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2.
Crit Care ; 26(1): 211, 2022 07 11.
Article in English | MEDLINE | ID: covidwho-1925796

ABSTRACT

PURPOSE: In the acute respiratory distress syndrome (ARDS), decreasing Ventilation-Perfusion [Formula: see text] mismatch might enhance lung protection. We investigated the regional effects of higher Positive End Expiratory Pressure (PEEP) on [Formula: see text] mismatch and their correlation with recruitability. We aimed to verify whether PEEP improves regional [Formula: see text] mismatch, and to study the underlying mechanisms. METHODS: In fifteen patients with moderate and severe ARDS, two PEEP levels (5 and 15 cmH2O) were applied in random order. [Formula: see text] mismatch was assessed by Electrical Impedance Tomography at each PEEP. Percentage of ventilation and perfusion reaching different ranges of [Formula: see text] ratios were analyzed in 3 gravitational lung regions, leading to precise assessment of their distribution throughout different [Formula: see text] mismatch compartments. Recruitability between the two PEEP levels was measured by the recruitment-to-inflation ratio method. RESULTS: In the non-dependent region, at higher PEEP, ventilation reaching the normal [Formula: see text] compartment (p = 0.018) increased, while it decreased in the high [Formula: see text] one (p = 0.023). In the middle region, at PEEP 15 cmH2O, ventilation and perfusion to the low [Formula: see text] compartment decreased (p = 0.006 and p = 0.011) and perfusion to normal [Formula: see text] increased (p = 0.003). In the dependent lung, the percentage of blood flowing through the non-ventilated compartment decreased (p = 0.041). Regional [Formula: see text] mismatch improvement was correlated to lung recruitability and changes in regional tidal volume. CONCLUSIONS: In patients with ARDS, higher PEEP optimizes the distribution of both ventilation (in the non-dependent areas) and perfusion (in the middle and dependent lung). Bedside measure of recruitability is associated with improved [Formula: see text] mismatch.


Subject(s)
Respiratory Distress Syndrome , Humans , Lung , Perfusion , Positive-Pressure Respiration/methods , Respiratory Distress Syndrome/therapy , Respiratory Physiological Phenomena
3.
Nutrition ; : 111901, 2022.
Article in English | ScienceDirect | ID: covidwho-2095860

ABSTRACT

Aims The aim of this study was to investigate the potential benefits of using an energy-dense, high-protein (HP) formula enriched with β-hydroxy-β-methylbutyrate (HMB), fructo-oligosaccharide (FOS) and vitamin D (VitD) for enteral feeding in intensive care unit (ICU). Methods This was a nested-case control, multicenter study. Mechanically ventilated COVID-19 patients in whom enteral nutrition was not contraindicated and receiving an energy-dense, HP-HMB-FOS-VitD formula (1.5 kcal/mL;21.5% of calories from protein;N=53) were matched (1:1) by age (±1 year), gender, body mass index (±1.0 kg/m2) and SOFA score (±1 point) and compared to patients fed with a standard HP, fiber-free formula (1.25-1.3 kcal/mL;20% of calories from protein;N=53). The primary endpoint was protein intake (g/kg/day) on day 4. Protein-calorie intake on day 7, gastrointestinal intolerance and clinical outcomes were also addressed as secondary endpoints. Results The use of a HP-HMB-FOS-VitD formula resulted in higher protein intake on both day 4 and 7 (P=.006 and P=.013, respectively), with similar energy intake but higher provision of calories from enteral nutrition at both time-points (P<.001 and P=.017, respectively). Gastrointestinal tolerance was superior, with less patients fed with a HP-HMB-FOS-VitD formula reporting at least one symptom of intolerance (55% vs. 74%;OR=0.43 [0.18-0.99], P=.046) and constipation (38% vs. 66%;OR=0.27 [0.12-0.61], P=.002). A lower rate of ICU-acquired infections was also observed (42% vs. 72%;OR=0.29 [0.13-0.65], P=.003), while no difference was found in mortality, ICU stay and ventilation-free survival. Conclusions An energy-dense, HP-HMB-FOS-VitD formula enabled to provide a more satisfactory protein intake and a higher provision of calories intake from enteral nutrition than a standard HP formula in mechanically ventilated COVID-19 patients. Lower rates of gastrointestinal intolerance and ICU-acquired infections were also observed.

5.
JAMA Netw Open ; 5(10): e2238871, 2022 Oct 03.
Article in English | MEDLINE | ID: covidwho-2084948

ABSTRACT

Importance: Data on the association of COVID-19 vaccination with intensive care unit (ICU) admission and outcomes of patients with SARS-CoV-2-related pneumonia are scarce. Objective: To evaluate whether COVID-19 vaccination is associated with preventing ICU admission for COVID-19 pneumonia and to compare baseline characteristics and outcomes of vaccinated and unvaccinated patients admitted to an ICU. Design, Setting, and Participants: This retrospective cohort study on regional data sets reports: (1) daily number of administered vaccines and (2) data of all consecutive patients admitted to an ICU in Lombardy, Italy, from August 1 to December 15, 2021 (Delta variant predominant). Vaccinated patients received either mRNA vaccines (BNT162b2 or mRNA-1273) or adenoviral vector vaccines (ChAdOx1-S or Ad26.COV2). Incident rate ratios (IRRs) were computed from August 1, 2021, to January 31, 2022; ICU and baseline characteristics and outcomes of vaccinated and unvaccinated patients admitted to an ICU were analyzed from August 1 to December 15, 2021. Exposures: COVID-19 vaccination status (no vaccination, mRNA vaccine, adenoviral vector vaccine). Main Outcomes and Measures: The incidence IRR of ICU admission was evaluated, comparing vaccinated people with unvaccinated, adjusted for age and sex. The baseline characteristics at ICU admission of vaccinated and unvaccinated patients were investigated. The association between vaccination status at ICU admission and mortality at ICU and hospital discharge were also studied, adjusting for possible confounders. Results: Among the 10 107 674 inhabitants of Lombardy, Italy, at the time of this study, the median [IQR] age was 48 [28-64] years and 5 154 914 (51.0%) were female. Of the 7 863 417 individuals who were vaccinated (median [IQR] age: 53 [33-68] years; 4 010 343 [51.4%] female), 6 251 417 (79.5%) received an mRNA vaccine, 550 439 (7.0%) received an adenoviral vector vaccine, and 1 061 561 (13.5%) received a mix of vaccines and 4 497 875 (57.2%) were boosted. Compared with unvaccinated people, IRR of individuals who received an mRNA vaccine within 120 days from the last dose was 0.03 (95% CI, 0.03-0.04; P < .001), whereas IRR of individuals who received an adenoviral vector vaccine after 120 days was 0.21 (95% CI, 0.19-0.24; P < .001). There were 553 patients admitted to an ICU for COVID-19 pneumonia during the study period: 139 patients (25.1%) were vaccinated and 414 (74.9%) were unvaccinated. Compared with unvaccinated patients, vaccinated patients were older (median [IQR]: 72 [66-76] vs 60 [51-69] years; P < .001), primarily male individuals (110 patients [79.1%] vs 252 patients [60.9%]; P < .001), with more comorbidities (median [IQR]: 2 [1-3] vs 0 [0-1] comorbidities; P < .001) and had higher ratio of arterial partial pressure of oxygen (Pao2) and fraction of inspiratory oxygen (FiO2) at ICU admission (median [IQR]: 138 [100-180] vs 120 [90-158] mm Hg; P = .007). Factors associated with ICU and hospital mortality were higher age, premorbid heart disease, lower Pao2/FiO2 at ICU admission, and female sex (this factor only for ICU mortality). ICU and hospital mortality were similar between vaccinated and unvaccinated patients. Conclusions and Relevance: In this cohort study, mRNA and adenoviral vector vaccines were associated with significantly lower risk of ICU admission for COVID-19 pneumonia. ICU and hospital mortality were not associated with vaccinated status. These findings suggest a substantial reduction of the risk of developing COVID-19-related severe acute respiratory failure requiring ICU admission among vaccinated people.


