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Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: machine learning approach – CORRIGENDUM
- Micah Cearns, Azmeraw T. Amare, Klaus Oliver Schubert, Anbupalam Thalamuthu, Joseph Frank, Fabian Streit, Mazda Adli, Nirmala Akula, Kazufumi Akiyama, Raffaella Ardau, Bárbara Arias, JeanMichel Aubry, Lena Backlund, Abesh Kumar Bhattacharjee, Frank Bellivier, Antonio Benabarre, Susanne Bengesser, Joanna M. Biernacka, Armin Birner, Clara Brichant-Petitjean, Pablo Cervantes, HsiChung Chen, Caterina Chillotti, Sven Cichon, Cristiana Cruceanu, Piotr M. Czerski, Nina Dalkner, Alexandre Dayer, Franziska Degenhardt, Maria Del Zompo, J. Raymond DePaulo, Bruno Étain, Peter Falkai, Andreas J. Forstner, Louise Frisen, Mark A. Frye, Janice M. Fullerton, Sébastien Gard, Julie S. Garnham, Fernando S. Goes, Maria Grigoroiu-Serbanescu, Paul Grof, Ryota Hashimoto, Joanna Hauser, Urs Heilbronner, Stefan Herms, Per Hoffmann, Andrea Hofmann, Liping Hou, Yi-Hsiang Hsu, Stephane Jamain, Esther Jiménez, Jean-Pierre Kahn, Layla Kassem, Po-Hsiu Kuo, Tadafumi Kato, John Kelsoe, Sarah Kittel-Schneider, Sebastian Kliwicki, Barbara König, Ichiro Kusumi, Gonzalo Laje, Mikael Landén, Catharina Lavebratt, Marion Leboyer, Susan G. Leckband, Mario Maj, the Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Mirko Manchia, Lina Martinsson, Michael J. McCarthy, Susan McElroy, Francesc Colom, Marina Mitjans, Francis M. Mondimore, Palmiero Monteleone, Caroline M. Nievergelt, Markus M. Nöthen, Tomas Novák, Claire O'Donovan, Norio Ozaki, Vincent Millischer, Sergi Papiol, Andrea Pfennig, Claudia Pisanu, James B. Potash, Andreas Reif, Eva Reininghaus, Guy A. Rouleau, Janusz K. Rybakowski, Martin Schalling, Peter R. Schofield, Barbara W. Schweizer, Giovanni Severino, Tatyana Shekhtman, Paul D. Shilling, Katzutaka Shimoda, Christian Simhandl, Claire M. Slaney, Alessio Squassina, Thomas Stamm, Pavla Stopkova, Fasil TekolaAyele, Alfonso Tortorella, Gustavo Turecki, Julia Veeh, Eduard Vieta, Stephanie H. Witt, Gloria Roberts, Peter P. Zandi, Martin Alda, Michael Bauer, Francis J. McMahon, Philip B. Mitchell, Thomas G. Schulze, Marcella Rietschel, Scott R. Clark, Bernhard T. Baune
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- Journal:
- The British Journal of Psychiatry / Volume 221 / Issue 2 / August 2022
- Published online by Cambridge University Press:
- 04 May 2022, p. 494
- Print publication:
- August 2022
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Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: machine learning approach
- Micah Cearns, Azmeraw T. Amare, Klaus Oliver Schubert, Anbupalam Thalamuthu, Joseph Frank, Fabian Streit, Mazda Adli, Nirmala Akula, Kazufumi Akiyama, Raffaella Ardau, Bárbara Arias, Jean-Michel Aubry, Lena Backlund, Abesh Kumar Bhattacharjee, Frank Bellivier, Antonio Benabarre, Susanne Bengesser, Joanna M. Biernacka, Armin Birner, Clara Brichant-Petitjean, Pablo Cervantes, Hsi-Chung Chen, Caterina Chillotti, Sven Cichon, Cristiana Cruceanu, Piotr M. Czerski, Nina Dalkner, Alexandre Dayer, Franziska Degenhardt, Maria Del Zompo, J. Raymond DePaulo, Bruno Étain, Peter Falkai, Andreas J. Forstner, Louise Frisen, Mark A. Frye, Janice M. Fullerton, Sébastien Gard, Julie S. Garnham, Fernando S. Goes, Maria Grigoroiu-Serbanescu, Paul Grof, Ryota Hashimoto, Joanna Hauser, Urs Heilbronner, Stefan Herms, Per Hoffmann, Andrea Hofmann, Liping Hou, Yi-Hsiang Hsu, Stephane Jamain, Esther Jiménez, Jean-Pierre Kahn, Layla Kassem, Po-Hsiu Kuo, Tadafumi Kato, John Kelsoe, Sarah Kittel-Schneider, Sebastian Kliwicki, Barbara König, Ichiro Kusumi, Gonzalo Laje, Mikael Landén, Catharina Lavebratt, Marion Leboyer, Susan G. Leckband, Mario Maj, the Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Mirko Manchia, Lina Martinsson, Michael J. McCarthy, Susan McElroy, Francesc Colom, Marina Mitjans, Francis M. Mondimore, Palmiero Monteleone, Caroline M. Nievergelt, Markus M. Nöthen, Tomas Novák, Claire O'Donovan, Norio Ozaki, Vincent Millischer, Sergi Papiol, Andrea Pfennig, Claudia Pisanu, James B. Potash, Andreas Reif, Eva Reininghaus, Guy A. Rouleau, Janusz K. Rybakowski, Martin Schalling, Peter R. Schofield, Barbara W. Schweizer, Giovanni Severino, Tatyana Shekhtman, Paul D. Shilling, Katzutaka Shimoda, Christian Simhandl, Claire M. Slaney, Alessio Squassina, Thomas Stamm, Pavla Stopkova, Fasil Tekola-Ayele, Alfonso Tortorella, Gustavo Turecki, Julia Veeh, Eduard Vieta, Stephanie H. Witt, Gloria Roberts, Peter P. Zandi, Martin Alda, Michael Bauer, Francis J. McMahon, Philip B. Mitchell, Thomas G. Schulze, Marcella Rietschel, Scott R. Clark, Bernhard T. Baune
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- Journal:
- The British Journal of Psychiatry / Volume 220 / Issue 4 / April 2022
- Published online by Cambridge University Press:
- 28 February 2022, pp. 219-228
- Print publication:
- April 2022
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Background
Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.
