94 research outputs found
Anticonvulsant and antiarrhythmic effects of nifedipine in rats prone to audiogenic seizures
- Author
- A.J. Ferreira
- A.P. Almeida
- Almeida AP
- Ansakorpi H
- Baxter GF
- Bernauer W
- Brooks WW
- Chen HI
- Cockerell OC
- Curtis MJ
- Czuczwar SJ
- D.D. Damasceno
- De Sarro GB
- Desai CK
- Dias-Lopes C
- Garcia-Cairasco N
- Gavranovic M
- Harvey RD
- Khanna N
- Laurent D
- Lubbe WF
- M.C. Doretto
- Magalhaes LH
- Missiaen L
- Nei M
- Opherk C
- Pal S
- Reis GM
- Sahadevan P
- Thandroyen FT
- Theodore WH
- Tigaran SPC
- Publication venue
- 'FapUNIFESP (SciELO)'
- Publication date
- Field of study
Increased 30-Day Mortality in Very Old ICU Patients with COVID-19 Compared to Patients with Respiratory Failure without COVID-19
- Author
- Abosheaishaa H
- Abualqumboz E
- Ahmed A
- Ahmed H
- Aidoni Z
- Al-Sadaw M
- Aldecoa C
- Alexandru N
- Ali Y
- Andersen F
- Andersen F
- Andersen K
- Artigas A
- Assis R
- Azab M
- Azzam A
- Badawy M
- Balleby I
- Barth E
- Barth E
- Beil M
- Ben-Hamouda N
- Besch G
- Besset S
- Bjerregaard A
- Bollen Pinto B
- Boumendil A
- Brix H
- Brushoej J
- Bundgaard H
- Burtin P
- Caillard A
- Canas-Perez I
- Cecconi M
- Charron C
- Chrisanthopoulou E
- Comellini V
- Cornet A
- Cubero P
- Czuczwar M
- Dauger S
- De Lange D
- de Lange D
- Diaz-Rodriguez C
- Dieperink W
- Dindane Z
- Djibré M
- Dormans T
- Dullenkopf A
- Dumas G
- Elgazzar Y
- Eller P
- Elsaka A
- Evers M
- Faltlhauser A
- Ferreira A
- FjĂžlner J
- FjĂžlner J
- Flaatten H
- Fleury Y
- Galbois A
- Garcon P
- Garnier M
- Gawda R
- Ghannam A
- Goebel U
- GomĂ G
- Goncalves B
- Gordinho A
- Groenendijk M
- Guerot E
- Guidet B
- Gurjar M
- Haake H
- Haas L
- Habib A
- Hahn M
- Hansen M
- Hilles M
- Hussein A
- Iglesias D
- Joannidis M
- Joannidis M
- Jung C
- Jurcisin I
- Kabitz H
- Kindgen-Milles D
- Klimkiewicz J
- Kondili E
- Kuhn K
- Kunstein A
- Kurt M
- Leaver S
- Leaver S
- Lutz M
- Mahmoodpoor A
- Maizel J
- Marin N
- Marsh B
- Marsh B
- Megarbane B
- Mesotten D
- Meybohm P
- Meyer C
- Mira A
- Moreno R
- Namendys-Silva S
- Nedergaard H
- Nseir S
- Oeyen S
- Oeyen S
- Olasveengen T
- Oliveira AI
- Oziel J
- Papadogoulas A
- Perez-Torres D
- Pinto B
- Piton G
- Plantefeve G
- Poerner T
- Priego J
- Rabha A
- Randerath W
- Raphalen J
- Reper P
- Rigaud JP
- Rivera S
- Roberti A
- Romundstad L
- Rovina N
- Salah R
- Saleh M
- Sancho S
- Santos H
- Santos ML
- Schaller S
- Schaller S
- Schaller S
- Schefold J
- Schefold J
- Schuster M
- Shala G
- Sigal S
- SjĂžbĂž B
- Steiner S
- Strietzel H
- Sviri S
- Swinnen W
- Szczeklik W
- Tamayo-Lomas L
- Tharwat S
- Tomasa T
- Uhrenholt S
- Urbina T
- Vaissiere M
- Valent A
- Valette X
- Vanderlinden T
- Vernon van Heerden P
- Villamayor M
- Villefrance M
- Voigt I
- VĂĄzquez E
- Wassim K
- Welte M
- Wollborn J
- Zalba-Etayo B
- Zegers M
- Publication venue
- Springer
- Publication date
- 01/04/2022
- Field of study
Purpose: The number of patients â„ 80 years admitted into critical care is increasing. Coronavirus disease 2019 (COVID-19) added another challenge for clinical decisions for both admission and limitation of life-sustaining treatments (LLST). We aimed to compare the characteristics and mortality of very old critically ill patients with or without COVID-19 with a focus on LLST.
Methods: Patients 80 years or older with acute respiratory failure were recruited from the VIP2 and COVIP studies. Baseline patient characteristics, interventions in intensive care unit (ICU) and outcomes (30-day survival) were recorded. COVID patients were matched to non-COVID patients based on the following factors: age (± 2 years), Sequential Organ Failure Assessment (SOFA) score (± 2 points), clinical frailty scale (± 1 point), gender and region on a 1:2 ratio. Specific ICU procedures and LLST were compared between the cohorts by means of cumulative incidence curves taking into account the competing risk of discharge and death.
Results: 693 COVID patients were compared to 1393 non-COVID patients. COVID patients were younger, less frail, less severely ill with lower SOFA score, but were treated more often with invasive mechanical ventilation (MV) and had a lower 30-day survival. 404 COVID patients could be matched to 666 non-COVID patients. For COVID patients, withholding and withdrawing of LST were more frequent than for non-COVID and the 30-day survival was almost half compared to non-COVID patients.