Subject(s)
COVID-19 , Pneumonia , Humans , Male , Female , Middle Aged , Adult , COVID-19/epidemiology , COVID-19/prevention & control , SARS-CoV-2 , Critical Illness/therapy , COVID-19 Vaccines , Retrospective Studies , Cohort Studies , BNT162 Vaccine , Intensive Care Units , Pneumonia/epidemiology , Oxygen
6.
Int J Med Inform ; 164: 104807, 2022 08.
Article in English | MEDLINE | ID: covidwho-2076190

ABSTRACT

PURPOSE: COVID-19 disease frequently affects the lungs leading to bilateral viral pneumonia, progressing in some cases to severe respiratory failure requiring ICU admission and mechanical ventilation. Risk stratification at ICU admission is fundamental for resource allocation and decision making. We assessed performances of three machine learning approaches to predict mortality in COVID-19 patients admitted to ICU using early operative data from the Lombardy ICU Network. METHODS: This is a secondary analysis of prospectively collected data from Lombardy ICU network. A logistic regression, balanced logistic regression and random forest were built to predict survival on two datasets: dataset A included patient demographics, medications before admission and comorbidities, and dataset B included respiratory data the first day in ICU. RESULTS: Models were trained on 1484 patients on four outcomes (7/14/21/28 days) and reached the greatest predictive performance at 28 days (F1-score: 0.75 and AUC: 0.80). Age, number of comorbidities and male gender were strongly associated with mortality. On dataset B, mode of ventilatory assistance at ICU admission and fraction of inspired oxygen were associated with an increase in prediction performances. CONCLUSIONS: Machine learning techniques might be useful in emergency phases to reach good predictive performances maintaining interpretability to gain knowledge on complex situations and enhance patient management and resources.


Subject(s)
COVID-19 , COVID-19/epidemiology , Critical Illness/epidemiology , Disease Outbreaks , Humans , Intensive Care Units , Male , Retrospective Studies , SARS-CoV-2 , Supervised Machine Learning
7.
Front Med (Lausanne) ; 9: 994900, 2022.
Article in English | MEDLINE | ID: covidwho-2043491

ABSTRACT

Background: Respiratory physiotherapy is reported as safe and feasible in mechanically ventilated patients with severe Coronavirus Disease (COVID-19) admitted to Intensive Care Unit (ICU), but the short-term benefits remain unclear. Methods: We performed a retrospective observational study in four ICUs in Northern Italy. All patients with COVID-19 admitted to ICU and under invasive mechanical ventilation (MV) between March 1st and May 30th, 2020, were enrolled into the study. Overlap weighting based on the propensity score was used to adjust for confounding in the comparison of patients who had or had not been treated by physiotherapists. The primary outcome was the number of days alive and ventilator-free (VFDs). The secondary outcomes were arterial partial pressure of oxygen (PaO2)/fraction of inspired oxygen (FiO2) ratio (P/F) at ICU discharge, ICU length of stay, ICU and hospital mortality, and survival at 90 days. The trial protocol was registered on clinicaltrials.gov (NCT05067907). Results: A total of 317 patients were included in the analysis. The median VFDs was 18 days [interquartile range (IQR) 10; 24] in patients performing physiotherapy and 21 days (IQR 0; 26) in the group without physiotherapy [incidence rate ratio (IRR) 0.86, 95% confidence interval (CI): 0.78; 0.95]. The chance of 0 VFDs was lower for patients treated by physiotherapists compared to those who were not [odds ratio (OR) = 0.36, 95% CI: 0.18-0.71]. Survival at 90 days was 96.0% in the physiotherapy group and 70.6% in patients not performing physiotherapy [hazard ratio (HR) = 0.14, 95% CI: 0.03-0.71]. Number of VFDs was not associated with body mass index (BMI), sex, or P/F at ICU admission for individuals with at least 1 day off the ventilator. Conclusion: In patients with COVID-19 admitted to ICU during the first pandemic wave and treated by physiotherapists, the number of days alive and free from MV was lower compared to patients who did not perform respiratory physiotherapy. Survival at 90 days in the physiotherapy group was greater compared to no physiotherapy. These findings may be the starting point for further investigation in this setting.