AimsTo use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.
MethodThis study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.
ResultsThe best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.
ConclusionsUsing PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.
Characterisation of age and polarity at onset in bipolar disorder
- Janos L. Kalman, Loes M. Olde Loohuis, Annabel Vreeker, Andrew McQuillin, Eli A. Stahl, Douglas Ruderfer, Maria Grigoroiu-Serbanescu, Georgia Panagiotaropoulou, Stephan Ripke, Tim B. Bigdeli, Frederike Stein, Tina Meller, Susanne Meinert, Helena Pelin, Fabian Streit, Sergi Papiol, Mark J. Adams, Rolf Adolfsson, Kristina Adorjan, Ingrid Agartz, Sofie R. Aminoff, Heike Anderson-Schmidt, Ole A. Andreassen, Raffaella Ardau, Jean-Michel Aubry, Ceylan Balaban, Nicholas Bass, Bernhard T. Baune, Frank Bellivier, Antoni Benabarre, Susanne Bengesser, Wade H Berrettini, Marco P. Boks, Evelyn J. Bromet, Katharina Brosch, Monika Budde, William Byerley, Pablo Cervantes, Catina Chillotti, Sven Cichon, Scott R. Clark, Ashley L. Comes, Aiden Corvin, William Coryell, Nick Craddock, David W. Craig, Paul E. Croarkin, Cristiana Cruceanu, Piotr M. Czerski, Nina Dalkner, Udo Dannlowski, Franziska Degenhardt, Maria Del Zompo, J. Raymond DePaulo, Srdjan Djurovic, Howard J. Edenberg, Mariam Al Eissa, Torbjørn Elvsåshagen, Bruno Etain, Ayman H. Fanous, Frederike Fellendorf, Alessia Fiorentino, Andreas J. Forstner, Mark A. Frye, Janice M. Fullerton, Katrin Gade, Julie Garnham, Elliot Gershon, Michael Gill, Fernando S. Goes, Katherine Gordon-Smith, Paul Grof, Jose Guzman-Parra, Tim Hahn, Roland Hasler, Maria Heilbronner, Urs Heilbronner, Stephane Jamain, Esther Jimenez, Ian Jones, Lisa Jones, Lina Jonsson, Rene S. Kahn, John R. Kelsoe, James L. Kennedy, Tilo Kircher, George Kirov, Sarah Kittel-Schneider, Farah Klöhn-Saghatolislam, James A. Knowles, Thorsten M. Kranz, Trine Vik Lagerberg, Mikael Landen, William B. Lawson, Marion Leboyer, Qingqin S. Li, Mario Maj, Dolores Malaspina, Mirko Manchia, Fermin Mayoral, Susan L. McElroy, Melvin G. McInnis, Andrew M. McIntosh, Helena Medeiros, Ingrid Melle, Vihra Milanova, Philip B. Mitchell, Palmiero Monteleone, Alessio Maria Monteleone, Markus M. Nöthen, Tomas Novak, John I. Nurnberger, Niamh O'Brien, Kevin S. O'Connell, Claire O'Donovan, Michael C. O'Donovan, Nils Opel, Abigail Ortiz, Michael J. Owen, Erik Pålsson, Carlos Pato, Michele T. Pato, Joanna Pawlak, Julia-Katharina Pfarr, Claudia Pisanu, James B. Potash, Mark H Rapaport, Daniela Reich-Erkelenz, Andreas Reif, Eva Reininghaus, Jonathan Repple, Hélène Richard-Lepouriel, Marcella Rietschel, Kai Ringwald, Gloria Roberts, Guy Rouleau, Sabrina Schaupp, William A Scheftner, Simon Schmitt, Peter R. Schofield, K. Oliver Schubert, Eva C. Schulte, Barbara Schweizer, Fanny Senner, Giovanni Severino, Sally Sharp, Claire Slaney, Olav B. Smeland, Janet L. Sobell, Alessio Squassina, Pavla Stopkova, John Strauss, Alfonso Tortorella, Gustavo Turecki, Joanna Twarowska-Hauser, Marin Veldic, Eduard Vieta, John B. Vincent, Wei Xu, Clement C. Zai, Peter P. Zandi, Psychiatric Genomics Consortium (PGC) Bipolar Disorder Working Group, International Consortium on Lithium Genetics (ConLiGen), Colombia-US Cross Disorder Collaboration in Psychiatric Genetics, Arianna Di Florio, Jordan W. Smoller, Joanna M. Biernacka, Francis J. McMahon, Martin Alda, Bertram Müller-Myhsok, Nikolaos Koutsouleris, Peter Falkai, Nelson B. Freimer, Till F.M. Andlauer, Thomas G. Schulze, Roel A. Ophoff
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- Journal:
- The British Journal of Psychiatry / Volume 219 / Issue 6 / December 2021
- Published online by Cambridge University Press:
- 25 August 2021, pp. 659-669
- Print publication:
- December 2021
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Background
Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.
AimsTo examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.
MethodGenome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.
ResultsEarlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.
ConclusionsAAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.