Conclusion: Very old COVID patients have a different trajectory than non-COVID patients. Whether this finding is due to a decision policy with more active treatment limitation or to an inherent higher risk of death due to COVID-19 is unclear.info:eu-repo/semantics/publishedVersio
Cumulative Prognostic Score Predicting Mortality in Patients Older Than 80 Years Admitted to the ICU.
- Author
- Abraham P.
- Adamik B.
- Adorni A.
- Aguilar G.
- Aidoni Z.
- Aissaoui N.
- Al-Subaie N.
- Aloizos S.
- Alvarez J.
- Andersen F.
- Antoniou A.
- Artigas A.
- Babini M.
- Balasubramaniam M.
- Barattini M.
- Barbagallo M.
- Bark B.
- Barnes K.
- Barnes V.
- Barros I.
- Barros N.
- Barth E.
- Bassford C.
- Belskiy V.
- Bergstrom A.
- Berkius J.
- Bernas S.
- Berruto F.
- Bertolini G.
- Besch G.
- Biernawska J.
- Biskup E.
- Bjorsvik G.
- Bloos F.
- Bocchi A.
- Bocci M.
- Bodi M.
- Bohatyrewicz R.
- Bolger C.
- Bollen Pinto B.
- Bormans L.
- Boscolo A.
- Boskholov B.
- Bottazzi A.
- Boulanger C.
- Boumendil A.
- Bourenne J.
- Bowyer H.
- Branco M.
- Brenner T.
- Brinkman S.
- Brizio E.
- Brorsson C.
- Brresen O.
- Burns K.
- Burt K.
- Burtenshaw A.
- Calamai I.
- Calicchio G.
- Camsooksai J.
- Casalicchio T.
- Catorze N.
- Cecconi M.
- Charron C.
- Chilton P.
- Christensen S.
- Chukkambotla S.
- Clark R.
- Clark T.
- Clementi S.
- Codazzi D.
- Coetzee S.
- Constantin B.
- Cortegiani A.
- Cowton A.
- Cowton A.
- Craig J.
- Crayford A.
- Cubattoli L.
- Cuenca S.
- Cupitt J.
- Cwyl K.
- Cyrankiewicz W.
- Czuczwar M.
- De Buysscher P.
- De Geer L.
- de Lange D.
- De Neve N.
- de Smet A.
- de Waard M.
- Dempsey G.
- Dey N.
- Di Lascio G.
- Dias C.
- Dieck T.
- Dieperink W.
- Donnison P.
- Dormans T.
- Dowling S.
- Doyle N.
- Dybwik K.
- Ebelt H.
- Eller P.
- Elloway E.
- Facondini F.
- Faraldi L.
- Faulkner M.
- Fehrle L.
- Fernandes A.
- Fitzpatrick G.
- Fjolner J.
- Flaatten H.
- Forceville X.
- Franz M.
- Frey C.
- Fronczek J.
- Fuest K.
- Fumagalli P.
- Fumagalli R.
- Gajdosz R.
- Gawda R.
- Gigliuto C.
- Gimenez M.
- Goffin K.
- Gomes R.
- Goulenok C.
- Graf T.
- Graziani E.
- Grecu I.
- Grecu I.
- Grudzien P.
- Guidet B.
- Guillot M.
- Gupta M.
- Gurjar M.
- Guzman M.
- Hahn M.
- Hayes I.
- Henning J.
- Hergafi L.
- Holmstrom J.
- Honrado T.
- Hormis A.
- Humphreys S.
- Ibarz M.
- Jaimes M.
- Janosi R.
- Jansen T.
- Joannidis M.
- Jung C.
- Jung C.
- Jungner M.
- Kajtor I.
- Kam E.
- Kapoor R.
- Katsoulas T.
- Kawati R.
- Kelly Y.
- Kemmerer N.
- Kent L.
- Kent L.
- Khaliq W.
- Klepstad P.
- Kotfis K.
- Kounougeri A.
- Krawczyk P.
- Krystopchuk A.
- Kumar R.
- Kyparissi A.
- Laha S.
- Lamhaut L.
- Lampiri K.
- Lauten A.
- Lawton T.
- Lefons U.
- Legernaes T.
- Lembo R.
- Lewandowski J.
- Lupi G.
- Lyren J.
- Machala W.
- Maciejewski D.
- Maciejewski P.
- Maheshwari D.
- Maini S.
- Maji I.
- Marin N.
- Marinakis G.
- Marsh B.
- Martin D.
- Marudi A.
- Masdeu G.
- Mateu P.
- Mathew S.
- Mellea S.
- Mendoza J.
- Mentec H.
- Messika J.
- Meybohm P.
- Michel P.
- Michel P.
- Mira A.
- Morandi A.
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- Motherway C.
- Munaron S.
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- Nalapko Y.
- Nasilowski P.
- Nattino G.
- Nauska J.
- Negri G.
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- Nia A.
- Nilsson A.
- Nooteboom F.
- Nordling B.
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- Nowak I.
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- Ohman C.
- Olaussen E.
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- Pagaki E.
- Paggioro A.
- Palsson S.
- Parenmark F.
- Parrini V.
- Pastorini S.
- Pedeferri M.
- Persson S.
- Petrisor C.
- Piechota M.
- Piechota M.
- Piza P.
- Pogson D.
- Pope A.
- Popek N.
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- Prowle J.
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- Rabe C.
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- Ramnarain D.
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- Ravani I.
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- Rebollo S.
- Richardson N.
- Rico-Feijoo J.
- Ridgway S.
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- Rockstroh K.
- Rodriguez E.
- Rossi M.
- Rossi S.
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- Ryan C.
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- Sacher A.
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- Savelli F.
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- Schefold J.
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- Skold H.
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- Smole D.
- Soliman I.
- Solling C.
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- Spray D.