8.
Baruch, Joaquin, Rojek, Amanda, Kartsonaki, Christiana, Vijayaraghavan, Bharath K. T.; Gonçalves, Bronner P.; Pritchard, Mark G.; Merson, Laura, Dunning, Jake, Hall, Matthew, Sigfrid, Louise, Citarella, Barbara W.; Murthy, Srinivas, Yeabah, Trokon O.; Olliaro, Piero, Abbas, Ali, Abdukahil, Sheryl Ann, Abdulkadir, Nurul Najmee, Abe, Ryuzo, Abel, Laurent, Absil, Lara, Acharya, Subhash, Acker, Andrew, Adam, Elisabeth, Adrião, Diana, Al Ageel, Saleh, Ahmed, Shakeel, Ainscough, Kate, Airlangga, Eka, Aisa, Tharwat, Hssain, Ali Ait, Tamlihat, Younes Ait, Akimoto, Takako, Akmal, Ernita, Al Qasim, Eman, Alalqam, Razi, Alberti, Angela, Al‐dabbous, Tala, Alegesan, Senthilkumar, Alegre, Cynthia, Alessi, Marta, Alex, Beatrice, Alexandre, Kévin, Al‐Fares, Abdulrahman, Alfoudri, Huda, Ali, Imran, Ali, Adam, Shah, Naseem Ali, Alidjnou, Kazali Enagnon, Aliudin, Jeffrey, Alkhafajee, Qabas, Allavena, Clotilde, Allou, Nathalie, Altaf, Aneela, Alves, João, Alves, Rita, Alves, João Melo, Amaral, Maria, Amira, Nur, Ampaw, Phoebe, Andini, Roberto, Andréjak, Claire, Angheben, Andrea, Angoulvant, François, Ansart, Séverine, Anthonidass, Sivanesen, Antonelli, Massimo, de Brito, Carlos Alexandre Antunes, Apriyana, Ardiyan, Arabi, Yaseen, Aragao, Irene, Araujo, Carolline, Arcadipane, Antonio, Archambault, Patrick, Arenz, Lukas, Arlet, Jean‐Benoît, Arora, Lovkesh, Arora, Rakesh, Artaud‐Macari, Elise, Aryal, Diptesh, Asensio, Angel, Ashraf, Muhammad, Asif, Namra, Asim, Mohammad, Assie, Jean Baptiste, Asyraf, Amirul, Atique, Anika, Attanyake, A. M. Udara Lakshan, Auchabie, Johann, Aumaitre, Hugues, Auvet, Adrien, Axelsen, Eyvind W.; Azemar, Laurène, Azoulay, Cecile, Bach, Benjamin, Bachelet, Delphine, Badr, Claudine, Bævre‐Jensen, Roar, Baig, Nadia, Baillie, J. Kenneth, Baird, J. Kevin, Bak, Erica, Bakakos, Agamemnon, Bakar, Nazreen Abu, Bal, Andriy, Balakrishnan, Mohanaprasanth, Balan, Valeria, Bani‐Sadr, Firouzé, Barbalho, Renata, Barbosa, Nicholas Yuri, Barclay, Wendy S.; Barnett, Saef Umar, Barnikel, Michaela, Barrasa, Helena, Barrelet, Audrey, Barrigoto, Cleide, Bartoli, Marie, Baruch, Joaquín, Bashir, Mustehan, Basmaci, Romain, Basri, Muhammad Fadhli Hassin, Battaglini, Denise, Bauer, Jules, Rincon, Diego Fernando Bautista, Dow, Denisse Bazan, Beane, Abigail, Bedossa, Alexandra, Bee, Ker Hong, Begum, Husna, Behilill, Sylvie, Beishuizen, Albertus, Beljantsev, Aleksandr, Bellemare, David, Beltrame, Anna, Beltrão, Beatriz Amorim, Beluze, Marine, Benech, Nicolas, Benjiman, Lionel Eric, Benkerrou, Dehbia, Bennett, Suzanne, Bento, Luís, Berdal, Jan‐Erik, Bergeaud, Delphine, Bergin, Hazel, Sobrino, José Luis Bernal, Bertoli, Giulia, Bertolino, Lorenzo, Bessis, Simon, Bevilcaqua, Sybille, Bezulier, Karine, Bhatt, Amar, Bhavsar, Krishna, Bianco, Claudia, Bidin, Farah Nadiah, Singh, Moirangthem Bikram, Humaid, Felwa Bin, Kamarudin, Mohd Nazlin Bin, Bissuel, François, Bitker, Laurent, Bitton, Jonathan, Blanco‐Schweizer, Pablo, Blier, Catherine, Bloos, Frank, Blot, Mathieu, Boccia, Filomena, Bodenes, Laetitia, Bogaarts, Alice, Bogaert, Debby, Boivin, Anne‐Hélène, Bolze, Pierre‐Adrien, Bompart, François, Bonfasius, Aurelius, Borges, Diogo, Borie, Raphaël, Bosse, Hans Martin, Botelho‐Nevers, Elisabeth, Bouadma, Lila, Bouchaud, Olivier, Bouchez, Sabelline, Bouhmani, Dounia, Bouhour, Damien, Bouiller, Kévin, Bouillet, Laurence, Bouisse, Camile, Boureau, Anne‐Sophie, Bourke, John, Bouscambert, Maude, Bousquet, Aurore, Bouziotis, Jason, Boxma, Bianca, Boyer‐Besseyre, Marielle, Boylan, Maria, Bozza, Fernando Augusto, Braconnier, Axelle, Braga, Cynthia, Brandenburger, Timo, Monteiro, Filipa Brás, Brazzi, Luca, Breen, Patrick, Breen, Dorothy, Breen, Patrick, Brickell, Kathy, Browne, Shaunagh, Browne, Alex, Brozzi, Nicolas, Brunvoll, Sonja Hjellegjerde, Brusse‐Keizer, Marjolein, Buchtele, Nina, Buesaquillo, Christian, Bugaeva, Polina, Buisson, Marielle, Buonsenso, Danilo, Burhan, Erlina, Burrell, Aidan, Bustos, Ingrid G.; Butnaru, Denis, Cabie, André, Cabral, Susana, Caceres, Eder, Cadoz, Cyril, Calligy, Kate, Calvache, Jose Andres, Camões, João, Campana, Valentine, Campbell, Paul, Campisi, Josie, Canepa, Cecilia, Cantero, Mireia, Caraux‐Paz, Pauline, Cárcel, Sheila, Cardellino, Chiara Simona, Cardoso, Sofia, Cardoso, Filipe, Cardoso, Filipa, Cardoso, Nelson, Carelli, Simone, Carlier, Nicolas, Carmoi, Thierry, Carney, Gayle, Carqueja, Inês, Carret, Marie‐Christine, Carrier, François Martin, Carroll, Ida, Carson, Gail, Casanova, Maire‐Laure, Cascão, Mariana, Casey, Siobhan, Casimiro, José, Cassandra, Bailey, Castañeda, Silvia, Castanheira, Nidyanara, Castor‐Alexandre, Guylaine, Castrillón, Henry, Castro, Ivo, Catarino, Ana, Catherine, François‐Xavier, Cattaneo, Paolo, Cavalin, Roberta, Cavalli, Giulio Giovanni, Cavayas, Alexandros, Ceccato, Adrian, Cervantes‐Gonzalez, Minerva, Chair, Anissa, Chakveatze, Catherine, Chan, Adrienne, Chand, Meera, Auger, Christelle Chantalat, Chapplain, Jean‐Marc, Chas, Julie, Chatterjee, Allegra, Chaudry, Mobin, Iñiguez, Jonathan Samuel Chávez, Chen, Anjellica, Chen, Yih‐Sharng, Cheng, Matthew Pellan, Cheret, Antoine, Chiarabini, Thibault, Chica, Julian, Chidambaram, Suresh Kumar, Tho, Leong Chin, Chirouze, Catherine, Chiumello, Davide, Cho, Sung‐Min, Cholley, Bernard, Chopin, Marie‐Charlotte, Chow, Ting Soo, Chow, Yock Ping, Chua, Jonathan, Chua, Hiu Jian, Cidade, Jose Pedro, Herreros, José Miguel Cisneros, Citarella, Barbara Wanjiru, Ciullo, Anna, Clarke, Jennifer, Clarke, Emma, Granado, Rolando Claure‐Del, Clohisey, Sara, Cobb, Perren J.; Codan, Cassidy, Cody, Caitriona, Coelho, Alexandra, Coles, Megan, Colin, Gwenhaël, Collins, Michael, Colombo, Sebastiano Maria, Combs, Pamela, Connor, Marie, Conrad, Anne, Contreras, Sofía, Conway, Elaine, Cooke, Graham S.; Copland, Mary, Cordel, Hugues, Corley, Amanda, Cornelis, Sabine, Cornet, Alexander Daniel, Corpuz, Arianne Joy, Cortegiani, Andrea, Corvaisier, Grégory, Costigan, Emma, Couffignal, Camille, Couffin‐Cadiergues, Sandrine, Courtois, Roxane, Cousse, Stéphanie, Cregan, Rachel, Croonen, Sabine, Crowl, Gloria, Crump, Jonathan, Cruz, Claudina, Bermúdez, Juan Luis Cruz, Rojo, Jaime Cruz, Csete, Marc, Cullen, Ailbhe, Cummings, Matthew, Curley, Gerard, Curlier, Elodie, Curran, Colleen, Custodio, Paula, da Silva Filipe, Ana, Da Silveira, Charlene, Dabaliz, Al‐Awwab, Dagens, Andrew, Dahl, John Arne, Dahly, Darren, Dalton, Heidi, Dalton, Jo, Daly, Seamus, Daneman, Nick, Daniel, Corinne, Dankwa, Emmanuelle A.; Dantas, Jorge, D'Aragon, Frédérick, de Loughry, Gillian, de Mendoza, Diego, De Montmollin, Etienne, de Oliveira França, Rafael Freitas, de Pinho Oliveira, Ana Isabel, De Rosa, Rosanna, De Rose, Cristina, de Silva, Thushan, de Vries, Peter, Deacon, Jillian, Dean, David, Debard, Alexa, Debray, Marie‐Pierre, DeCastro, Nathalie, Dechert, William, Deconninck, Lauren, Decours, Romain, Defous, Eve, Delacroix, Isabelle, Delaveuve, Eric, Delavigne, Karen, Delfos, Nathalie M.; Deligiannis, Ionna, Dell'Amore, Andrea, Delmas, Christelle, Delobel, Pierre, Delsing, Corine, Demonchy, Elisa, Denis, Emmanuelle, Deplanque, Dominique, Depuydt, Pieter, Desai, Mehul, Descamps, Diane, Desvallées, Mathilde, Dewayanti, Santi, Dhanger, Pathik, Diallo, Alpha, Diamantis, Sylvain, Dias, André, Diaz, Juan Jose, Diaz, Priscila, Diaz, Rodrigo, Didier, Kévin, Diehl, Jean‐Luc, Dieperink, Wim, Dimet, Jérôme, Dinot, Vincent, Diop, Fara, Diouf, Alphonsine, Dishon, Yael, Djossou, Félix, Docherty, Annemarie B.; Doherty, Helen, Dondorp, Arjen M.; Donnelly, Maria, Donnelly, Christl A.; Donohue, Sean, Donohue, Yoann, Donohue, Chloe, Doran, Peter, Dorival, Céline, D'Ortenzio, Eric, Douglas, James Joshua, Douma, Renee, Dournon, Nathalie, Downer, Triona, Downey, Joanne, Downing, Mark, Drake, Tom, Driscoll, Aoife, Dryden, Murray, Fonseca, Claudio Duarte, Dubee, Vincent, Dubos, François, Ducancelle, Alexandre, Duculan, Toni, Dudman, Susanne, Duggal, Abhijit, Dunand, Paul, Dunning, Jake, Duplaix, Mathilde, Durante‐Mangoni, Emanuele, Durham, Lucian, Dussol, Bertrand, Duthoit, Juliette, Duval, Xavier, Dyrhol‐Riise, Anne Margarita, Ean, Sim Choon, Echeverria‐Villalobos, Marco, Egan, Siobhan, Eggesbø, Linn Margrete, Eira, Carla, El Sanharawi, Mohammed, Elapavaluru, Subbarao, Elharrar, Brigitte, Ellerbroek, Jacobien, Ellingjord‐Dale, Merete, Eloy, Philippine, Elshazly, Tarek, Elyazar, Iqbal, Enderle, Isabelle, Endo, Tomoyuki, Eng, Chan Chee, Engelmann, Ilka, Enouf, Vincent, Epaulard, Olivier, Escher, Martina, Esperatti, Mariano, Esperou, Hélène, Esposito‐Farese, Marina, Estevão, João, Etienne, Manuel, Ettalhaoui, Nadia, Everding, Anna Greti, Evers, Mirjam, Fabre, Marc, Fabre, Isabelle, Faheem, Amna, Fahy, Arabella, Fairfield, Cameron J.; Fakar, Zul, Fareed, Komal, Faria, Pedro, Farooq, Ahmed, Fateena, Hanan, Fatoni, Arie Zainul, Faure, Karine, Favory, Raphaël, Fayed, Mohamed, Feely, Niamh, Feeney, Laura, Fernandes, Jorge, Fernandes, Marília Andreia, Fernandes, Susana, Ferrand, François‐Xavier, Devouge, Eglantine Ferrand, Ferrão, Joana, Ferraz, Mário, Ferreira, Sílvia, Ferreira, Isabel, Ferreira, Benigno, Ferrer‐Roca, Ricard, Ferriere, Nicolas, Ficko, Céline, Figueiredo‐Mello, Claudia, Finlayson, William, Fiorda, Juan, Flament, Thomas, Flateau, Clara, Fletcher, Tom, Florio, Letizia Lucia, Flynn, Deirdre, Foley, Claire, Foley, Jean, Fomin, Victor, Fonseca, Tatiana, Fontela, Patricia, Forsyth, Simon, Foster, Denise, Foti, Giuseppe, Fourn, Erwan, Fowler, Robert A.; Fraher, Marianne, Franch‐Llasat, Diego, Fraser, John F.; Fraser, Christophe, Freire, Marcela Vieira, Ribeiro, Ana Freitas, Friedrich, Caren, Fry, Stéphanie, Fuentes, Nora, Fukuda, Masahiro, Argin, G.; Gaborieau, Valérie, Gaci, Rostane, Gagliardi, Massimo, Gagnard, Jean‐Charles, Gagneux‐Brunon, Amandine, Gaião, Sérgio, Skeie, Linda Gail, Gallagher, Phil, Gamble, Carrol, Gani, Yasmin, Garan, Arthur, Garcia, Rebekha, Barrio, Noelia García, Garcia‐Diaz, Julia, Garcia‐Gallo, Esteban, Garimella, Navya, Garot, Denis, Garrait, Valérie, Gauli, Basanta, Gault, Nathalie, Gavin, Aisling, Gavrylov, Anatoliy, Gaymard, Alexandre, Gebauer, Johannes, Geraud, Eva, Morlaes, Louis Gerbaud, Germano, Nuno, Ghisulal, Praveen Kumar, Ghosn, Jade, Giani, Marco, Gibson, Jess, Gigante, Tristan, Gilg, Morgane, Gilroy, Elaine, Giordano, Guillermo, Girvan, Michelle, Gissot, Valérie, Glikman, Daniel, Glybochko, Petr, Gnall, Eric, Goco, Geraldine, Goehringer, François, Goepel, Siri, Goffard, Jean‐Christophe, Goh, Jin Yi, Golob, Jonathan, Gomez, Kyle, Gómez‐Junyent, Joan, Gominet, Marie, Gonçalves, Bronner P.; Gonzalez, Alicia, Gordon, Patricia, Gorenne, Isabelle, Goubert, Laure, Goujard, Cécile, Goulenok, Tiphaine, Grable, Margarite, Graf, Jeronimo, Grandin, Edward Wilson, Granier, Pascal, Grasselli, Giacomo, Green, Christopher A.; Greene, Courtney, Greenhalf, William, Greffe, Segolène, Grieco, Domenico Luca, Griffee, Matthew, Griffiths, Fiona, Grigoras, Ioana, Groenendijk, Albert, Lordemann, Anja Grosse, Gruner, Heidi, Gu, Yusing, Guedj, Jérémie, Guego, Martin, Guellec, Dewi, Guerguerian, Anne‐Marie, Guerreiro, Daniela, Guery, Romain, Guillaumot, Anne, Guilleminault, Laurent, Guimarães de Castro, Maisa, Guimard, Thomas, Haalboom, Marieke, Haber, Daniel, Habraken, Hannah, Hachemi, Ali, Hackmann, Amy, Hadri, Nadir, Haidri, Fakhir, Hakak, Sheeba, Hall, Adam, Hall, Matthew, Halpin, Sophie, Hameed, Jawad, Hamer, Ansley, Hamers, Raph L.; Hamidfar, Rebecca, Hammarström, Bato, Hammond, Terese, Han, Lim Yuen, Haniffa, Rashan, Hao, Kok Wei, Hardwick, Hayley, Harrison, Ewen M.; Harrison, Janet, Harrison, Samuel Bernard Ekow, Hartman, Alan, Hasan, Mohd Shahnaz, Hashmi, Junaid, Hayat, Muhammad, Hayes, Ailbhe, Hays, Leanne, Heerman, Jan, Heggelund, Lars, Hendry, Ross, Hennessy, Martina, Henriquez‐Trujillo, Aquiles, Hentzien, Maxime, Hernandez‐Montfort, Jaime, Hershey, Andrew, Hesstvedt, Liv, Hidayah, Astarini, Higgins, Eibhilin, Higgins, Dawn, Higgins, Rupert, Hinchion, Rita, Hinton, Samuel, Hiraiwa, Hiroaki, Hirkani, Haider, Hitoto, Hikombo, Ho, Yi Bin, Ho, Antonia, Hoctin, Alexandre, Hoffmann, Isabelle, Hoh, Wei Han, Hoiting, Oscar, Holt, Rebecca, Holter, Jan Cato, Horby, Peter, Horcajada, Juan Pablo, Hoshino, Koji, Houas, Ikram, Hough, Catherine L.; 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Influenza and Other Respiratory Viruses ; 2022.
Article in English | Web of Science | ID: covidwho-2019369