Cosmology with Phase 1 of the Square Kilometre Array Red Book 2018: Technical specifications and performance forecasts
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- Square Kilometre Array Cosmology Science Working Group:, David J. Bacon, Richard A. Battye, Philip Bull, Stefano Camera, Pedro G. Ferreira, Ian Harrison, David Parkinson, Alkistis Pourtsidou, Mário G. Santos, Laura Wolz, Filipe Abdalla, Yashar Akrami, David Alonso, Sambatra Andrianomena, Mario Ballardini, José Luis Bernal, Daniele Bertacca, Carlos A. P. Bengaly, Anna Bonaldi, Camille Bonvin, Michael L. Brown, Emma Chapman, Song Chen, Xuelei Chen, Steven Cunnington, Tamara M. Davis, Clive Dickinson, José Fonseca, Keith Grainge, Stuart Harper, Matt J. Jarvis, Roy Maartens, Natasha Maddox, Hamsa Padmanabhan, Jonathan R. Pritchard, Alvise Raccanelli, Marzia Rivi, Sambit Roychowdhury, Martin Sahlén, Dominik J. Schwarz, Thilo M. Siewert, Matteo Viel, Francisco Villaescusa-Navarro, Yidong Xu, Daisuke Yamauchi, Joe Zuntz
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- Journal:
- Publications of the Astronomical Society of Australia / Volume 37 / 2020
- Published online by Cambridge University Press:
- 06 March 2020, e007
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We present a detailed overview of the cosmological surveys that we aim to carry out with Phase 1 of the Square Kilometre Array (SKA1) and the science that they will enable. We highlight three main surveys: a medium-deep continuum weak lensing and low-redshift spectroscopic HI galaxy survey over 5 000 deg2; a wide and deep continuum galaxy and HI intensity mapping (IM) survey over 20 000 deg2 from $z = 0.35$ to 3; and a deep, high-redshift HI IM survey over 100 deg2 from $z = 3$ to 6. Taken together, these surveys will achieve an array of important scientific goals: measuring the equation of state of dark energy out to $z \sim 3$ with percent-level precision measurements of the cosmic expansion rate; constraining possible deviations from General Relativity on cosmological scales by measuring the growth rate of structure through multiple independent methods; mapping the structure of the Universe on the largest accessible scales, thus constraining fundamental properties such as isotropy, homogeneity, and non-Gaussianity; and measuring the HI density and bias out to $z = 6$ . These surveys will also provide highly complementary clustering and weak lensing measurements that have independent systematic uncertainties to those of optical and near-infrared (NIR) surveys like Euclid, LSST, and WFIRST leading to a multitude of synergies that can improve constraints significantly beyond what optical or radio surveys can achieve on their own. This document, the 2018 Red Book, provides reference technical specifications, cosmological parameter forecasts, and an overview of relevant systematic effects for the three key surveys and will be regularly updated by the Cosmology Science Working Group in the run up to start of operations and the Key Science Programme of SKA1.
2307: Resting state network profiles of Alzheimer disease and frontotemporal dementia: A preliminary examination
- Joey Annette Contreras, Shannon L. Risacher, Mario Dzemidzic, John D. West, Brenna C. McDonald, Martin R. Farlow, Brandy R. Matthews, Liana G. Apostolova, Jared Brosch, Bernard Ghetti, Joaquin GoÑi
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- Journal:
- Journal of Clinical and Translational Science / Volume 1 / Issue S1 / September 2017
- Published online by Cambridge University Press:
- 10 May 2018, p. 6
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OBJECTIVES/SPECIFIC AIMS: Recent evidence from resting-state fMRI studies have shown that brain network connectivity is altered in patients with neurodegenerative disorders. However, few studies have examined the complete connectivity patterns of these well-reported RSNs using a whole brain approach and how they compare between dementias. Here, we used advanced connectomic approaches to examine the connectivity of RSNs in Alzheimer disease (AD), Frontotemporal dementia (FTD), and age-matched control participants. METHODS/STUDY POPULATION: In total, 44 participants [27 controls (66.4±7.6 years), 13 AD (68.5.63±13.9 years), 4 FTD (59.575±12.2 years)] from an ongoing study at Indiana University School of Medicine were used. Resting-state fMRI data was processed using an in-house pipeline modeled after Power et al. (2014). Images were parcellated into 278 regions of interest (ROI) based on Shen et al. (2013). Connectivity between each ROI pair was described by Pearson correlation coefficient. Brain regions were grouped into 7 canonical RSNs as described by Yeo et al. (2015). Pearson correlation values were then averaged across pairs of ROIs in each network and averaged across individuals in each group. These values were used to determine relative expression of FC in each RSN (intranetwork) and create RSN profiles for each group. RESULTS/ANTICIPATED RESULTS: Our findings support previous literature which shows that limbic networks are disrupted in FTLD participants compared with AD and age-matched controls. In addition, interactions between different RSNs was also examined and a significant difference between controls and AD subjects was found between FP and DMN RSNs. Similarly, previous literature has reported a disruption between executive (frontoparietal) network and default mode network in AD compared with controls. DISCUSSION/SIGNIFICANCE OF IMPACT: Our approach allows us to create profiles that could help compare intranetwork FC in different neurodegenerative diseases. Future work with expanded samples will help us to draw more substantial conclusions regarding differences, if any, in the connectivity patterns between RSNs in various neurodegenerative diseases.
Weed Control and Dry Bean (Phaseolus vulgaris) Response to In-Row Cultivation, Rotary Hoeing, and Herbicides
- Mario D. Amador-Ramirez, Robert G. Wilson, Alex R. Martin
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- Journal:
- Weed Technology / Volume 15 / Issue 3 / September 2001
- Published online by Cambridge University Press:
- 20 January 2017, pp. 429-436
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Field experiments were conducted in 1996 and 1997 to evaluate weed control and dry bean response to mechanical tillage and herbicide treatments. Herbicide treatments were EPTC plus ethalfluralin, dimethenamid, and imazethapyr plus bentazon. Herbicides were applied alone or combined with rotary hoeing and in-row cultivation. Differences in dry bean yields between years were due to differences in weed density. Weed species included redroot pigweed, common lambsquarters, hairy nightshade, wild proso millet, and green foxtail. Weed density in the untreated check plots at the end of the growing season was 35 plants/m2 in 1996 and 134 plants/m2 in 1997. Dry bean stands were not reduced by rotary hoeing, in-row cultivation, and herbicides in 1996, but in-row cultivation reduced dry bean populations 27% compared to the hand-weeded check in 1997. In-row cultivation and rotary hoeing provided similar weed control in both years. At low weed densities, either mechanical tillage or herbicides alone were effective in suppressing weeds, whereas at higher densities, herbicides combined with mechanical tillage were required for effective control.