- Spyropoulou A.
- Stefaniak J.
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- Stoker W.
- Strietzel H.
- Strinnholm M.
- Studzinska D.
- Swinnen W.
- Szczeklik W.
- Szymkowiak M.
- Tait M.
- Taliadoros I.
- Tamm T.
- Tasioudis P.
- Templeton M.
- Thieulot-Rolin N.
- Thiringer K.
- Tsimpoukas F.
- Utzolino S.
- Valentin A.
- Vamplew L.
- van der Voort P.
- van Dijk I.
- van Lelyveld-Haas L.
- Vettoretti L.
- Vulcano G.
- Walther S.
- Watson X.
- Wawrzyniak K.
- Westbrook A.
- Wilcock D.
- Williams P.
- Wimmer F.
- Wnuk M.
- Wood J.
- Wujtewicz M.
- Zaccaria M.
- Zafeiridis T.
- Zetterquist H.
- Zhao X.
- Zietkiewicz M.
- Zisopoulou V.
- Zukowski M.
- Zygoulis P.
- Publication venue
- 'Wiley'
- Publication date
- 01/01/2019
- Field of study
OBJECTIVES: To develop a scoring system model that predicts mortality within 30âdays of admission of patients older than 80âyears admitted to intensive care units (ICUs). DESIGN: Prospective cohort study. SETTING: A total of 306 ICUs from 24 European countries. PARTICIPANTS: Older adults admitted to European ICUs (Nâ=â3730; median ageâ=â84âyears [interquartile rangeâ=â81-87 y]; 51.8% male). MEASUREMENTS: Overall, 24 variables available during ICU admission were included as potential predictive variables. Multivariable logistic regression was used to identify independent predictors of 30-day mortality. Model sensitivity, specificity, and accuracy were evaluated with receiver operating characteristic curves. RESULTS: The 30-day-mortality was 1562 (41.9%). In multivariable analysis, these variables were selected as independent predictors of mortality: age, sex, ICU admission diagnosis, Clinical Frailty Scale, Sequential Organ Failure Score, invasive mechanical ventilation, and renal replacement therapy. The discrimination, accuracy, and calibration of the model were good: the area under the curve for a score of 10 or higher was .80, and the Brier score was .18. At a cut point of 10 or higher (75% of all patients), the model predicts 30-day mortality in 91.1% of all patients who die. CONCLUSION: A predictive model of cumulative events predicts 30-day mortality in patients older than 80âyears admitted to ICUs. Future studies should include other potential predictor variables including functional status, presence of advance care plans, and assessment of each patient's decision-making capacity
Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)
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- A. -G. Wu
- A. C. Ma
- A. K. Au
- Abdel-Aziz A. K.
- Abdelfatah S.
- Abdellatif M.
- Abdoli A.
- Abel S.
- Abeliovich H.
- Abildgaard M. H.
- Abudu Y. P.
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- Adamopoulos I. E.
- Adeli K.
- Adolph T. E.
- Adornetto A.
- Aflaki E.
- Agam G.
- Agarwal A.
- Aggarwal B. B.
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- Aits S.
- Aizawa S.
- Akkoc Y.
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- Al-Abd A. M.
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- Al-Gharaibeh A.
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- Alcocer-Gomez E.
- Alessandri C.
- Ali M.
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- Publication venue
- 'Informa UK Limited'
- Publication date
- 01/01/2021
- Field of study
Relationship between the Clinical Frailty Scale and short-term mortality in patientsââ„â80Â years old acutely admitted to the ICU: a prospective cohort study.
- Author
- Abraham P.
- Adamik B.
- Adorni A.
- Aguilar G.
- Aguilar G.
- Agvald-Ăhman Christina
- Ahmed H.
- Aidoni Z.
- Aidoni Z.
- Aikaterini K.
- Aissaoui N.
- Al-Subaie N.
- AllgÀuer S.
- Aloizos S.
- Alvarez J. Trenado
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- Andersen Finn H.
- Antoniou A.
- Artigas Antonio
- Babini M.
- Baird Y.
- Balasubramaniam M.
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- Reay M.
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- Rhodes Andrew
- Rice E.
- Richardson N.
- Rico-Feijoo J.
- Ridgway S.
- Rigaud J. P.
- Rime A. K.
- Ritzema J.
- Rockstroh K.
- Rodriguez E.
- Rodriguez E.
- Rolin N.
- Romen A.
- Rose S.
- Rosman J.
- Rossi M.
- Rossi S.
- Rovina N.
- Ryan C.
- Ryan C.
- Rydén S.
- Sacher A. L.
- Saha R.
- Salaunkey K.
- Santos A. R.
- Savary G.
- Savelli F.
- Savine R.
- Schaller S. J.
- Schaller S. J.
- Schefold J. C.
- Schefold J. C.
- Schefold Joerg C.
- Schering S.
- Schiöler F.
- Schmutz R.
- Schmutz R.
- Schuster M.
- Schuster M.
- Scott C.
- Sendur P.
- Serwa M.
- Serwa M.
- Shelton J.
- Shelton S.
- Simon P.
- Sivik J.
- Sivik J.
- Sjöqvist A.
- SjĂžbĂže B.
- Sköld H.
- Slapgard A.
- Smith N.
- Smole D.
- Solek-Pastuszka J.
- Sousa C.
- Sousa C.
- Spadaro S.
- Spittle N.
- Spittle N.
- Spivey M.
- Spray D.
- Spray D.
- Spyropoulou A.
- SpÄngfors M.
- Stefaniak J.
- Stefaniak J.
- Steiner S.
- Steiner S.
- Stevenson C.
- Stoker W.
- Strand K.
- Strietzel H. F.
- Strietzel H. F.
- Strinnholm M.
- StudziĆska D.
- StudziĆska D.
