN: Data from the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) patients who underwent colorectal surgery in 2006 to 2007 were used to generate logistic prediction models for 30-day morbidity, serious morbidity, and mortality. Results for these three models were then used to construct a universal multivariable model to predict risk for all three outcomes. Model performance was externally validated against 2005 data. RESULTS: For 2006 to 2007, 28,863 patients were identified who underwent major colorectal operations at 182 hospitals. A single 15-variable predictor model exhibited discrimination (c-statistic) close to that observed for the separate models on all three outcomes. Similar discrimination was found when the 2006 to 2007 universal model was applied to 3,037 operations conducted in 2005 at 37 hospitals. CONCLUSIONS: The ACS NSQIP colorectal risk calculator allows surgeons to preoperatively provide patients with detailed information about their personal risks of overall morbidity, serious morbidity, and mortality. Because ACS NSQIP can also categorize hospitals as performing better or worse than expected (or as expected), surgeons have the opportunity to adjust risk probabilities for patients at their institutions accordingly.

Current prescribing practices for major depressive disorder (MDD) produce limited treatment success. Although pharmacogenomics may improve outcomes by identifying genetically inappropriate medications, studies to date were limited in scope. Outpatients (N = 1167) diagnosed with MDD and with a patient- or clinician-reported inadequate response to at least one antidepressant were enrolled in the Genomics Used to Improve DEpression Decisions (GUIDED) trial - a rater- and patient-blind randomized controlled trial. Patients were randomized to treatment as usual (TAU) or a pharmacogenomics-guided intervention arm in which clinicians had access to a pharmacogenomic test report to inform medication selections (guided-care). Medications were considered congruent ('use as directed' or 'use with caution' test categories) or incongruent ('use with increased caution and with more frequent monitoring' test category) with test results. Unblinding occurred after week 8. Primary outcome was symptom improvement [change in 17-item Hamilton Depression Rating Scale (HAM-D17)] at week 8; secondary outcomes were response (≥50% decrease in HAM-D17) and remission (HAM-D17 ≤ 7) at week 8. At week 8, symptom improvement for guided-care was not significantly different than TAU (27.2% versus 24.4%, p = 0.107); however, improvements in response (26.0% versus 19.9%, p = 0.013) and remission (15.3% versus 10.1%, p = 0.007) were statistically significant. Patients taking incongruent medications prior to baseline who switched to congruent medications by week 8 experienced greater symptom improvement (33.5% versus 21.1%, p = 0.002), response (28.5% versus 16.7%, p = 0.036), and remission (21.5% versus 8.5%, p = 0.007) compared to those remaining incongruent. Pharmacogenomic testing did not significantly improve mean symptoms but did significantly improve response and remission rates for difficult-to-treat depression patients over standard of care (ClinicalTrials.gov NCT02109939).

BACKGROUND: Postoperative respiratory failure (RF) is associated with an increase in hospital morbidity, mortality, cost, and late mortality. We developed and tested a model to predict the risk of postoperative RF in patients undergoing major vascular and general surgical operations. This model is an extension of an earlier model that was derived and tested exclusively from a population of male patients from the Veterans Affairs National Surgical Quality Improvement Program. METHODS: Patients undergoing vascular and general surgical procedures at 14 academic and 128 Veterans Affairs Medical Centers from October 2001 through September 2004 were used to develop and test a predictive model of postoperative RF using logistic regression analyses. RF was defined as postoperative mechanical ventilation for longer than 48 hours or unanticipated reintubation. RESULTS: Of 180,359 patients, 5,389 (3.0%) experienced postoperative RF. Twenty-eight variables were found to be independently associated with RF. Current procedural terminology group, patients with a higher American Society of Anesthesiologists classification, emergency operations, more complex operation (work relative value units), preoperative sepsis, and elevated creatinine were more likely to experience RF. Older patients, male patients, smokers, and those with a history of congestive heart failure or COPD, or both, were also predisposed. The model's discrimination (c-statistic) was excellent, with no decrement from development (0.856) to validation (0.863) samples. CONCLUSIONS: This model updates a previously validated one and is more broadly applicable. Its use to predict postoperative RF risk enables the study of preventative measures or preoperative risk adjustment and intervention to improve outcomes.