Effect of in-row cultivation, herbicides, and dry bean canopy on weed seedling emergence
- Mario D. Amador-Ramirez, Robert G. Wilson, Alex R. Martin
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- Journal:
- Weed Science / Volume 50 / Issue 3 / June 2002
- Published online by Cambridge University Press:
- 20 January 2017, pp. 370-377
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Field experiments were conducted in 1996 and 1997 to evaluate the effect of EPTC (S-ethyl dipropyl carbamothioate) plus ethalfluralin at 2.4 plus 0.83 kg ai ha−1, rotary hoeing, in-row cultivation, rotary hoeing plus in-row cultivation, and dry bean canopy on weed seedling emergence. Cumulative weed emergence in 1996 and 1997 was similar in cropped and noncropped areas. Herbicides were more effective than mechanical cultivation in reducing weed emergence 91% in 1996 and 88% in 1997. Weed emergence was similar in both rotary hoed area and cultivated area in 1996 but weed emergence was 44% lower in rotary hoed plots than in cultivated plots in 1997. The Gompertz equation did not adequately predict weed seedling emergence in the untreated control and with in-row cultivation in 1996. Initial weed seedling emergence was observed at about 120 growing degree-days with 3 to 9% cumulative emergence among treatments. In 1997, the Gompertz equation adequately described weed seedling emergence in plots with or without disturbed soil. Weed emergence was first observed at 80 growing degree-days with 6 to 16% cumulative emergence among treatments. Predicted percent weed emergence closely approximated observed emergence in 1996 and 1997. Rotary hoeing plus in-row cultivation reduced maximum percent emergence rate 37% on an average. The greater maximum percent emergence rate obtained with in-row cultivation suggests that this treatment increased weed seedling emergence in 1997. On average, weed seedling emergence in the untreated check was lower in cropped areas than in noncropped areas, implying a competitive effect by the dry bean crop. Although weed seedling emergence occurred throughout the growing season, more weed seedlings emerged in June and early July than in late July and August.
Delirium in elderly patients: association with educational attainment
- Sónia Martins, José Artur Paiva, Mário R. Simões, Lia Fernandes
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- Journal:
- Acta Neuropsychiatrica / Volume 29 / Issue 2 / April 2017
- Published online by Cambridge University Press:
- 09 August 2016, pp. 95-101
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Objective
Among cognitive reserve markers, educational attainment is the most widely studied, with several studies establishing a strong association with risk of dementia. However, it has not yet been fully examined in delirium. This study aims to analyse the relationship between educational attainment and delirium.
MethodsThe study included elderly hospitalised patients admitted (≥48 h) into an intermediate care unit (IMCU) of Intensive Care Medicine Service. Exclusion criteria were as follows: Glasgow Coma Scale (total≤11), blindness/deafness, inability to communicate or to speak Portuguese. The European Portuguese Version of the Confusion Assessment Method (CAM) was used for delirium assessment.
ResultsThe final sample (n=157) had a mean age of 78.8 (SD=7.6) the majority being female (52.2%), married (51.5%) and with low educational level (49%). According to CAM, 21% of the patients had delirium. The delirium group presented the fewest years of education (median 1 vs. 4), with statistical significance (p=0.003). Delirium was more frequent among male patients [odds ratio (OR) 0.32; 95% confidence interval (CI) 0.12–0.86; p=0.023], as well as those patients with lower education (OR 0.76; 95% CI 0.62–0.95; p=0.016), and with respiratory disease (OR 3.35; 95% CI 1.20–9.33; p=0.020), after controlling for age and medication.
ConclusionSimilar to previous studies, these findings point to a negative correlation between education and delirium. This study appears as an attempt to contribute to the knowledge about the role of cognitive reserve in risk of delirium, particularly because is the first one that has been carried out in an IMCU, with lower educated elderly patients. Further studies are needed to clarify this relationship considering other markers (e.g. cognitive activities), which can contribute to the definition of preventive strategies.
Contributors