- Sviri Sigal
- Swinnen W.
- Swinnen W.
- Szczeklik W.
- Szczeklik Wojciech
- Szymkowiak M.
- SĂžlling C.
- SĂžlling C.
- Tait M.
- Taliadoros I.
- Tamm T.
- Tarek A.
- Tasioudis P.
- Templeton M.
- Thevenin D.
- Thieulot-Rolin N.
- Thiringer K.
- Thiringer K. Kleiven
- Thomsen J. Edelberg
- Tiercelet K.
- Tomasa T.
- Tsimpoukas F.
- Tsimpoukas F.
- TĂžien K.
- Utzolino S.
- Vakalos A.
- Valentin Andreas
- Valette X.
- Vamplew L.
- van Boven E.
- van den Berg L.
- van der Voort P. H. J.
- van Dijk I.
- van Heerden Peter Vernon
- van Lelyveld-Haas L. E. M.
- Velasco G. Navarro
- Vettoretti L.
- Vettoretti L.
- Villamayor M. Ibarz
- Vinsonneau C.
- VIP2 study group [missing]
- Vizcaychipi M.
- Vulcano G. A.
- Wakefield P.
- Walther S.
- Walther S.
- Walther Sten
- Watson Ximena
- Wawrzyniak K.
- Welters I. D.
- Westberg H.
- Westbrook A.
- White N.
- Wilcock D.
- Williams P.
- Williams P.
- Wimmer F.
- Wnuk M.
- Wood J.
- Wujtewicz M.
- Yıldız I.
- Yovenko I.
- Zaccaria M.
- Zafeiridis Tilemachos
- Zatorski P.
- Zetterquist H.
- Zhao X.
- Zidianakis V.
- Zisopoulou V.
- ZiÄtkiewicz M.
- ZiÄtkiewicz M.
- Zorska J.
- Zukowski M.
- Zygoulis P.
- Ărsnes D.
- ƻukowski M.
- Publication venue
- 'Springer Science and Business Media LLC'
- Publication date
- 01/01/2021
- Field of study
BACKGROUND: The Clinical Frailty Scale (CFS) is frequently used to measure frailty in critically ill adults. There is wide variation in the approach to analysing the relationship between the CFS score and mortality after admission to the ICU. This study aimed to evaluate the influence of modelling approach on the association between the CFS score and short-term mortality and quantify the prognostic value of frailty in this context. METHODS: We analysed data from two multicentre prospective cohort studies which enrolled intensive care unit patientsââ„â80Â years old in 26 countries. The primary outcome was mortality within 30-days from admission to the ICU. Logistic regression models for both ICU and 30-day mortality included the CFS score as either a categorical, continuous or dichotomous variable and were adjusted for patient's age, sex, reason for admission to the ICU, and admission Sequential Organ Failure Assessment score. RESULTS: The median age in the sample of 7487 consecutive patients was 84Â years (IQR 81-87). The highest fraction of new prognostic information from frailty in the context of 30-day mortality was observed when the CFS score was treated as either a categorical variable using all original levels of frailty or a nonlinear continuous variable and was equal to 9% using these modelling approaches (pâ<â0.001). The relationship between the CFS score and mortality was nonlinear (pâ<â0.01). CONCLUSION: Knowledge about a patient's frailty status adds a substantial amount of new prognostic information at the moment of admission to the ICU. Arbitrary simplification of the CFS score into fewer groups than originally intended leads to a loss of information and should be avoided. Trial registration NCT03134807 (VIP1), NCT03370692 (VIP2)
Fluid challenges in intensive care: the FENICE study A global inception cohort study
- Author
- Abouelala A
- Acquarolo A
- Adamik B
- Adanir T
- Aguilar G
- Al-subaie N
- Alampi D
- Albanese D
- Aldecoa C
- Aldecoa C
- Aldecoa C
- Aldecoa C
- Almekhlafi G
- Alsabbah A
- Ambekar H
- Andersen Fh
- Anglada M
- Anthopoulos G
- Araujo Aguilar P
- Argaud L
- Arias Ortiz J
- Arias J
- Arribas P
- Artigas A
- Artigas A
- Artigas A
- Asfar P
- Astola I
- Baht S
- Bakker J
- Bakker J
- Balik M
- Barrera Groba C
- Basilio C
- Bauer P
- Baumann H
- Beck O
- Belluomo Ac
- Belskiy V
- Benbenishty J
- Bendjelid K
- Benes J
- Benes J
- Bengler C
- Benitez F
- Bestle M
- Biston P
- Bland M
- Bloos F
- Bottino N
- Boulain T
- Boulanger C
- Branco V
- Brazzi L
- Breen D
- Brienza N
- Bubenek-turconi Si
- Bulpa P
- Burtin P
- Buttigieg M
- Cai G
- Cannesson M
- Cardelino S
- Castiglione G
- Cavric G
- Cecconi M
- Cecconi M
- Cecconi M
- Cecconi M1
- Celaya Lopez M
- Chiche Jd
- Chruscikowski M
- Citerio G
- Conde K
- Csabi P
- Cueto G
- Czerwiec A
- Czerwinska A
- Czuczwar M
- Damas P
- Darmon M
- David A
- De Backer D
- De Backer D
- De Backer D
- De Backer D
- De Backer D
- De Backer D
- De Backer D
- De Nadal M
- Debaveye Y
- Della Rocca G
- Della Rocca G
- Della Rocca G