ABSTRACT

Introduction: Case definitions are used to guide clinical practice, surveillance and research protocols. However, how they identify COVID-19-hospitalised patients is not fully understood. We analysed the proportion of hospitalised patients with laboratory-confirmed COVID-19, in the ISARIC prospective cohort study database, meeting widely used case definitions. Methods: Patients were assessed using the Centers for Disease Control (CDC), European Centre for Disease Prevention and Control (ECDC), World Health Organization (WHO) and UK Health Security Agency (UKHSA) case definitions by age, region and time. Case fatality ratios (CFRs) and symptoms of those who did and who did not meet the case definitions were evaluated. Patients with incomplete data and non-laboratory-confirmed test result were excluded. Results: A total of 263,218 of the patients (42%) in the ISARIC database were included. Most patients (90.4%) were from Europe arid Central Asia. The proportions of patients meeting the case definitions were 56.8% (WHO), 74.4% (UKHSA), 81.6% (ECDC) and 82.3% (CDC). For each case definition, patients at the extremes of age distribution met the criteria less frequently than those aged 30 to 70 years;geographical and time variations were also observed. Estimated CFRs were similar for the patients who met the case definitions. However, when more patients did riot meet the case definition, the CFR increased. Conclusions: The performance of case definitions might be different in different regions and may change over time. Similarly concerning is the fact that older patients often did not meet case definitions, risking delayed medical care. While epidemiologists must balance their analytics with field applicability, ongoing revision of case definitions is necessary to improve patient care through early diagnosis and limit potential nosocomial spread.