Nutrient deprivation has been shown to cause cancer cell death. To exploit nutrient deprivation as anti-cancer therapy, we investigated the effects of the anti-metabolite 2-deoxy-D-glucose on breast cancer cells in vitro. This compound has been shown to inhibit glucose metabolism. Treatment of human breast cancer cell lines with 2-deoxy-D-glucose results in cessation of cell growth in a dose dependent manner. Cell viability as measured by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide conversion assay and clonogenic survival are decreased with 2-deoxy-D-glucose treatment indicating that 2-deoxy-D-glucose causes breast cancer cell death. The cell death induced by 2-deoxy-D-glucose was found to be due to apoptosis as demonstrated by induction of caspase 3 activity and cleavage of poly (ADP-ribose) polymerase. Breast cancer cells treated with 2-deoxy-D-glucose express higher levels of Glut1 transporter protein as measured by Western blot analysis and have increased glucose uptake compared to non-treated breast cancer cells. From these results we conclude that 2-deoxy-D-glucose treatment causes death in human breast cancer cell lines by the activation of the apoptotic pathway. Our data suggest that breast cancer cells treated with 2-deoxy-D-glucose accelerate their own demise by initially expressing high levels of glucose transporter protein, which allows increased uptake of 2-deoxy-D-glucose, and subsequent induction of cell death. These data support the targeting of glucose metabolism as a site for chemotherapeutic intervention by agents such as 2-deoxy-D-glucose.

Most cancer treatment strategies target cell proliferation, angiogenesis, migration, and intravasation of tumor cells in an attempt to limit tumor growth and metastasis. An in vitro platform to assess tumor progression and drug sensitivity could provide avenues to enhance our understanding of tumor metastasis as well as precision medicine. We present a microfluidic platform that mimics biological mass transport near the arterial end of a capillary in the tumor microenvironment. A central feature is a quiescent perfused 3D microvascular network created prior to loading tumor cells or patient-derived tumor organoids in an adjacent compartment. The physiological delivery of nutrients and/or drugs to the tumor then occurs through the vascular network. We demonstrate the culture, growth, and treatment of tumor cell lines and patient-derived breast cancer organoids. The platform provides the opportunity to simultaneously and dynamically observe hallmark features of tumor progression including cell proliferation, angiogenesis, cell migration, and tumor cell intravasation. Additionally, primary breast tumor organoids are viable in the device for several weeks and induce robust sprouting angiogenesis. Finally, we demonstrate the feasibility of our platform for drug discovery and personalized medicine by analyzing the response to chemo- and anti-angiogenic therapy. Precision medicine-based cancer treatments can only be realized if individual tumors can be rapidly assessed for therapeutic sensitivity in a clinically relevant timeframe (⪅14 days). Our platform indicates that this goal can be achieved and provides compelling opportunities to advance precision medicine for cancer.

In Brief Objective: To estimate the effect of preventing postoperative complications on readmission rates and costs. Background: Policymakers are targeting readmission for quality improvement and cost savings. Little is known regarding mutable factors associated with postoperative readmissions. Methods: Patient records (2005–2008) from the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) were linked to Medicare inpatient claims. Risk factors, procedure, and 30-day postoperative complications were determined from ACS-NSQIP. The 30-day postoperative readmission and costs were determined from Medicare. Occurrence of a postoperative complication included surgical site infections and cardiac, pulmonary, neurologic, and renal complications. Multivariate regression models predicted the effect of reducing complication rates on risk-adjusted readmission rates and costs by procedure. Results: The 30-day postoperative readmission rate was 12.8%. Complication rates for readmitted and nonreadmitted patients were 53% and 16% (P < 0.001). Patients with a postoperative complication had higher predicted probability of readmission and cost of readmission than patients without a complication. For the 20 procedures accounting for the greatest number of readmissions, reducing ACS-NSQIP complication rates by a relative 5% could result in prevention of 2092 readmissions per year and a savings to Medicare of $31.0 million per year. Preventing all ACS-NSQIP complications for these procedures could result in prevention of 41,846 readmissions per year and a savings of $620.3 million per year. Conclusions: This study provides substantial evidence that efforts to reduce postoperative readmissions should begin by focusing on postoperative complications that can be reliably and validly measured. Such an approach will not eliminate all postoperative readmissions but will likely have a major effect on readmission rates. Policymakers are targeting readmission for quality improvement and cost savings. This study provides substantial evidence that efforts to reduce postoperative readmissions should begin by focusing on postoperative complications that can be reliably and validly measured. Such an approach will not eliminate all postoperative readmissions but will likely have a major effect on readmission rates.