- Della Rocca G
- Demirkiran O
- Deschamps P
- Desebbe O
- Devriendt J
- Dhonneur G
- Dias F
- Dimoula A
- Diogo C
- Dive A
- Dixit S
- Ducrocq N
- Dugernier T
- Dujardin Mf
- Durand M
- Elahi N
- Ergin Ozcan P
- Esen F
- Espie L
- Estilita J
- Ferguson A
- Fernandez Gonzalez I
- Fernandez S
- Ferrer R
- Ferri Riera C
- Fijaikowska A
- Filipescu D
- Foti G
- Franck S
- François G
- Freita-ramos S
- Freml P
- Friis J
- Fulesdi B
- Fumeaux T
- Garcia Nogales X
- Garcia Olivares P
- Garcia-delgado H
- Gartner B
- Gasenkampf A
- Ghosh S
- Gimenez-esparzavich C
- Gkiokas G
- Glorieux D
- Goila Ak
- Goldmann A
- Gomez O
- Gonzalez Rojas M
- Goodson J
- Gornik I
- Goswami J
- Gratrix A
- Gregoire C
- Grigoryev E
- Grion C
- Guillot M
- Guitard Pg
- Guttormsen Ab
- Haentjens L
- Hamilton M
- Hamzaoui O
- Harvey D
- Hashemian M
- Hauge J
- Heenen S
- Henning J
- Herrera Para L
- Hobrok M
- Hockley S
- Hofer C
- Hofer C
- Hofer C
- Hofer C
- Hofer C
- Hormis A
- Hoste E
- Hovilehto S
- Iannuccelli F
- Jagiasi B
- Jakkinaboina S
- Jedynak M
- Jimenez Bartolome Mb
- Joannes-boyau O
- Jog S
- Jog S
- Jog S
- Jog S
- Jonas A
- Kantor S
- Kashef S
- Kashyap R
- Kasipandian V
- Kelebek Girgin N
- Kersten A
- Kesecioglu J
- King B
- Kirov M
- Kiviniemi O
- Kjelle Bj
- Knibel M
- Koch M
- Koch M
- Koelle J
- Kofinas G
- Kolpak O
- Kopitko C
- Korzybski J
- Kratochvil M
- Kuitunen A
- Kuniavsky M
- Laitio R
- Lakhal K
- Lapichino G
- Larche J
- Laterre Pf
- Leal Micharet Am
- Lefrant Jy
- Lefrant Jy
- Lefrant Jy
- Lefrant Jy
- Lefrant Jy
- Lepouse C
- Lewis K
- Lombardo A
- Londono Arcila Hf
- Lowe A
- Lukaszewska A
- Lukic E
- Maciejewski D
- Maggiorini M
- Mahmoodpoor A
- Malledant Y
- Mangani V
- Manzoni D
- Marini F
- Martin S
- Martinez Mc
- Martucci G
- Maseda E
- Mataloun S
- Mazzini P
- Mekontso Dessap A
- Meldgaard M
- Mendes C
- Menor Em
- Meybohm P
- Mijzen L
- Mikaszewska-sokolewicz M
- Mikaszewska-sokolewicz M
- Milkowska E
- Mira Jp
- Miribung M
- Misiewska-kaczur A
- Mitra D
- Molin A
- Molina F
- Molnar Z
- Molnar Z
- Molnar Z
- Molnar Z
- Monastra L
- Mongardon N
- Monge Garcia Mi
- Monti G
- Morimatsu H
- Morsch R
- Mosquera D
- Mottard N
- Munoz A
- Munster L
- Namendys-silva S. A.
- Nandakumar S
- Nayyar A
- Njimi H
- Novak I
- Numis F
- Oggioni R
- Ormskerk P
- Ortiz G
- Ospina-tascon G
- Ospina-tascĂłn G
- Palo Je
- Panarello G
- Pankotai B
- Parke R
- Parke R
- Parrini V
- Patel M
- Pereira F
- Perner A
- Petersen A
- Pettila V
- Pettila V
- Pettila V
- PettilÀ V
- Piasecka-twarog M
- Pickkers P
- Picos Sa
- Pignataro A
- Planas K
- Ploner F
- Popescu M
- Pota V
- Preau S
- Protti A
- Przemyslaw D
- Pugachev S
- Pulkkinen A
- Rai V
- Raineri Sm
- Raj A
- Ramasco F
- Ramos I
- Ramos M
- Ranganathan M
- Rasmussen Bs
- Reignier J
- Riccardi S
- Richards J
- Ripolles Melchor J
- Roasio A
- Roberts C
- Rovira A
- Ruberto F
- Rupnik E
- Saez Fernandez A
- Samavedam S
- Sanchez-galvez Hf
- Sanchez-izquierdo Ja
- Sander M
- Sander M
- Sander M
- Sarkany A
- Satinsky I
- Saveker R
- Schaffer E
- Schmauss M
- Shah B
- Shelley B
- Sherwood N
- Shimizu K
- Silva E
- Silva F
- Silversides J
- Silvestri R
- Smetkin A
- Smiechowicz K
- Sole Violan J
- Spadaro S
- Spies C
- Spies C
- Spies C
- Spivey M
- Sprung C
- Strange Dg
- Suk P
- Sulkowski W
- Szakmany T
- Szturz P
- Tallgren M
- Tamowicz B
- Tavares M
- Teboul Jl
- Teboul Jl
- Teboul Jl
- Teboul Jl
- Teboul Jl
- Teboul Jl
- Tham L
- Thomson R
- Thuerey J
- Titova J
- Tolnai P
- Toma R
- TomĂĄs Marsilla Ji
- Toome V
- Toraskar K
- Torrente S
- Torrents E
- Toth-tarsoly P
- Treskatsch S
- Van Duijn D
- Van Huelst S
- Varila S
- Vickers E
- Vizcaychipi Mp
- Volta Ca
- Wadelek J
- Walden A
- Webb S
- Weerakoon Rk
- Wernerman J
- Wernerman J
- Wieczorek A
- Wilkman E
- Wilkman E
- Wilkman E
- Wilkman E
- Williams D
- Wise M
- Xiangyu Z
- Yang C
- Yepes D
- Zacharowski K
- Zavala E
- Zhang X
- Zsolt M
- Zykova I
- Publication venue
- 'Springer Science and Business Media LLC'
- Publication date
- 01/01/2015
- Field of study