9.
Am J Hematol ; 97(11): 1404-1412, 2022 Nov.
Article in English | MEDLINE | ID: covidwho-1976682

ABSTRACT

Coronavirus Disease (COVID-19) can be considered as a human pathological model of inflammation combined with hypoxia. In this setting, both erythropoiesis and iron metabolism appear to be profoundly affected by inflammatory and hypoxic stimuli, which act in the opposite direction on hepcidin regulation. The impact of low blood oxygen levels on erythropoiesis and iron metabolism in the context of human hypoxic disease (e.g., pneumonia) has not been fully elucidated. This multicentric observational study was aimed at investigating the prevalence of anemia, the alterations of iron homeostasis, and the relationship between inflammation, hypoxia, and erythropoietic parameters in a cohort of 481 COVID-19 patients admitted both to medical wards and intensive care units (ICU). Data were collected on admission and after 7 days of hospitalization. On admission, nearly half of the patients were anemic, displaying mild-to-moderate anemia. We found that hepcidin levels were increased during the whole period of observation. The patients with a higher burden of disease (i.e., those who needed intensive care treatment or had a more severe degree of hypoxia) showed lower hepcidin levels, despite having a more marked inflammatory pattern. Erythropoietin (EPO) levels were also lower in the ICU group on admission. After 7 days, EPO levels rose in the ICU group while they remained stable in the non-ICU group, reflecting that the initial hypoxic stimulus was stronger in the first group. These findings strengthen the hypothesis that, at least in the early phases, hypoxia-driven stimuli prevail over inflammation in the regulation of hepcidin and, finally, of erythropoiesis.


Subject(s)
Anemia , COVID-19 , Erythropoietin , Erythropoiesis/physiology , Hepcidins , Humans , Hypoxia , Inflammation , Iron
10.
Crit Care ; 26(1): 176, 2022 06 13.
Article in English | MEDLINE | ID: covidwho-1951306

ABSTRACT

OBJECTIVE: To assess the impact of treatment with steroids on the incidence and outcome of ventilator-associated pneumonia (VAP) in mechanically ventilated COVID-19 patients. DESIGN: Propensity-matched retrospective cohort study from February 24 to December 31, 2020, in 4 dedicated COVID-19 Intensive Care Units (ICU) in Lombardy (Italy). PATIENTS: Adult consecutive mechanically ventilated COVID-19 patients were subdivided into two groups: (1) treated with low-dose corticosteroids (dexamethasone 6 mg/day intravenous for 10 days) (DEXA+); (2) not treated with corticosteroids (DEXA-). A propensity score matching procedure (1:1 ratio) identified patients' cohorts based on: age, weight, PEEP Level, PaO2/FiO2 ratio, non-respiratory Sequential Organ Failure Assessment (SOFA) score, Charlson Comorbidity Index (CCI), C reactive protein plasma concentration at admission, sex and admission hospital (exact matching). INTERVENTION: Dexamethasone 6 mg/day intravenous for 10 days from hospital admission. MEASUREMENTS AND MAIN RESULTS: Seven hundred and thirty-nine patients were included, and the propensity-score matching identified two groups of 158 subjects each. Eighty-nine (56%) DEXA+ versus 55 (34%) DEXA- patients developed a VAP (RR 1.61 (1.26-2.098), p = 0.0001), after similar time from hospitalization, ICU admission and intubation. DEXA+ patients had higher crude VAP incidence rate (49.58 (49.26-49.91) vs. 31.65 (31.38-31.91)VAP*1000/pd), (IRR 1.57 (1.55-1.58), p < 0.0001) and risk for VAP (HR 1.81 (1.31-2.50), p = 0.0003), with longer ICU LOS and invasive mechanical ventilation but similar mortality (RR 1.17 (0.85-1.63), p = 0.3332). VAPs were similarly due to G+ bacteria (mostly Staphylococcus aureus) and G- bacteria (mostly Enterobacterales). Forty-one (28%) VAPs were due to multi-drug resistant bacteria. VAP was associated with almost doubled ICU and hospital LOS and invasive mechanical ventilation, and increased mortality (RR 1.64 [1.02-2.65], p = 0.040) with no differences among patients' groups. CONCLUSIONS: Critically ill COVID-19 patients are at high risk for VAP, frequently caused by multidrug-resistant bacteria, and the risk is increased by corticosteroid treatment. TRIAL REGISTRATION: NCT04388670, retrospectively registered May 14, 2020.


Subject(s)
COVID-19 , Pneumonia, Ventilator-Associated , Adult , COVID-19/drug therapy , COVID-19/epidemiology , Cohort Studies , Dexamethasone/therapeutic use , Humans , Incidence , Intensive Care Units , Pneumonia, Ventilator-Associated/drug therapy , Pneumonia, Ventilator-Associated/epidemiology , Pneumonia, Ventilator-Associated/etiology , Respiration, Artificial/adverse effects , Retrospective Studies
11.
Intensive Care Med ; 48(6): 690-705, 2022 Jun.
Article in English | MEDLINE | ID: covidwho-1899123

ABSTRACT

PURPOSE: To accommodate the unprecedented number of critically ill patients with pneumonia caused by coronavirus disease 2019 (COVID-19) expansion of the capacity of intensive care unit (ICU) to clinical areas not previously used for critical care was necessary. We describe the global burden of COVID-19 admissions and the clinical and organizational characteristics associated with outcomes in critically ill COVID-19 patients. METHODS: Multicenter, international, point prevalence study, including adult patients with SARS-CoV-2 infection confirmed by polymerase chain reaction (PCR) and a diagnosis of COVID-19 admitted to ICU between February 15th and May 15th, 2020. RESULTS: 4994 patients from 280 ICUs in 46 countries were included. Included ICUs increased their total capacity from 4931 to 7630 beds, deploying personnel from other areas. Overall, 1986 (39.8%) patients were admitted to surge capacity beds. Invasive ventilation at admission was present in 2325 (46.5%) patients and was required during ICU stay in 85.8% of patients. 60-day mortality was 33.9% (IQR across units: 20%-50%) and ICU mortality 32.7%. Older age, invasive mechanical ventilation, and acute kidney injury (AKI) were associated with increased mortality. These associations were also confirmed specifically in mechanically ventilated patients. Admission to surge capacity beds was not associated with mortality, even after controlling for other factors. CONCLUSIONS: ICUs responded to the increase in COVID-19 patients by increasing bed availability and staff, admitting up to 40% of patients in surge capacity beds. Although mortality in this population was high, admission to a surge capacity bed was not associated with increased mortality. Older age, invasive mechanical ventilation, and AKI were identified as the strongest predictors of mortality.