The goal of breast-conserving surgery is to completely remove all of the cancer. Currently, no intraoperative tools can microscopically analyze the entire lumpectomy specimen, which results in 20 to 60% of patients undergoing second surgeries to achieve clear margins. To address this critical need, we have laid the foundation for the development of a device that could allow accurate intraoperative margin assessment. We demonstrate that by taking advantage of the intrinsic optical contrast of breast tissue, photoacoustic microscopy (PAM) can achieve multilayered histology-like imaging of the tissue surface. The high correlation of the PAM images to the conventional histologic images allows rapid computations of diagnostic features such as nuclear size and packing density, potentially identifying small clusters of cancer cells. Because PAM does not require tissue processing or staining, it can be performed promptly and intraoperatively, enabling immediate directed re-excision and reducing the number of second surgeries.

In sporadic Alzheimer's disease (AD), impaired Aβ removal contributes to elevated extracellular Aβ levels that drive amyloid plaque pathogenesis. Extracellular proteolysis, export across the blood-brain barrier, and cellular uptake facilitate physiologic Aβ clearance. Astrocytes can take up and degrade Aβ, but it remains unclear whether this function is insufficient in AD or can be enhanced to accelerate Aβ removal. Additionally, age-related dysfunction of lysosomes, the major degradative organelles wherein Aβ localizes after uptake, has been implicated in amyloid plaque pathogenesis. We tested the hypothesis that enhancing lysosomal function in astrocytes with transcription factor EB (TFEB), a master regulator of lysosome biogenesis, would promote Aβ uptake and catabolism and attenuate plaque pathogenesis. Exogenous TFEB localized to the nucleus with transcriptional induction of lysosomal biogenesis and function in vitro. This resulted in significantly accelerated uptake of exogenously applied Aβ42, with increased localization to and degradation within lysosomes in C17.2 cells and primary astrocytes, indicating that TFEB is sufficient to coordinately enhance uptake, trafficking, and degradation of Aβ. Stereotactic injection of adeno-associated viral particles carrying TFEB driven by a glial fibrillary acidic protein promoter was used to achieve astrocyte-specific expression in the hippocampus of APP/PS1 transgenic mice. Exogenous TFEB localized to astrocyte nuclei and enhanced lysosome function, resulting in reduced Aβ levels and shortened half-life in the brain interstitial fluid and reduced amyloid plaque load in the hippocampus compared with control virus-injected mice. Therefore, activation of TFEB in astrocytes is an effective strategy to restore adequate Aβ removal and counter amyloid plaque pathogenesis in AD.

Abstract Fifty-seven hypertensive patients who ingested from 200 to 3,000 Gm. of hydralazine during 1 to 15 years were studied in search of factors related to delayed hydralazine toxicity, minimal manifestations of which were considered to be arthralgia plus elevated cephalin cholesterol flocculation of the plasma. Throughout the study blood pressure was measured and circulating cells and proteins were examined. At the end of the study the presence of serum antinuclear antibodies (ANA) was determined by a fluorescent antibody technique and the activity of hepatic acetyl transferase, an enzyme which metabolizes hydralazine, was assayed. The patients could be divided into 33 and 24 fast acetylators of hydralazine, and 31 of the 57 were found to have ANA. During the study 12 patients had symptoms of hydralazine toxicity; all 12 belonged to the Caucasian race, were slow acetylators, and had ANA. Almost half of the nontoxic patients also had ANA, with the incidence being the same for Negro as for Caucasian patients. The data suggested that ANA might develop with less exposure to hydralazine in than fast acetylators. Good control of blood pressure accompanied drug toxicity, but toxic symptoms could not be related to severity of hypertension before treatment or to anemia, leukopenia, or hyperglobulinemia during treatment.

Two cases of a previously undescribed tumor were studied. The lesion is a primary pancreatic neoplasm, which by light microscopy has an appearance indistinguishable from that of a giant cell tumor of bone. Electron microscopy was done in one of the two cases. Both giant and “stromal” cells have abundant granular endoplasmic reticulum containing intracisternal granules of proteic nature similar to those described in pancreatic acinar cells. Microvilli are present in the giant cells, and numerous desmosomes are found between the “stromal” cells. These features are strongly suggestive that epithelial—and specifically acinar—elements are the cells of origin of the tumor.