Fluid challenges (FCs) are one of the most commonly used therapies in critically ill patients and represent the cornerstone of hemodynamic management in intensive care units. There are clear benefits and harms from fluid therapy. Limited data on the indication, type, amount and rate of an FC in critically ill patients exist in the literature. The primary aim was to evaluate how physicians conduct FCs in terms of type, volume, and rate of given fluid; the secondary aim was to evaluate variables used to trigger an FC and to compare the proportion of patients receiving further fluid administration based on the response to the FC.This was an observational study conducted in ICUs around the world. Each participating unit entered a maximum of 20 patients with one FC.2213 patients were enrolled and analyzed in the study. The median [interquartile range] amount of fluid given during an FC was 500 ml (500-1000). The median time was 24 min (40-60 min), and the median rate of FC was 1000 [500-1333] ml/h. The main indication for FC was hypotension in 1211 (59 %, CI 57-61 %). In 43 % (CI 41-45 %) of the cases no hemodynamic variable was used. Static markers of preload were used in 785 of 2213 cases (36 %, CI 34-37 %). Dynamic indices of preload responsiveness were used in 483 of 2213 cases (22 %, CI 20-24 %). No safety variable for the FC was used in 72 % (CI 70-74 %) of the cases. There was no statistically significant difference in the proportion of patients who received further fluids after the FC between those with a positive, with an uncertain or with a negatively judged response.The current practice and evaluation of FC in critically ill patients are highly variable. Prediction of fluid responsiveness is not used routinely, safety limits are rarely used, and information from previous failed FCs is not always taken into account
Organic pollutants in sea-surface microlayer and aerosol in thecoastal environment of Leghornâ(Tyrrhenian Sea)
- Author
- A Contractor
- A Fisahn
- A Frandsen
- A Hadj Tahar
- A Herb
- A Kumar
- A Samii
- A Schmid
- A Takeuchi
- AD Roses
- AD Roses
- AI Faden
- AS Chappell
- AW Dunah
- B Bettler
- B Bettler
- B Sommer
- B Sommer
- B Stauch Slusher
- BT Hyman
- C Addy
- C Akazawa
- C Ferrarese
- C Hyman
- C Matute
- C Mulle
- C Sze
- CS Bjornsson
- CW Tabor
- D Aarsland
- D Dewar
- DA Hovda
- DJ Surmeier
- DM Armstrong
- DM Rock
- DR Curtis
- DR Curtis
- DW Choi
- E Aronica
- E Forsyth
- EA Kharlamov
- EL Schaeffer
- F Bibbiani
- F Blandini
- F Calon
- F Gallyas Jr
- F Jaskolski
- FJ Garcia-Ladona
- G Zundorf
- GC Castellani
- GL Collingridge
- GM Durand
- GM Shankar
- GM Shankar
- GT Swanson
- H Bernert
- H Lomeli
- H Monyer
- H Monyer
- H Sugihara
- HC Ha
- HK Lee
- HK Lee
- HK Lee
- I Ahmed
- I Shoulson
- I Smolders
- IJ Reynolds
- J Boehm
- J Boulter
- J Bruns Jr
- J Egebjerg
- J Grosskreutz
- J Lerma
- J Schumann
- J Ulas
- JA Bennett
- JA French
- JC Lauterborn
- JD Clements
- JE Huettner
- JE Nash
- JG Nutt
- JJ Chang
- JL Fisher
- JM Li
- JM Rabey
- JM Spaethling
- JT Coyle
- JT Greenamyre
- JW Olney
- K Keinanen
- K Krnjevic
- K Megyeri
- K Moriyoshi
- K Stromgaard
- K Wakabayashi
- K Williams
- KW Lange
- L Zhang
- LA Raymond
- LD Morrison
- LD Morrison
- LJ Stephen
- LK Evans
- LM Lau de
- M Arundine
- M Bobinski
- M Bouvier
- M Castagna
- M Constantine-Paton
- M Constantine-Paton
- M Darstein
- M Erecinska
- M Frigo
- M Ghasemi
- M Hollmann
- M Hollmann
- M Hollmann
- M Rigby
- M Watanabe
- M Yamazaki
- M Zimmer
- MA Paquette
- MD Ikonomovic
- MD Ikonomovic
- ME Barton
- MJ OâNeill
- MR Hynd
- MR Hynd
- MR Hynd
- MS Beattie
- MS Starr
- N Nakanishi
- NJ Sucher
- NK Woods
- P Calabresi
- P Celano
- P Luo
- P Vincent
- P Werner
- PA Loschmann
- PB Goforth
- PH Seeburg
- PH Seeburg
- R Bullock
- R Dingledine
- R Sultana
- RC Araneda
- RK Kamboj
- RL Albin
- RL Hayes
- RP Yasuda
- RS Petralia
- RS Petralia
- RS Petralia
- S Das
- S Konitsiotis
- S Lenzen
- S Ozawa
- S Sarhan
- SD Santos
- SF Traynelis
- SJ Czuczwar
- SJ Karp
- SS Panter
- SS Wu
- T Costa
- T Ishii
- TK McIntosh
- TK Murray
- TL Carter
- TM Bockers
- TN Chase
- TV Bliss
- V Gallo
- VA Derkach
- VK Moojen
- W Paschen
- WM Armstead
- WO Whetsell Jr
- World Health Organization
- Y Kanai
- Z Gu
- Z Zheng
- Publication venue
- Publication date
- 01/01/2001
- Field of study
The levels of dissolved and particle-associated n-alkanes, alkylbenzenes, phthalates, PAHs, anionic surfactants and
surfactant fluorescent organic matter ĆœSFOM. were measured in sea-surface microlayer ĆœSML. and sub-surface water ĆœSSL.
samples collected in the Leghorn marine environment in September and October 1999.