Subject(s)
Acute Kidney Injury , COVID-19 , Adult , Critical Illness , Humans , Intensive Care Units , Respiration, Artificial , SARS-CoV-2
12.
Crit Care ; 25(1): 268, 2021 07 30.
Article in English | MEDLINE | ID: covidwho-1892224

ABSTRACT

BACKGROUND: Noninvasive respiratory support (NIRS) has been diffusely employed outside the intensive care unit (ICU) to face the high request of ventilatory support due to the massive influx of patients with acute respiratory failure (ARF) caused by coronavirus-19 disease (COVID-19). We sought to summarize the evidence on clinically relevant outcomes in COVID-19 patients supported by NIV outside the ICU. METHODS: We searched PUBMED®, EMBASE®, and the Cochrane Controlled Clinical trials register, along with medRxiv and bioRxiv repositories for pre-prints, for observational studies and randomized controlled trials, from inception to the end of February 2021. Two authors independently selected the investigations according to the following criteria: (1) observational study or randomized clinical trials enrolling ≥ 50 hospitalized patients undergoing NIRS outside the ICU, (2) laboratory-confirmed COVID-19, and (3) at least the intra-hospital mortality reported. Preferred Reporting Items for Systematic reviews and Meta-analysis guidelines were followed. Data extraction was independently performed by two authors to assess: investigation features, demographics and clinical characteristics, treatments employed, NIRS regulations, and clinical outcomes. Methodological index for nonrandomized studies tool was applied to determine the quality of the enrolled studies. The primary outcome was to assess the overall intra-hospital mortality of patients under NIRS outside the ICU. The secondary outcomes included the proportions intra-hospital mortalities of patients who underwent invasive mechanical ventilation following NIRS failure and of those with 'do-not-intubate' (DNI) orders. RESULTS: Seventeen investigations (14 peer-reviewed and 3 pre-prints) were included with a low risk of bias and a high heterogeneity, for a total of 3377 patients. The overall intra-hospital mortality of patients receiving NIRS outside the ICU was 36% [30-41%]. 26% [21-30%] of the patients failed NIRS and required intubation, with an intra-hospital mortality rising to 45% [36-54%]. 23% [15-32%] of the patients received DNI orders with an intra-hospital mortality of 72% [65-78%]. Oxygenation on admission was the main source of between-study heterogeneity. CONCLUSIONS: During COVID-19 outbreak, delivering NIRS outside the ICU revealed as a feasible strategy to cope with the massive demand of ventilatory assistance. REGISTRATION: PROSPERO, https://www.crd.york.ac.uk/prospero/ , CRD42020224788, December 11, 2020.


Subject(s)
COVID-19/therapy , Noninvasive Ventilation , Respiratory Distress Syndrome/therapy , COVID-19/mortality , Continuous Positive Airway Pressure , Hospital Mortality , Humans , Intensive Care Units , Intubation/statistics & numerical data , Observational Studies as Topic , Randomized Controlled Trials as Topic , Respiration, Artificial , Respiratory Distress Syndrome/virology
13.
International journal of medical informatics ; 164:104807-104807, 2022.
Article in English | EuropePMC | ID: covidwho-1876963

ABSTRACT

Purpose COVID-19 disease frequently affects the lungs leading to bilateral viral pneumonia, progressing in some cases to severe respiratory failure requiring ICU admission and mechanical ventilation. Risk stratification at ICU admission is fundamental for resource allocation and decision making. We assessed performances of three machine learning approaches to predict mortality in COVID-19 patients admitted to ICU using early operative data from the Lombardy ICU Network. Methods This is a secondary analysis of prospectively collected data from Lombardy ICU network. A logistic regression, balanced logistic regression and random forest were built to predict survival on two datasets: dataset A included patient demographics, medications before admission and comorbidities, and dataset B included respiratory data the first day in ICU. Results Models were trained on 1484 patients on four outcomes (7/14/21/28 days) and reached the greatest predictive performance at 28 days (F1-score: 0.75 and AUC: 0.80). Age, number of comorbidities and male gender were strongly associated with mortality. On dataset B, mode of ventilatory assistance at ICU admission and fraction of inspired oxygen were associated with an increase in prediction performances. Conclusions Machine learning techniques might be useful in emergency phases to reach good predictive performances maintaining interpretability to gain knowledge on complex situations and enhance patient management and resources.

14.
Nurs Crit Care ; 2022 May 22.
Article in English | MEDLINE | ID: covidwho-1861492

ABSTRACT

BACKGROUND: During the Coronavirus disease 2019 (COVID-19) pandemic, hospital visits were suspended and video calls were offered to connect patients with their family members, especially toward the end of life (EoL). AIM: The primary aim was to describe EoL care for COVID-19 patients dying in an intensive care unit (ICU). The secondary aim was to explore whether making video calls and allowing visits was associated with lower death-related stress in family members. DESIGN: Single centre cross-sectional study. The setting was the ICU of a COVID-19 center in northern Italy, during the first year of the pandemic. Data on patients who died in the ICU were collected; death-related stress on their family members was measured using the Impact of Event Scale-Revised (IES-R). The statistical association was tested by means of logistic regression. RESULTS: The study sample included 70 patients and 56 family members. All patients died with mechanical ventilation, hydration, nutrition, analgesia and sedation ongoing. Resuscitation procedures were performed in 5/70 patients (7.1%). Only 6/56 (10.7%) of the family members interviewed had visited their loved ones in the ICU and 28/56 (50%) had made a video call. EoL video calls were judged useful by 53/56 family members (94.6%) but all (56/56, 100%) wished they could have visited the patient. High-stress levels were found in 38/56 family members (67.9%), regardless of whether they were allowed ICU access or made a video call. Compared with other degrees of kinship, patients' offspring were less likely to show a positive IES-R score (odds ratio [OR] 0.22, 95% confidence interval [CI] 0.05 to 0.89). CONCLUSIONS: During the first year of the COVID-19 pandemic, patients died without their family members at the bedside while on life-sustaining treatment. Stress levels were high in most family members, especially in patients' spouses. Video calls or ICU visits were judged favourably by family members but insufficient to alleviate death-related stress. RELEVANCE FOR CLINICAL PRACTICE: During a pandemic, ICU access by patients' family members should be considered, particularly as the time of death approaches. Although generally appreciated by family members, EoL video calls should be arranged together with other measures to alleviate death-related stress, especially for the patient's spouse.

15.
Crit Care ; 26(1): 141, 2022 05 17.
Article in English | MEDLINE | ID: covidwho-1846858

ABSTRACT

BACKGROUND: The role of neuromuscular blocking agents (NMBAs) in coronavirus disease 2019 (COVID-19) acute respiratory distress syndrome (ARDS) is not fully elucidated. Therefore, we aimed to investigate in COVID-19 patients with moderate-to-severe ARDS the impact of early use of NMBAs on 90-day mortality, through propensity score (PS) matching analysis. METHODS: We analyzed a convenience sample of patients with COVID-19 and moderate-to-severe ARDS, admitted to 244 intensive care units within the COVID-19 Critical Care Consortium, from February 1, 2020, through October 31, 2021. Patients undergoing at least 2 days and up to 3 consecutive days of NMBAs (NMBA treatment), within 48 h from commencement of IMV were compared with subjects who did not receive NMBAs or only upon commencement of IMV (control). The primary objective in the PS-matched cohort was comparison between groups in 90-day in-hospital mortality, assessed through Cox proportional hazard modeling. Secondary objectives were comparisons in the numbers of ventilator-free days (VFD) between day 1 and day 28 and between day 1 and 90 through competing risk regression. RESULTS: Data from 1953 patients were included. After propensity score matching, 210 cases from each group were well matched. In the PS-matched cohort, mean (± SD) age was 60.3 ± 13.2 years and 296 (70.5%) were male and the most common comorbidities were hypertension (56.9%), obesity (41.1%), and diabetes (30.0%). The unadjusted hazard ratio (HR) for death at 90 days in the NMBA treatment vs control group was 1.12 (95% CI 0.79, 1.59, p = 0.534). After adjustment for smoking habit and critical therapeutic covariates, the HR was 1.07 (95% CI 0.72, 1.61, p = 0.729). At 28 days, VFD were 16 (IQR 0-25) and 25 (IQR 7-26) in the NMBA treatment and control groups, respectively (sub-hazard ratio 0.82, 95% CI 0.67, 1.00, p = 0.055). At 90 days, VFD were 77 (IQR 0-87) and 87 (IQR 0-88) (sub-hazard ratio 0.86 (95% CI 0.69, 1.07; p = 0.177). CONCLUSIONS: In patients with COVID-19 and moderate-to-severe ARDS, short course of NMBA treatment, applied early, did not significantly improve 90-day mortality and VFD. In the absence of definitive data from clinical trials, NMBAs should be indicated cautiously in this setting.