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- By Mitchell Aboulafia, Frederick Adams, Marilyn McCord Adams, Robert M. Adams, Laird Addis, James W. Allard, David Allison, William P. Alston, Karl Ameriks, C. Anthony Anderson, David Leech Anderson, Lanier Anderson, Roger Ariew, David Armstrong, Denis G. Arnold, E. J. Ashworth, Margaret Atherton, Robin Attfield, Bruce Aune, Edward Wilson Averill, Jody Azzouni, Kent Bach, Andrew Bailey, Lynne Rudder Baker, Thomas R. Baldwin, Jon Barwise, George Bealer, William Bechtel, Lawrence C. Becker, Mark A. Bedau, Ernst Behler, José A. Benardete, Ermanno Bencivenga, Jan Berg, Michael Bergmann, Robert L. Bernasconi, Sven Bernecker, Bernard Berofsky, Rod Bertolet, Charles J. Beyer, Christian Beyer, Joseph Bien, Joseph Bien, Peg Birmingham, Ivan Boh, James Bohman, Daniel Bonevac, Laurence BonJour, William J. Bouwsma, Raymond D. Bradley, Myles Brand, Richard B. Brandt, Michael E. Bratman, Stephen E. Braude, Daniel Breazeale, Angela Breitenbach, Jason Bridges, David O. Brink, Gordon G. Brittan, Justin Broackes, Dan W. Brock, Aaron Bronfman, Jeffrey E. Brower, Bartosz Brozek, Anthony Brueckner, Jeffrey Bub, Lara Buchak, Otavio Bueno, Ann E. Bumpus, Robert W. Burch, John Burgess, Arthur W. Burks, Panayot Butchvarov, Robert E. Butts, Marina Bykova, Patrick Byrne, David Carr, Noël Carroll, Edward S. Casey, Victor Caston, Victor Caston, Albert Casullo, Robert L. Causey, Alan K. L. Chan, Ruth Chang, Deen K. Chatterjee, Andrew Chignell, Roderick M. Chisholm, Kelly J. Clark, E. J. Coffman, Robin Collins, Brian P. Copenhaver, John Corcoran, John Cottingham, Roger Crisp, Frederick J. Crosson, Antonio S. Cua, Phillip D. Cummins, Martin Curd, Adam Cureton, Andrew Cutrofello, Stephen Darwall, Paul Sheldon Davies, Wayne A. Davis, Timothy Joseph Day, Claudio de Almeida, Mario De Caro, Mario De Caro, John Deigh, C. F. Delaney, Daniel C. Dennett, Michael R. DePaul, Michael Detlefsen, Daniel Trent Devereux, Philip E. Devine, John M. Dillon, Martin C. Dillon, Robert DiSalle, Mary Domski, Alan Donagan, Paul Draper, Fred Dretske, Mircea Dumitru, Wilhelm Dupré, Gerald Dworkin, John Earman, Ellery Eells, Catherine Z. Elgin, Berent Enç, Ronald P. Endicott, Edward Erwin, John Etchemendy, C. Stephen Evans, Susan L. Feagin, Solomon Feferman, Richard Feldman, Arthur Fine, Maurice A. Finocchiaro, William FitzPatrick, Richard E. Flathman, Gvozden Flego, Richard Foley, Graeme Forbes, Rainer Forst, Malcolm R. Forster, Daniel Fouke, Patrick Francken, Samuel Freeman, Elizabeth Fricker, Miranda Fricker, Michael Friedman, Michael Fuerstein, Richard A. Fumerton, Alan Gabbey, Pieranna Garavaso, Daniel Garber, Jorge L. A. Garcia, Robert K. Garcia, Don Garrett, Philip Gasper, Gerald Gaus, Berys Gaut, Bernard Gert, Roger F. Gibson, Cody Gilmore, Carl Ginet, Alan H. Goldman, Alvin I. Goldman, Alfonso Gömez-Lobo, Lenn E. Goodman, Robert M. Gordon, Stefan Gosepath, Jorge J. E. Gracia, Daniel W. Graham, George A. Graham, Peter J. Graham, Richard E. Grandy, I. Grattan-Guinness, John Greco, Philip T. Grier, Nicholas Griffin, Nicholas Griffin, David A. Griffiths, Paul J. Griffiths, Stephen R. Grimm, Charles L. Griswold, Charles B. Guignon, Pete A. Y. Gunter, Dimitri Gutas, Gary Gutting, Paul Guyer, Kwame Gyekye, Oscar A. Haac, Raul Hakli, Raul Hakli, Michael Hallett, Edward C. Halper, Jean Hampton, R. James Hankinson, K. R. Hanley, Russell Hardin, Robert M. Harnish, William Harper, David Harrah, Kevin Hart, Ali Hasan, William Hasker, John Haugeland, Roger Hausheer, William Heald, Peter Heath, Richard Heck, John F. Heil, Vincent F. Hendricks, Stephen Hetherington, Francis Heylighen, Kathleen Marie Higgins, Risto Hilpinen, Harold T. Hodes, Joshua Hoffman, Alan Holland, Robert L. Holmes, Richard Holton, Brad W. Hooker, Terence E. Horgan, Tamara Horowitz, Paul Horwich, Vittorio Hösle, Paul Hoβfeld, Daniel Howard-Snyder, Frances Howard-Snyder, Anne Hudson, Deal W. Hudson, Carl A. Huffman, David L. Hull, Patricia Huntington, Thomas Hurka, Paul Hurley, Rosalind Hursthouse, Guillermo Hurtado, Ronald E. Hustwit, Sarah Hutton, Jonathan Jenkins Ichikawa, Harry A. Ide, David Ingram, Philip J. Ivanhoe, Alfred L. Ivry, Frank Jackson, Dale Jacquette, Joseph Jedwab, Richard Jeffrey, David Alan Johnson, Edward Johnson, Mark D. Jordan, Richard Joyce, Hwa Yol Jung, Robert Hillary Kane, Tomis Kapitan, Jacquelyn Ann K. Kegley, James A. Keller, Ralph Kennedy, Sergei Khoruzhii, Jaegwon Kim, Yersu Kim, Nathan L. King, Patricia Kitcher, Peter D. Klein, E. D. Klemke, Virginia Klenk, George L. Kline, Christian Klotz, Simo Knuuttila, Joseph J. Kockelmans, Konstantin Kolenda, Sebastian Tomasz Kołodziejczyk, Isaac Kramnick, Richard Kraut, Fred Kroon, Manfred Kuehn, Steven T. Kuhn, Henry E. Kyburg, John Lachs, Jennifer Lackey, Stephen E. Lahey, Andrea Lavazza, Thomas H. Leahey, Joo Heung Lee, Keith Lehrer, Dorothy Leland, Noah M. Lemos, Ernest LePore, Sarah-Jane Leslie, Isaac Levi, Andrew Levine, Alan E. Lewis, Daniel E. Little, Shu-hsien Liu, Shu-hsien Liu, Alan K. L. Chan, Brian Loar, Lawrence B. Lombard, John Longeway, Dominic McIver Lopes, Michael J. Loux, E. J. Lowe, Steven Luper, Eugene C. Luschei, William G. Lycan, David