Nine stations, located in the Leghorn harbour and at increasing distances from the Port, were sampled three times on the
same day. At all the stations, SML concentrations of the selected organic compounds were significantly higher than SSL
values and the enrichment factors ĆœEFsSML concentrationrSSL concentration. were greater in the particulate phase than
in the dissolved phase.
SML concentrations varied greatly among the sampling sites, the highest levels Ćœn-alkanes 3674 mgrl, phthalates 177
mgrl, total PAHs 226 mgrl. being found in the particulate phase in the Leghorn harbour.
To improve the knowledge on pollutant exchanges between sea-surface waters and atmosphere, the validity of spray drop
adsorption model ĆœSDAM. was verified for SFOM, surface-active agents, such as phthalates, and compounds which can
interact with SFOM, such as n-alkanes and PAHs. q2001 Elsevier Science B.V. All rights reserved
Epidemiology of intra-abdominal infection and sepsis in critically ill patients: âAbSeSâ, a multinational observational cohort study and ESICM Trials Group Project
- Author
- Abdelsalam A.
- Abegao E. M.
- Aguilar G.
- Akbas T.
- Akinyi F.
- Al-Khalid M.
- Aldarsani A.
- Aldecoa C.
- Alli A.
- Almekhlafi G.
- Alsheikhly A. S.
- Alsisi A.
- Alvarez B.
- Alvarez J. T.
- Alves R.
- Anisoglou S.
- Antonelli M.
- Antypa E.
- Arias M.
- Armstrong M.
- Arroyo-Sanchez A.
- Arvaniti K.
- Aslan N. A.
- Atchade E.
- Attwood B.
- Austin P.
- Awad Y.
- Azad R.
- Bakker J.
- Bala M.
- Balasini C.
- Baranowski B.
- Barbagallo M.
- Barjon G.
- Baronia A.
- Barrachina L. G.
- Beck O.
- Belavic M.
- Belda J.
- Bellocchio A.
- Belskiy V.
- Bernedo C. G.
- Bettini L.
- Bhandary R.
- Bhowmick K.
- Bianchi L.
- Bilinska J.
- Biskup E.
- Bitzani M.
- Blahut L.
- Blot K.
- Blot S.
- Bodulica B.
- Bonetto N.
- Boraso S.
- Bormans L.
- Bosman G.
- Box R.
- Boyd C.
- Boyd O.
- Brazzi L.
- Brescia G.
- Brevard S.
- Burtin P.
- Calleja P. L. -A.
- Campbell L.
- Camsooksai J.
- Canale M.
- Candeias C.
- Capponi P.
- Cardenas Y.
- Cardenas Y.
- Cardonnet L.
- Castro G.
- Celis E.
- Cesio C.
- Chacon M. E.
- Chalkiadaki A.
- Charalambous E.
- Chasou E.
- Chavan N.
- Chediack V.
- Chinery E.
- Chinthamuneedi M.
- Chouris I.
- Christopoulos C.
- Chtsomkasem A.
- Cimic N.
- Cinnella G.
- Coggon M.
- Cole S.
- Collange O.
- Collin V.
- Colorado-Dominguez E.
- Cornet A. D.
- Corradi F.
- Correger E.
- Cortegiani A.
- Costa R. P.
- Cotoia A.
- Couce R.
- Creagh-Brown B.
- Creagh-Brown B.
- Cruz C.
- Cunto E.
- Czuczwar M.
- Dalton J.
- Dams K.
- Davis N.
- De Backer D.
- De Bels D.
- de Carvalho M. R. L. M.
- de la Torre-Prados M. -V.
- de Lange D.
- De Pascale G.
- De Schryver N.
- De Waele J.
- Debarre M.
- del Carmen Cordoba Nielfa M.
- del Rio-Carbajo L.
- Demirkiran O.
- Deschepper M.
- Descotte E. J.
- Diakaki C.
- Dickens J.
- Dietz L. S.
- Dikmen Y.
- Dimopoulos G.
- Doble P.
- Doglia J.
- Dohnal M.
- Doklestic K.
- Domingo-Marin S.
- Domingos G.
- Dominguez C.
- Dormans T.
- Dubois J.
- Duclos G.
- Dugernier T.
- Dullenkopf A.
- Dupont H.
- Dupuis C.
- Eckmann C.
- Einav S.
- Elke G.
- Elli-Nikki Flioni
- Emmerich M.
- Estevarena L. G.
- Fahmy A.
- Farazi-Chongouki C.
- Farfan A. B.
- Fernandez N.
- Fernandez R.
- Ferney B. B.
- Ferreira A.
- Ferreira A.
- Filipovic-Grcic I.
- Fjeldsoee-Nielsen H.
- Fletcher J.
- Flocco R.
- Floros J.
- Forfori F.
- Foucrier A.
- Francois G.
- Fromentin M.
- Fumale M.
- Furneval J.
- Gaigolnik D.
- Garcia J. G.
- Garcia M.
- Garcia-Alvarez R.
- Garcia-Guillen F. J.
- Georgakopoulos P.
- George M.
- Gibson B.
- Gil S. A. P.
- Girardis M.
- Gomes P.
- Gomez C. D.
- Gonzalez J. F.
- Gonzalez S.
- Gorordo L.
- Grangeat S. H.
- Grecu I.
- Grecu I.
- Grigoras I.
- Gritsan A.
- Gritsan A.
- Groba C. B.
- Groh C.
- Grubissich N.
- Gumiela N. S.
- Gumus A.
- Gunst J.
- Gurjar M.
- Haas L.