Subject(s)
COVID-19 , Neuromuscular Blocking Agents , Respiratory Distress Syndrome , Aged , COVID-19/drug therapy , Female , Humans , Intensive Care Units , Male , Middle Aged , Neuromuscular Blocking Agents/therapeutic use , Propensity Score , Respiration, Artificial , Respiratory Distress Syndrome/drug therapy
16.
Front Med (Lausanne) ; 9: 850535, 2022.
Article in English | MEDLINE | ID: covidwho-1809422

ABSTRACT

Background and Aim: The novel coronavirus disease 2019 remains challenging. A large number of hospitalized patients are at a high risk of developing AKI. For this reason, we conducted a nationwide survey to assess the incidence and management of AKI in critically ill patients affected by the SARS-CoV-2 infection. Methods: This is a multicenter, observational, nationwide online survey, involving the Italian Society of Nephrology and the critical care units in Italy, developed in partnership between the scientific societies such as SIN and SIAARTI. Invitations to participate were distributed through emails and social networks. Data were collected for a period of 1 week during the COVID-19 pandemic. Results: A total of 141 responses were collected in the SIN-SIAARTI survey: 54.6% from intensivists and 44.6% from nephrologists. About 19,000 cases of COVID-19 infection have been recorded in hospitalized patients; among these cases, 7.3% had a confirmed acute kidney injury (AKI), of which 82.2% were managed in ICUs. Only 43% of clinicians routinely used the international KDIGO criteria. Renal replacement therapy (RRT) was performed in 628 patients with continuous techniques used most frequently, and oliguria was the most common indication (74.05%). Early initiation was preferred, and RRT was contraindicated in the case of therapeutic withdrawal or in the presence of severe comorbidities or hemodynamic instability. Regional anticoagulation with citrate was the most common choice. About 41.04% of the interviewed physicians never used extracorporeal blood purification therapies (EBPTs) for inflammatory cytokine or endotoxin removal. Moreover, 4.33% of interviewed clinicians used these techniques only in the presence of AKI, whereas 24.63% adopted them even in the absence of AKI. Nephrologists made more use of EBPT, especially in the presence of AKI. HVHF was never used in 58.54% of respondents, but HCO membranes and adsorbents were used in more than 50% of cases. Conclusion: This joint SIN-SIAARTI survey at the Italian Society of Nephrology and the critical care units in Italy showed that, during the COVID-19 pandemic, there was an underestimation of AKI based on the "non-use" of common diagnostic criteria, especially by intensivists. Similarly, the use of specific types of RRT and, in particular, blood purification therapies for immune modulation and organ support strongly differed between centers, suggesting the need for the development of standardized clinical guidelines.

17.
Semin Respir Crit Care Med ; 43(3): 405-416, 2022 06.
Article in English | MEDLINE | ID: covidwho-1795617

ABSTRACT

Non-invasive ventilation (NIV) or invasive mechanical ventilation (MV) is frequently needed in patients with acute hypoxemic respiratory failure due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. While NIV can be delivered in hospital wards and nonintensive care environments, intubated patients require intensive care unit (ICU) admission and support. Thus, the lack of ICU beds generated by the pandemic has often forced the use of NIV in severely hypoxemic patients treated outside the ICU. In this context, awake prone positioning has been widely adopted to ameliorate oxygenation during noninvasive respiratory support. Still, the incidence of NIV failure and the role of patient self-induced lung injury on hospital outcomes of COVID-19 subjects need to be elucidated. On the other hand, endotracheal intubation is indicated when gas exchange deterioration, muscular exhaustion, and/or neurological impairment ensue. Yet, the best timing for intubation in COVID-19 is still widely debated, as it is the safest use of neuromuscular blocking agents. Not differently from other types of acute respiratory distress syndrome, the aim of MV during COVID-19 is to provide adequate gas exchange while avoiding ventilator-induced lung injury. At the same time, the use of rescue therapies is advocated when standard care is unable to guarantee sufficient organ support. Nevertheless, the general shortage of health care resources experienced during SARS-CoV-2 pandemic might affect the utilization of high-cost, highly specialized, and long-term supports. In this article, we describe the state-of-the-art of NIV and MV setting and their usage for acute hypoxemic respiratory failure of COVID-19 patients.


Subject(s)
COVID-19 , Noninvasive Ventilation , Respiratory Insufficiency , COVID-19/therapy , Humans , Intensive Care Units , Noninvasive Ventilation/adverse effects , Respiration, Artificial/adverse effects , Respiratory Insufficiency/etiology , Respiratory Insufficiency/therapy , SARS-CoV-2
18.
Front Neurol ; 13: 774953, 2022.
Article in English | MEDLINE | ID: covidwho-1785380

ABSTRACT

The clinical outcome of the disease provoked by the SARS-CoV-2 infection, COVID-19, is largely due to the development of interstitial pneumonia accompanied by an Acute Respiratory Distress Syndrome (ARDS), often requiring ventilatory support therapy in Intensive Care Units (ICUs). Current epidemiologic evidence is demonstrating that the COVID-19 prognosis is significantly influenced by its acute complications. Among these, delirium figures as one of the most frequent and severe, especially in the emergency setting, where it shows a significantly negative prognostic impact. In this regard, the aim of our study is to identify clinical severity factors of delirium complicating COVID-19 related-ARDS. We performed a comparative and correlation analysis using demographics, comorbidities, multisystemic and delirium severity scores and anti-delirium therapy in two cohorts of ARDS patients with delirium, respectively, due to COVID-19 (n = 40) or other medical conditions (n = 39). Our results indicate that delirium in COVID-19-related ARDS is more severe since its onset despite a relatively less severe systemic condition at the point of ICU admission and required higher dosages of antipsychotic and non-benzodiazepinic sedative therapy respect to non-COVID patients. Finally, the correlation analysis showed a direct association between the male gender and maximum dosage of anti-delirium medications needed within the COVID-19 group, which was taken as a surrogate of delirium severity. Overall, our results seem to indicate that pathogenetic factors specifically associated to severe COVID-19 are responsible for the high severity of delirium, paving the way for future research focused on the mechanisms of the cognitive alterations associated with COVID-19.

19.
Crit Care ; 26(1): 34, 2022 02 05.
Article in English | MEDLINE | ID: covidwho-1706840

ABSTRACT

BACKGROUND: Extracorporeal membrane oxygenation (ECMO) has become an established rescue therapy for severe acute respiratory distress syndrome (ARDS) in several etiologies including influenza A H1N1 pneumonia. The benefit of receiving ECMO in coronavirus disease 2019 (COVID-19) is still uncertain. The aim of this analysis was to compare the outcome of patients who received veno-venous ECMO for COVID-19 and Influenza A H1N1 associated ARDS. METHODS: This was a multicenter retrospective cohort study including adults with ARDS, receiving ECMO for COVID-19 and influenza A H1N1 pneumonia between 2009 and 2021 in seven Italian ICU. The primary outcome was any-cause mortality at 60 days after ECMO initiation. We used a multivariable Cox model to estimate the difference in mortality accounting for patients' characteristics and treatment factors before ECMO was started. Secondary outcomes were mortality at 90 days, ICU and hospital length of stay and ECMO associated complications. RESULTS: Data from 308 patients with COVID-19 (N = 146) and H1N1 (N = 162) associated ARDS who had received ECMO support were included. The estimated cumulative mortality at 60 days after initiating ECMO was higher in COVID-19 (46%) than H1N1 (27%) patients (hazard ratio 1.76, 95% CI 1.17-2.46). When adjusting for confounders, specifically age and hospital length of stay before ECMO support, the hazard ratio decreased to 1.39, 95% CI 0.78-2.47. ICU and hospital length of stay, duration of ECMO and invasive mechanical ventilation and ECMO-associated hemorrhagic complications were higher in COVID-19 than H1N1 patients. CONCLUSION: In patients with ARDS who received ECMO, the observed unadjusted 60-day mortality was higher in cases of COVID-19 than H1N1 pneumonia. This difference in mortality was not significant after multivariable adjustment; older age and longer hospital length of stay before ECMO emerged as important covariates that could explain the observed difference. TRIAL REGISTRATION NUMBER: NCT05080933 , retrospectively registered.