) is an interferon (IFN)-stimulated gene that shows broad antiviral activities against a wide range of enveloped viruses. Here, using an IFN-stimulated gene screen against vesicular stomatitis virus (VSV)-SARS-CoV and VSV-SARS-CoV-2 chimeric viruses, we identified CH25H and its enzymatic product 25-hydroxycholesterol (25HC) as potent inhibitors of SARS-CoV-2 replication. Internalized 25HC accumulates in the late endosomes and potentially restricts SARS-CoV-2 spike protein catalyzed membrane fusion via blockade of cholesterol export. Our results highlight one of the possible antiviral mechanisms of 25HC and provide the molecular basis for its therapeutic development.

In AD, an imbalance between Aβ production and removal drives elevated brain Aβ levels and eventual amyloid plaque deposition. APP undergoes nonamyloidogenic processing via α-cleavage at the plasma membrane, amyloidogenic β- and γ-cleavage within endosomes to generate Aβ, or lysosomal degradation in neurons. Considering multiple reports implicating impaired lysosome function as a driver of increased amyloidogenic processing of APP, we explored the efficacy of targeting transcription factor EB (TFEB), a master regulator of lysosomal pathways, to reduce Aβ levels. CMV promoter-driven TFEB, transduced via stereotactic hippocampal injections of adeno-associated virus particles in APP/PS1 mice, localized primarily to neuronal nuclei and upregulated lysosome biogenesis. This resulted in reduction of APP protein, the α and β C-terminal APP fragments (CTFs), and in the steady-state Aβ levels in the brain interstitial fluid. In aged mice, total Aβ levels and amyloid plaque load were selectively reduced in the TFEB-transduced hippocampi. TFEB transfection in N2a cells stably expressing APP695, stimulated lysosome biogenesis, reduced steady-state levels of APP and α- and β-CTFs, and attenuated Aβ generation by accelerating flux through the endosome-lysosome pathway. Cycloheximide chase assays revealed a shortening of APP half-life with exogenous TFEB expression, which was prevented by concomitant inhibition of lysosomal acidification. These data indicate that TFEB enhances flux through lysosomal degradative pathways to induce APP degradation and reduce Aβ generation. Activation of TFEB in neurons is an effective strategy to attenuate Aβ generation and attenuate amyloid plaque deposition in AD. SIGNIFICANCE STATEMENT: A key driver for AD pathogenesis is the net balance between production and clearance of Aβ, the major component of amyloid plaques. Here we demonstrate that lysosomal degradation of holo-APP influences Aβ production by limiting the availability of APP for amyloidogenic processing. Using viral gene transfer of transcription factor EB (TFEB), a master regulator of lysosome biogenesis in neurons of APP/PS1 mice, steady-state levels of APP were reduced, resulting in decreased interstitial fluid Aβ levels and attenuated amyloid deposits. These effects were caused by accelerated lysosomal degradation of endocytosed APP, reflected by reduced APP half-life and steady-state levels in TFEB-expressing cells, with resultant decrease in Aβ production and release. Additional studies are needed to explore the therapeutic potential of this approach.

Our website uses cookies to enhance your experience. By continuing to use our site, or clicking "Continue," you are agreeing to our Cookie Policy | Continue JAMA Psychiatry HomeNew OnlineCurrent IssueFor Authors Podcast Publications JAMA JAMA Network Open JAMA Cardiology JAMA Dermatology JAMA Health Forum JAMA Internal Medicine JAMA Neurology JAMA Oncology JAMA Ophthalmology JAMA Otolaryngology–Head & Neck Surgery JAMA Pediatrics JAMA Psychiatry JAMA Surgery Archives of Neurology & Psychiatry (1919-1959) JN Learning / CMESubscribeJobsInstitutions / LibrariansReprints & Permissions Terms of Use | Privacy Policy | Accessibility Statement 2023 American Medical Association. All Rights Reserved Search All JAMA JAMA Network Open JAMA Cardiology JAMA Dermatology JAMA Forum Archive JAMA Health Forum JAMA Internal Medicine JAMA Neurology JAMA Oncology JAMA Ophthalmology JAMA Otolaryngology–Head & Neck Surgery JAMA Pediatrics JAMA Psychiatry JAMA Surgery Archives of Neurology & Psychiatry Input Search Term Sign In Individual Sign In Sign inCreate an Account Access through your institution Sign In Purchase Options: Buy this article Rent this article Subscribe to the JAMA Psychiatry journal