Lyons, David Macarthur, Danielle Macbeth, Scott MacDonald, Jacob L. Mackey, Louis H. Mackey, Penelope Mackie, Edward H. Madden, Penelope Maddy, G. B. Madison, Bernd Magnus, Pekka Mäkelä, Rudolf A. Makkreel, David Manley, William E. Mann (W.E.M.), Vladimir Marchenkov, Peter Markie, Jean-Pierre Marquis, Ausonio Marras, Mike W. Martin, A. P. Martinich, William L. McBride, David McCabe, Storrs McCall, Hugh J. McCann, Robert N. McCauley, John J. McDermott, Sarah McGrath, Ralph McInerny, Daniel J. McKaughan, Thomas McKay, Michael McKinsey, Brian P. McLaughlin, Ernan McMullin, Anthonie Meijers, Jack W. Meiland, William Jason Melanson, Alfred R. Mele, Joseph R. Mendola, Christopher Menzel, Michael J. Meyer, Christian B. Miller, David W. Miller, Peter Millican, Robert N. Minor, Phillip Mitsis, James A. Montmarquet, Michael S. Moore, Tim Moore, Benjamin Morison, Donald R. Morrison, Stephen J. Morse, Paul K. Moser, Alexander P. D. Mourelatos, Ian Mueller, James Bernard Murphy, Mark C. Murphy, Steven Nadler, Jan Narveson, Alan Nelson, Jerome Neu, Samuel Newlands, Kai Nielsen, Ilkka Niiniluoto, Carlos G. Noreña, Calvin G. Normore, David Fate Norton, Nikolaj Nottelmann, Donald Nute, David S. Oderberg, Steve Odin, Michael O’Rourke, Willard G. Oxtoby, Heinz Paetzold, George S. Pappas, Anthony J. Parel, Lydia Patton, R. P. Peerenboom, Francis Jeffry Pelletier, Adriaan T. Peperzak, Derk Pereboom, Jaroslav Peregrin, Glen Pettigrove, Philip Pettit, Edmund L. Pincoffs, Andrew Pinsent, Robert B. Pippin, Alvin Plantinga, Louis P. Pojman, Richard H. Popkin, John F. Post, Carl J. Posy, William J. Prior, Richard Purtill, Michael Quante, Philip L. Quinn, Philip L. Quinn, Elizabeth S. Radcliffe, Diana Raffman, Gerard Raulet, Stephen L. Read, Andrews Reath, Andrew Reisner, Nicholas Rescher, Henry S. Richardson, Robert C. Richardson, Thomas Ricketts, Wayne D. Riggs, Mark Roberts, Robert C. Roberts, Luke Robinson, Alexander Rosenberg, Gary Rosenkranz, Bernice Glatzer Rosenthal, Adina L. Roskies, William L. Rowe, T. M. Rudavsky, Michael Ruse, Bruce Russell, Lilly-Marlene Russow, Dan Ryder, R. M. Sainsbury, Joseph Salerno, Nathan Salmon, Wesley C. Salmon, Constantine Sandis, David H. Sanford, Marco Santambrogio, David Sapire, Ruth A. Saunders, Geoffrey Sayre-McCord, Charles Sayward, James P. Scanlan, Richard Schacht, Tamar Schapiro, Frederick F. Schmitt, Jerome B. Schneewind, Calvin O. Schrag, Alan D. Schrift, George F. Schumm, Jean-Loup Seban, David N. Sedley, Kenneth Seeskin, Krister Segerberg, Charlene Haddock Seigfried, Dennis M. Senchuk, James F. Sennett, William Lad Sessions, Stewart Shapiro, Tommie Shelby, Donald W. Sherburne, Christopher Shields, Roger A. Shiner, Sydney Shoemaker, Robert K. Shope, Kwong-loi Shun, Wilfried Sieg, A. John Simmons, Robert L. Simon, Marcus G. Singer, Georgette Sinkler, Walter Sinnott-Armstrong, Matti T. Sintonen, Lawrence Sklar, Brian Skyrms, Robert C. Sleigh, Michael Anthony Slote, Hans Sluga, Barry Smith, Michael Smith, Robin Smith, Robert Sokolowski, Robert C. Solomon, Marta Soniewicka, Philip Soper, Ernest Sosa, Nicholas Southwood, Paul Vincent Spade, T. L. S. Sprigge, Eric O. Springsted, George J. Stack, Rebecca Stangl, Jason Stanley, Florian Steinberger, Sören Stenlund, Christopher Stephens, James P. Sterba, Josef Stern, Matthias Steup, M. A. Stewart, Leopold Stubenberg, Edith Dudley Sulla, Frederick Suppe, Jere Paul Surber, David George Sussman, Sigrún Svavarsdóttir, Zeno G. Swijtink, Richard Swinburne, Charles C. Taliaferro, Robert B. Talisse, John Tasioulas, Paul Teller, Larry S. Temkin, Mark Textor, H. S. Thayer, Peter Thielke, Alan Thomas, Amie L. Thomasson, Katherine Thomson-Jones, Joshua C. Thurow, Vzalerie Tiberius, Terrence N. Tice, Paul Tidman, Mark C. Timmons, William Tolhurst, James E. Tomberlin, Rosemarie Tong, Lawrence Torcello, Kelly Trogdon, J. D. Trout, Robert E. Tully, Raimo Tuomela, John Turri, Martin M. Tweedale, Thomas Uebel, Jennifer Uleman, James Van Cleve, Harry van der Linden, Peter van Inwagen, Bryan W. Van Norden, René van Woudenberg, Donald Phillip Verene, Samantha Vice, Thomas Vinci, Donald Wayne Viney, Barbara Von Eckardt, Peter B. M. Vranas, Steven J. Wagner, William J. Wainwright, Paul E. Walker, Robert E. Wall, Craig Walton, Douglas Walton, Eric Watkins, Richard A. Watson, Michael V. Wedin, Rudolph H. Weingartner, Paul Weirich, Paul J. Weithman, Carl Wellman, Howard Wettstein, Samuel C. Wheeler, Stephen A. White, Jennifer Whiting, Edward R. Wierenga, Michael Williams, Fred Wilson, W. Kent Wilson, Kenneth P. Winkler, John F. Wippel, Jan Woleński, Allan B. Wolter, Nicholas P. Wolterstorff, Rega Wood, W. Jay Wood, Paul Woodruff, Alison Wylie, Gideon Yaffe, Takashi Yagisawa, Yutaka Yamamoto, Keith E. Yandell, Xiaomei Yang, Dean Zimmerman, Günter Zoller, Catherine Zuckert, Michael Zuckert, Jack A. Zupko (J.A.Z.)