Subject(s)
COVID-19 , Extracorporeal Membrane Oxygenation , Influenza A Virus, H1N1 Subtype , Influenza, Human , Respiratory Distress Syndrome , Adult , Aged , Humans , Influenza, Human/complications , Influenza, Human/therapy , Respiratory Distress Syndrome/therapy , Retrospective Studies , SARS-CoV-2
20.
Cochrane Database Syst Rev ; 1: CD015308, 2022 01 26.
Article in English | MEDLINE | ID: covidwho-1653145

ABSTRACT

BACKGROUND: Interleukin-1 (IL-1) blocking agents have been used for treating severe coronavirus disease 2019 (COVID-19), on the premise that their immunomodulatory effect might be beneficial in people with COVID-19. OBJECTIVES: To assess the effects of IL-1 blocking agents compared with standard care alone or with placebo on effectiveness and safety outcomes in people with COVID-19. We will update this assessment regularly. SEARCH METHODS: We searched the Cochrane COVID-19 Study Register and the COVID-19 L-OVE Platform (search date 5 November 2021). These sources are maintained through regular searches of MEDLINE, Embase, CENTRAL, trial registers and other sources. We also checked the World Health Organization International Clinical Trials Registry Platform, regulatory agency websites, Retraction Watch (search date 3 November 2021). SELECTION CRITERIA: We included randomised controlled trials (RCTs) evaluating IL-1 blocking agents compared with standard care alone or with placebo for people with COVID-19, regardless of disease severity. DATA COLLECTION AND ANALYSIS: We followed Cochrane methodology. The protocol was amended to reduce the number of outcomes considered. Two researchers independently screened and extracted data and assessed the risk of bias with the Cochrane Risk of Bias 2 tool. We rated the certainty of evidence using the GRADE approach for the critical outcomes of clinical improvement (Day 28; ≥ D60); WHO Clinical Progression Score of level 7 or above (i.e. the proportion of participants with mechanical ventilation +/- additional organ support OR death) (D28; ≥ D60); all-cause mortality (D28; ≥ D60); incidence of any adverse events; and incidence of serious adverse events. MAIN RESULTS: We identified four RCTs of anakinra (three published in peer-reviewed journals, one reported as a preprint) and two RCTs of canakinumab (published in peer-reviewed journals). All trials were multicentre (2 to 133 centres). Two trials stopped early (one due to futility and one as the trigger for inferiority was met). The median/mean age range varied from 58 to 68 years; the proportion of men varied from 58% to 77%. All participants were hospitalised; 67% to 100% were on oxygen at baseline but not intubated; between 0% and 33% were intubated at baseline. We identified a further 16 registered trials with no results available, of which 15 assessed anakinra (four completed, four terminated, five ongoing, three not recruiting) and one (completed) trial assessed canakinumab. Effectiveness of anakinra for people with COVID-19 Anakinra probably results in little or no increase in clinical improvement at D28 (risk ratio (RR) 1.08, 95% confidence interval (CI) 0.97 to 1.20; 3 RCTs, 837 participants; absolute effect: 59 more per 1000 (from 22 fewer to 147 more); moderate-certainty evidence. The evidence is uncertain about an effect of anakinra on 1) the proportion of participants with a WHO Clinical Progression Score of level 7 or above at D28 (RR 0.67, 95% CI 0.36 to 1.22; 2 RCTs, 722 participants; absolute effect: 55 fewer per 1000 (from 107 fewer to 37 more); low-certainty evidence) and ≥ D60 (RR 0.54, 95% CI 0.30 to 0.96; 1 RCT, 606 participants; absolute effect: 47 fewer per 1000 (from 72 fewer to 4 fewer) low-certainty evidence); and 2) all-cause mortality at D28 (RR 0.69, 95% CI 0.34 to 1.39; 2 RCTs, 722 participants; absolute effect: 32 fewer per 1000 (from 68 fewer to 40 more); low-certainty evidence).  The evidence is very uncertain about an effect of anakinra on 1) the proportion of participants with clinical improvement at ≥ D60 (RR 0.93, 95% CI 0.78 to 1.12; 1 RCT, 115 participants; absolute effect: 59 fewer per 1000 (from 186 fewer to 102 more); very low-certainty evidence); and 2) all-cause mortality at ≥ D60 (RR 1.03, 95% CI 0.68 to 1.56; 4 RCTs, 1633 participants; absolute effect: 8 more per 1000 (from 84 fewer to 147 more); very low-certainty evidence). Safety of anakinra for people with COVID-19 Anakinra probably results in little or no increase in adverse events (RR 1.02, 95% CI 0.94 to 1.11; 2 RCTs, 722 participants; absolute effect: 14 more per 1000 (from 43 fewer to 78 more); moderate-certainty evidence).  The evidence is uncertain regarding an effect of anakinra on serious adverse events (RR 0.95, 95% CI 0.58 to 1.56; 2 RCTs, 722 participants; absolute effect: 12 fewer per 1000 (from 104 fewer to 138 more); low-certainty evidence). Effectiveness of canakinumab for people with COVID-19 Canakinumab probably results in little or no increase in clinical improvement at D28 (RR 1.05, 95% CI 0.96 to 1.14; 2 RCTs, 499 participants; absolute effect: 42 more per 1000 (from 33 fewer to 116 more); moderate-certainty evidence).  The evidence of an effect of canakinumab is uncertain on 1) the proportion of participants with a WHO Clinical Progression Score of level 7 or above at D28 (RR 0.72, 95% CI 0.44 to 1.20; 2 RCTs, 499 participants; absolute effect: 35 fewer per 1000 (from 69 fewer to 25 more); low-certainty evidence); and 2) all-cause mortality at D28 (RR:0.75; 95% CI 0.39 to 1.42); 2 RCTs, 499 participants; absolute effect: 20 fewer per 1000 (from 48 fewer to 33 more); low-certainty evidence).  The evidence is very uncertain about an effect of canakinumab on all-cause mortality at ≥ D60 (RR 0.55, 95% CI 0.16 to 1.91; 1 RCT, 45 participants; absolute effect: 112 fewer per 1000 (from 210 fewer to 227 more); very low-certainty evidence). Safety of canakinumab for people with COVID-19 Canakinumab probably results in little or no increase in adverse events (RR 1.02; 95% CI 0.86 to 1.21; 1 RCT, 454 participants; absolute effect: 11 more per 1000 (from 74 fewer to 111 more); moderate-certainty evidence). The evidence of an effect of canakinumab on serious adverse events is uncertain (RR 0.80, 95% CI 0.57 to 1.13; 2 RCTs, 499 participants; absolute effect: 44 fewer per 1000 (from 94 fewer to 28 more); low-certainty evidence). AUTHORS' CONCLUSIONS: Overall, we did not find evidence for an important beneficial effect of IL-1 blocking agents. The evidence is uncertain or very uncertain for several outcomes. Sixteen trials of anakinra and canakinumab with no results are currently registered, of which four are completed, and four terminated. The findings of this review are updated on the COVID-NMA platform (covid-nma.com).


Subject(s)
COVID-19 , Interleukin-1/antagonists & inhibitors , Aged , COVID-19/drug therapy , Female , Humans , Male , Middle Aged , Randomized Controlled Trials as Topic , Respiration, Artificial
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