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Ling RR, Ponnapa Reddy M, Subramaniam A, Moran B, Ramanathan K, Ramanan M, Burrell A, Pilcher D, Shekar K. Epidemiology of acute hypoxaemic respiratory failure in Australian and New Zealand intensive care units during 2005-2022. A binational, registry-based study. Intensive Care Med 2024:10.1007/s00134-024-07609-y. [PMID: 39222135 DOI: 10.1007/s00134-024-07609-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Accepted: 08/10/2024] [Indexed: 09/04/2024]
Abstract
PURPOSE Acute hypoxaemic respiratory failure (AHRF) is a common reason for intensive care unit (ICU) admission. However, patient characteristics, outcomes, and trends over time are unclear. We describe the epidemiology and outcomes of patients with AHRF over time. METHODS In this binational, registry-based study from 2005 to 2022, we included all adults admitted to an Australian or New Zealand ICU with an arterial blood gas within the first 24 h of ICU stay. AHRF was defined as a partial pressure of oxygen/inspired oxygen ratio (PaO2/FiO2) ≤ 300. The primary outcome was adjusted in-hospital mortality, categorised based on PaO2/FiO2 (mild: 200-300, moderate: 100-200, and severe < 100, and non-linearly). We investigated how adjusted mortality evolved based on temporal trends (by year of admission), sex, age, admission diagnosis and the receipt of mechanical ventilation. RESULTS Of 1,560,221 patients, 826,106 (52.9%) were admitted with or developed AHRF within the first 24 h of ICU stay. Of these 826,106 patients, 51.4% had mild, 39.3% had moderate, and 9.3% had severe AHRF. Compared to patients without AHRF (5.3%), patients with mild (8%), moderate (14.2%) and severe (29.9%) AHRF had higher in-hospital mortality rates. As PaO2/FiO2 ratio decreased, adjusted in-hospital mortality progressively increased, particularly below an inflection point at a PaO2/FiO2 ratio of 200. The adjusted in-hospital mortality for all patients decreased over time (13.3% in 2005 to 8.2% in 2022), and this trend was similar in patients with and without AHRF. CONCLUSION The healthcare burden due to AHRF may be larger than expected, and mortality rates remain high in severe AHRF. Although mortality has decreased over time, this may reflect improvements in ICU care in general, rather than specifically in AHRF. More research is required to earlier identify AHRF and stratify these patients at risk of deterioration early, and to validate our findings.
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Affiliation(s)
- Ryan Ruiyang Ling
- Yong Loo Lin School of Medicine, National University of Singapore, National University Health System, Singapore, Singapore.
- Australian and New Zealand Intensive Care Research Centre, Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
- Department of Anaesthesia, National University Hospital, National University Health System, Singapore, Singapore.
| | - Mallikarjuna Ponnapa Reddy
- Department of Anaesthesia and Pain Medicine, Nepean Hospital, Sydney, Australia
- Department of Intensive Care Medicine, North Canberra Hospital, Canberra, ACT, Australia
- Department of Intensive Care Medicine, Peninsula Health, Frankston, VIC, Australia
| | - Ashwin Subramaniam
- Australian and New Zealand Intensive Care Research Centre, Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia
- Department of Intensive Care Medicine, Peninsula Health, Frankston, VIC, Australia
- Department of Intensive Care Medicine, Dandenong Hospital, Monash Health, Dandenong, VIC, Australia
- Peninsula Clinical School, Monash University, Frankston, VIC, Australia
| | - Benjamin Moran
- Department of Intensive Care Medicine, Gosford Hospital, Gosford, NSW, Australia
- Department of Anaesthesia and Pain Medicine, Gosford Hospital, Gosford, NSW, Australia
- University of Newcastle, Callaghan, NSW, Australia
| | - Kollengode Ramanathan
- Yong Loo Lin School of Medicine, National University of Singapore, National University Health System, Singapore, Singapore
- Cardiothoracic Intensive Care Unit, National University Heart Centre, National University Hospital, Singapore, Singapore
| | - Mahesh Ramanan
- Intensive Care Unit, Caboolture Hospital, Brisbane, QLD, Australia
- School of Medicine, Mayne Academy of Critical Care, The University of Queensland, St Lucia, QLD, Australia
- Adult Intensive Care Services, The Prince Charles Hospital, Brisbane, QLD, Australia
- Critical Care Division, The George Institute for Global Health, University of New South Wales, Sydney, NSW, Australia
| | - Aidan Burrell
- Australian and New Zealand Intensive Care Research Centre, Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia
- Department of Intensive Care, Alfred Hospital, Melbourne, VIC, Australia
| | - David Pilcher
- Australian and New Zealand Intensive Care Research Centre, Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia
- Department of Intensive Care, Alfred Hospital, Melbourne, VIC, Australia
- Centre for Outcome and Resource Evaluation, Australian and New Zealand Intensive Care Society, Melbourne, VIC, Australia
| | - Kiran Shekar
- Adult Intensive Care Services, The Prince Charles Hospital, Brisbane, QLD, Australia
- Bond University, Gold Coast, QLD, Australia
- Faculty of Health, Queensland University of Technology, Brisbane, Australia
- University of Queensland, Brisbane, QLD, Australia
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Yarnell CJ, Angriman F, Ferreyro BL, Liu K, De Grooth HJ, Burry L, Munshi L, Mehta S, Celi L, Elbers P, Thoral P, Brochard L, Wunsch H, Fowler RA, Sung L, Tomlinson G. Oxygenation thresholds for invasive ventilation in hypoxemic respiratory failure: a target trial emulation in two cohorts. Crit Care 2023; 27:67. [PMID: 36814287 PMCID: PMC9944781 DOI: 10.1186/s13054-023-04307-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 01/06/2023] [Indexed: 02/24/2023] Open