- Edited by Robert Audi, University of Notre Dame, Indiana
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- The Cambridge Dictionary of Philosophy
- Published online:
- 05 August 2015
- Print publication:
- 27 April 2015, pp ix-xxx
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Validation study of the European Portuguese version of the Confusion Assessment Method (CAM)
- Sónia Martins, Carla Lourenço, João Pinto-de-Sousa, Filipe Conceição, José Artur Paiva, Mário R. Simões, Lia Fernandes
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- Journal:
- International Psychogeriatrics / Volume 27 / Issue 5 / May 2015
- Published online by Cambridge University Press:
- 02 October 2014, pp. 777-784
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Background:
The Confusion Assessment Method (CAM) is the most widely used delirium screening instrument. The aim of this study was to evaluate the reliability and validity of the European Portuguese version of CAM.
Methods:The sample included elderly patients (≥65 years), admitted for at least 48 h, into two intermediate care units (ICMU) of Intensive Medicine and Surgical Services in a university hospital. Exclusion criteria were: score ≤11 on the Glasgow Coma Scale (GCS), blindness/deafness, inability to communicate and to speak Portuguese. For concurrent validity, a blinded assessment was conducted by a psychiatrist (DSM-IV-TR, as a reference standard) and by a trained researcher (CAM). This instrument was also compared with other cognitive measures to evaluate convergent validity. Inter-rater reliability was also assessed.
Results:In this sample (n = 208), 25% (n = 53) of the patients had delirium, according to DSM-IV-TR. Using this reference standard, the CAM had a moderate sensitivity of 79% and an excellent specificity of 99%. The positive predictive value was 95%, indicating a strong ability to confirm delirium with a positive test result, and the negative predictive value was lower (93%). Good convergent validity was also found, in particular with Mini-Mental State Examination (MMSE) (rs = −0.676; p ≤0.01) and Digit Span Test (DST) forward (rs = −0.605; p ≤0.01), as well as a high inter-rater reliability (diagnostic k = 1.00; single items’ k between 0.65 and 1.00).
Conclusion:Robust results on concurrent and convergent validity and good reliability were achieved. This version was shown to be a valid and reliable instrument for delirium detection in elderly patients hospitalized in intermediate care units.
Pilot study on the European Portuguese version of the Confusion Assessment Method
- Sónia Martins, Patrícia Moldes, João Pinto-de-Sousa, Filipe Conceição, José Artur Paiva, Mário R. Simões, Lia Fernandes
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- Journal:
- Acta Neuropsychiatrica / Volume 26 / Issue 5 / October 2014
- Published online by Cambridge University Press:
- 20 June 2014, pp. 321-324
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Objective
To present the pilot study on the European Portuguese validation of the Confusion Assessment Method (CAM).
MethodsThe translation process was carried out according to International Society Pharmacoeconomics and Outcomes Research guidelines with trained researchers and inter-rater reliability assessment. The study included 50 elderly patients, admitted (≥24 h) to two intermediate care units. Exclusion criteria were: Glasgow Coma Scale (total score ≤11), blindness/deafness, inability to communicate and not able to speak Portuguese. The sensitivity and specificity of CAM were assessed, with DSM-IV-TR criteria of delirium used as a reference standard.
ResultsFindings revealed excellent inter-rater reliability (k>0.81), moderate sensitivity (73%) and excellent specificity (95%).
ConclusionThese preliminary results suggested that this version emerges as a promising diagnostic instrument for delirium.
Contributors
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- By Peter J. D. Andrews, Sandeep Ankolekar, Issam A. Awad, Omar Ayoub, Philip Bath, Jürgen Bardutzky, Alexander Beck, Patrícia Canhão, J. Ricardo Carhuapoma, Winward Choy, Mahua Dey, Rajat Dhar, Michael C. Diringer, Arnd Dörfler, Joshua R. Dusick, Justin A. Dye, Corina Epple, José M. Ferro, Reiner Fietkau, Anthony Frattalone, Philippe Gailloud, Oliver Ganslandt, Anil Gholkar, Philipp Gölitz, Barbara A. Gregson, Daniel Hanley, Thomas M. Hemmen, Dan Holmes, Hagen B. Huttner, Jennifer Jaffe, Olav Jansen, Eric Jüttler, Karl L. Kiening, Martin Köhrmann, Rainer Kollmar, Kara L. Krajewski, Joji B. Kuramatsu, Perttu J. Lindsberg, Andrew Losiniecki, Patrick Lyden, Neil A. Martin, Heinrich P. Mattle, A. David Mendelow, Patrick Mitchell, Daniel T. Nagasawa, Neeraj S. Naval, Jan-Oliver Neumann, Tim Nowe, Berk Orakcioglu, Soenke Peters, Sara Pitoni, François Proust, Adnan I. Qureshi, Martin Radvany, Elise Rowan, Tiina Sairanen, Oliver W. Sakowitz, Edgar Santos, Peter D. Schellinger, Stefan Schwab, Günter Seidel, Sabine Semrau, Louise Sinclair, Dimitre Staykov, Thorsten Steiner, Jeanne Teitelbaum, Wondwossen G. Tekle, Andreas W. Unterberg, Katayoun Vahedi, H. Bart van der Worp, Paul M. Vespa, Raghu Vindlacheruvu, Jens Witsch, Isaac Yang, Wendy C. Ziai, Mario Zuccarello, Klaus Zweckberger
- Edited by Stefan Schwab, Daniel Hanley, A. David Mendelow
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- Critical Care of the Stroke Patient
- Published online:
- 05 June 2014
- Print publication:
- 05 June 2014, pp viii-xii
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Low/High Redshift Classification of Emission Line Galaxies in the HETDEX survey
- Viviana Acquaviva, Eric Gawiser, Andrew S. Leung, Mario R. Martin
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- Journal:
- Proceedings of the International Astronomical Union / Volume 10 / Issue S306 / May 2014
- Published online by Cambridge University Press:
- 01 July 2015, pp. 365-368
- Print publication:
- May 2014
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We discuss different methods to separate high- from low-redshift galaxies based on a combination of spectroscopic and photometric observations. Our baseline scenario is the Hobby-Eberly Telescope Dark Energy eXperiment (HETDEX) survey, which will observe several hundred thousand Lyman Alpha Emitting (LAE) galaxies at 1.9 < z < 3.5, and for which the main source of contamination is [OII]-emitting galaxies at z < 0.5. Additional information useful for the separation comes from empirical knowledge of LAE and [OII] luminosity functions and equivalent width distributions as a function of redshift. We consider three separation techniques: a simple cut in equivalent width, a Bayesian separation method, and machine learning algorithms, including support vector machines. These methods can be easily applied to other surveys and used on simulated data in the framework of survey planning.