- Haentjens L.
- Hagan S.
- Hamilton M.
- Han Y.
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- Zazu A.
- Zhao X.
- Zubareva N.
- Zunic J.
- Publication venue
- 'Springer Science and Business Media LLC'
- Publication date
- 01/01/2019
- Field of study
Purpose: To describe the epidemiology of intra-abdominal infection in an international cohort of ICU patients according to a new system that classifies cases according to setting of infection acquisition (community-acquired, early onset hospital-acquired, and late-onset hospital-acquired), anatomical disruption (absent or present with localized or diffuse peritonitis), and severity of disease expression (infection, sepsis, and septic shock). Methods: We performed a multicenter (n = 309), observational, epidemiological study including adult ICU patients diagnosed with intra-abdominal infection. Risk factors for mortality were assessed by logistic regression analysis. Results: The cohort included 2621 patients. Setting of infection acquisition was community-acquired in 31.6%, early onset hospital-acquired in 25%, and late-onset hospital-acquired in 43.4% of patients. Overall prevalence of antimicrobial resistance was 26.3% and difficult-to-treat resistant Gram-negative bacteria 4.3%, with great variation according to geographic region. No difference in prevalence of antimicrobial resistance was observed according to setting of infection acquisition. Overall mortality was 29.1%. Independent risk factors for mortality included late-onset hospital-acquired infection, diffuse peritonitis, sepsis, septic shock, older age, malnutrition, liver failure, congestive heart failure, antimicrobial resistance (either methicillin-resistant Staphylococcus aureus, vancomycin-resistant enterococci, extended-spectrum beta-lactamase-producing Gram-negative bacteria, or carbapenem-resistant Gram-negative bacteria) and source control failure evidenced by either the need for surgical revision or persistent inflammation. Conclusion: This multinational, heterogeneous cohort of ICU patients with intra-abdominal infection revealed that setting of infection acquisition, anatomical disruption, and severity of disease expression are disease-specific phenotypic characteristics associated with outcome, irrespective of the type of infection. Antimicrobial resistance is equally common in community-acquired as in hospital-acquired infection
Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity
- Author
- A. Abraheem
- A. Agasou
- A. Ahmed
- A. Ali
- A. Allan
- A. Altabaibeh
- A. Alvaro
- A. Aspinwall
- A. Ayers
- A. Bamford
- A. Barron
- A. Bashyal
- A. Bellini
- A. Bociek
- A. Botello
- A. Bowes
- A. Brady
- A. Brayne
- A. Brown
- A. Brown
- A. Butler
- A. Carter
- A. Collins
- A. Cowley
- A. Cowton
- A. Cowton
- A. Cox
- A. Crew
- A. Dance
- A. Daniel
- A. Daniels
- A. Dela Rosa
- A. Drummond
- A. Durie
- A. E. Heron
- A. Easthope
- A. Easthorpe
- A. Evans.
- A. Fofano
- A. Gales
- A. Ganesan
- A. Gardner
- A. Garg
- A. Gherman
- A. Gordon
- A. Gratrix
- A. Gulati
- A. Gupta
- A. Haigh
- A. Haldeos
- A. Harrison
- A. Harvey
- A. Hayes
- A. Higham
- A. Higham
- A. Hilldrith
- A. Holden
- A. Hormis
- A. Hutcheon
- A. Javaid
- A. Joseph
- A. Kaliappan
- A. Katary
- A. Kay
- A. Kayani
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- A. Kirkby
- A. Knight
- A. Kubisz-Pudelko
- A. Kuravi
- A. Lewis
- A. Loveridge
- A. Lyle
- A. Mayer
- A. McAlpine
- A. McCarthy
- A. McGregor
- A. McGregor
- A. Meikle
- A. Mitchell
- A. Mitra
- A. Morris
- A. Morrison
- A. Naranjo
- A. Nicholson
- A. Nicholson
- A. Noakes
- A. Patel
- A. Pickard
- A. Price
- A. Puxty
- A. Quinn
- A. Quinn
- A. Raithatha
- A. Rattray
- A. Reddy
- A. Reed
- A. Reyes
- A. Rose
- A. Rose
- A. Rostron
- A. Roy
- A. Roynon-Reed
- A. S. Raj
- A. Salberg
- A. Sanderson
- A. Serrano-Ruiz
- A. Solesbury
- A. Sukha
- A. Swain
- A. Tariq
- A. Thomas
- A. Thomas
- A. Todd
- A. Tomas
- A. Tridente
- A. Tucci
- A. Turnbull
- A. Uriel
- A. Ustianowski
- A. Vochin
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- A. Waite
- A. Walden
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- A. Zaki
- Achille Iolascon
- Adam Brown
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- Agnese Verzuri
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- Arianna Gabrieli
- Arsalin Azzadin
- Asma Al Thani &
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- Audrey Coutts
- Axel Schmidt
- Axel Schmidt
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- Claudia Suardi
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- Clemens M. Wendtner
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- Eva C. Schulte
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- Wadha Al-Muftah
- WES/WGS Working Group Within the HGI
- Wiktoria Izdebska
- Wilna Oosthuyzen
- X. Qiu
- Xia Shen
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- Z. Scott
- Zhijian Yang
- Publication venue
- Publication date
- 01/01/2022
- Field of study
The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)
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- Zhuang H
- Zhuang X
- Zientara-Rytter K
- Zimmermann CM
- Ziviani E
- Zoladek T
- Zong W-X
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- Zorzano A
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- Zwerschke W
- Ălvarez ĂMC
- Ăvalos Y
- Ănal G
- ĂstĂŒn S
- ÄoliÄ M
- ÄokiÄ J
- Ćœerovnik E
- Publication venue
- 'Informa UK Limited'
- Publication date
- 01/01/2021
- Field of study
In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide 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
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