Contributors
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- By Waiel Almoustadi, Brian J. Anderson, David B. Auyong, Michael Avidan, Michael J. Avram, Roland J. Bainton, Jeffrey R. Balser, Juliana Barr, W. Scott Beattie, Manfred Blobner, T. Andrew Bowdle, Walter A. Boyle, Eugene B. Campbell, Laura F. Cavallone, Mario Cibelli, C. Michael Crowder, Ola Dale, M. Frances Davies, Mark Dershwitz, George Despotis, Clifford S. Deutschman, Brian S. Donahue, Marcel E. Durieux, Thomas J. Ebert, Talmage D. Egan, Helge Eilers, E. Wesley Ely, Charles W. Emala, Alex S. Evers, Heidrun Fink, Pierre Foëx, Stuart A. Forman, Helen F. Galley, Josephine M. Garcia-Ferrer, Robert W. Gereau, Tony Gin, David Glick, B. Joseph Guglielmo, Dhanesh K. Gupta, Howard B. Gutstein, Robert G. Hahn, Greg B. Hammer, Brian P. Head, Helen Higham, Laureen Hill, Kirk Hogan, Charles W. Hogue, Christopher G. Hughes, Eric Jacobsohn, Roger A. Johns, Dean R. Jones, Max Kelz, Evan D. Kharasch, Ellen W. King, W. Andrew Kofke, Tom C. Krejcie, Richard M. Langford, H. T. Lee, Isobel Lever, Jerrold H. Levy, J. Lance Lichtor, Larry Lindenbaum, Hung Pin Liu, Geoff Lockwood, Alex Macario, Conan MacDougall, M. B. MacIver, Aman Mahajan, Nándor Marczin, J. A. Jeevendra Martyn, George A. Mashour, Mervyn Maze, Thomas McDowell, Stuart McGrane, Berend Mets, Patrick Meybohm, Charles F. Minto, Jonathan Moss, Mohamed Naguib, Istvan Nagy, Nick Oliver, Paul S. Pagel, Pratik P. Pandharipande, Piyush Patel, Andrew J. Patterson, Robert A. Pearce, Ronald G. Pearl, Misha Perouansky, Kristof Racz, Chinniampalayam Rajamohan, Nilesh Randive, Imre Redai, Stephen Robinson, Richard W. Rosenquist, Carl E. Rosow, Uwe Rudolph, Francis V. Salinas, Robert D. Sanders, Sunita Sastry, Michael Schäfer, Jens Scholz, Thomas W. Schnider, Mark A. Schumacher, John W. Sear, Frédérique S. Servin, Jeffrey H. Silverstein, Tom De Smet, Martin Smith, Joe Henry Steinbach, Markus Steinfath, David F. Stowe, Gary R. Strichartz, Michel M. R. F. Struys, Isao Tsuneyoshi, Robert A. Veselis, Arthur Wallace, Robert P. Walt, David C. Warltier, Nigel R. Webster, Jeanine Wiener-Kronish, Troy Wildes, Paul Wischmeyer, Ling-Gang Wu, Stephen Yang
- Edited by Alex S. Evers, Washington University School of Medicine, St Louis, Mervyn Maze, University of California, San Francisco, Evan D. Kharasch, Washington University School of Medicine, St Louis
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- Anesthetic Pharmacology
- Published online:
- 11 April 2011
- Print publication:
- 10 March 2011, pp viii-xiv
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Quality of life and functional evaluation after supracricoid partial laryngectomy with cricohyoidoepiglottopexy in Mexican patients
- Kuauhyama Luna-Ortiz, Ethel R. Núñez-Valencia, Mario Tamez-Velarde, Martin Granados-Garcia
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- Journal:
- The Journal of Laryngology & Otology / Volume 118 / Issue 4 / April 2004
- Published online by Cambridge University Press:
- 08 March 2006, pp. 284-288
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- April 2004
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This study assessed the functional results in patients treated primarily through supracricoid partial laryngectomy (SCPL) with cricohyoidoepiglottopexy (CHEP).
Fifteen patients with a diagnosis of epidermoid carcinoma of the glottis region admitted to the Instituto Nacional de Cancerología (México) between June 2001 and September 2002 were studied. Three patients were at stage I, five at stage II, six at stage III, and one at stage IV. Both cricoarytenoid units were preserved in 12 patients, and only one in three. Each case was assessed through the clinical grading postoperative aspiration (CGPA) scale, the performance status scale for head and neck cancer (PSS-HNC), and the Karnofsky Performance Scale (KPS). Likewise, voice quality of the patients was assessed regarding tone and intensity using the SpeechViewer version 1 (IBM) and data were obtained with the Cool Edit 2000 software.
Twelve patients received phoniatric rehabilitation and three were left without rehabilitation. The average time for decannulation was 12 days and 23 days for removal of the nasogastric catheter. The degree of aspiration was 0 in four patients and one in 11. According to PSS-HNC, the mean for normalcy in the diet was 95 and the mean for those eating in public was 91. Intelligibility reached an average of 90. Karnofsky’s assessment was related to the disease and not to the treatment, as it remained at 100 per cent in most patients and was never below 80 percent. The mean intensity of quality of voice was -18 dB below normal; however, the mean frequency was 243.7 Hz.
SCPL and CHEP allows the preservation of the basic function of the larynx; however, a clear alteration in voice occurs after the procedure, although normal frequency is kept when both arytenoids are preserved. Likewise, preservation of both arytenoids shortens the time needed for cannula and feeding catheter removal. PSS-HNC, Karnofsky, and CGPA assessments demonstrated thatpatients can reach an almost normal bio-psycho-social integration. It is recommended that all patients be subjected to phoniatric rehabilitation.