Abstract
BACKGROUND The optimal thresholds for the initiation of invasive ventilation in patients with hypoxemic respiratory failure are unknown. Using the saturation-to-inspired oxygen ratio (SF), we compared lower versus higher hypoxemia severity thresholds for initiating invasive ventilation. METHODS This target trial emulation included patients from the Medical Information Mart for Intensive Care (MIMIC-IV, 2008-2019) and the Amsterdam University Medical Centers (AmsterdamUMCdb, 2003-2016) databases admitted to intensive care and receiving inspired oxygen fraction ≥ 0.4 via non-rebreather mask, noninvasive ventilation, or high-flow nasal cannula. We compared the effect of using invasive ventilation initiation thresholds of SF < 110, < 98, and < 88 on 28-day mortality. MIMIC-IV was used for the primary analysis and AmsterdamUMCdb for the secondary analysis. We obtained posterior means and 95% credible intervals (CrI) with nonparametric Bayesian G-computation. RESULTS We studied 3,357 patients in the primary analysis. For invasive ventilation initiation thresholds SF < 110, SF < 98, and SF < 88, the predicted 28-day probabilities of invasive ventilation were 72%, 47%, and 19%. Predicted 28-day mortality was lowest with threshold SF < 110 (22.2%, CrI 19.2 to 25.0), compared to SF < 98 (absolute risk increase 1.6%, CrI 0.6 to 2.6) or SF < 88 (absolute risk increase 3.5%, CrI 1.4 to 5.4). In the secondary analysis (1,279 patients), the predicted 28-day probability of invasive ventilation was 50% for initiation threshold SF < 110, 28% for SF < 98, and 19% for SF < 88. In contrast with the primary analysis, predicted mortality was highest with threshold SF < 110 (14.6%, CrI 7.7 to 22.3), compared to SF < 98 (absolute risk decrease 0.5%, CrI 0.0 to 0.9) or SF < 88 (absolute risk decrease 1.9%, CrI 0.9 to 2.8). CONCLUSION Initiating invasive ventilation at lower hypoxemia severity will increase the rate of invasive ventilation, but this can either increase or decrease the expected mortality, with the direction of effect likely depending on baseline mortality risk and clinical context.
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Affiliation(s)
- Christopher J. Yarnell
- grid.17063.330000 0001 2157 2938Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Canada ,grid.231844.80000 0004 0474 0428Department of Medicine, Division of Respirology, University Health Network and Sinai Health System, Toronto, Canada ,grid.17063.330000 0001 2157 2938Institute of Health Policy, Management and Evaluation, University of Toronto, Medical-Surgical ICU, 10th floor, 585 University Avenue, Toronto, ON M5G 1X5 Canada
| | - Federico Angriman
- grid.17063.330000 0001 2157 2938Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Canada ,grid.17063.330000 0001 2157 2938Institute of Health Policy, Management and Evaluation, University of Toronto, Medical-Surgical ICU, 10th floor, 585 University Avenue, Toronto, ON M5G 1X5 Canada ,grid.413104.30000 0000 9743 1587Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Bruno L. Ferreyro
- grid.17063.330000 0001 2157 2938Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Canada ,grid.231844.80000 0004 0474 0428Department of Medicine, Division of Respirology, University Health Network and Sinai Health System, Toronto, Canada ,grid.17063.330000 0001 2157 2938Institute of Health Policy, Management and Evaluation, University of Toronto, Medical-Surgical ICU, 10th floor, 585 University Avenue, Toronto, ON M5G 1X5 Canada
| | - Kuan Liu
- grid.17063.330000 0001 2157 2938Institute of Health Policy, Management and Evaluation, University of Toronto, Medical-Surgical ICU, 10th floor, 585 University Avenue, Toronto, ON M5G 1X5 Canada
| | - Harm Jan De Grooth
- grid.12380.380000 0004 1754 9227Department of Intensive Care Medicine, Laboratory for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | - Lisa Burry
- grid.17063.330000 0001 2157 2938Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Canada ,grid.492573.e0000 0004 6477 6457Department of Pharmacy and Medicine, Sinai Health System, Toronto, Canada ,grid.17063.330000 0001 2157 2938Leslie Dan Faculty of Pharmacy and Interdepartmental Division of Critical Care, University of Toronto, Toronto, ON Canada
| | - Laveena Munshi
- grid.17063.330000 0001 2157 2938Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Canada ,grid.231844.80000 0004 0474 0428Department of Medicine, Division of Respirology, University Health Network and Sinai Health System, Toronto, Canada
| | - Sangeeta Mehta
- grid.17063.330000 0001 2157 2938Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Canada ,grid.231844.80000 0004 0474 0428Department of Medicine, Division of Respirology, University Health Network and Sinai Health System, Toronto, Canada
| | - Leo Celi
- grid.116068.80000 0001 2341 2786Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02142 USA ,grid.239395.70000 0000 9011 8547Division of Pulmonary, Critical Care and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, MA 02215 USA ,grid.38142.3c000000041936754XDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115 USA
| | - Paul Elbers
- grid.12380.380000 0004 1754 9227Department of Intensive Care Medicine, Laboratory for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | - Patrick Thoral
- grid.12380.380000 0004 1754 9227Department of Intensive Care Medicine, Laboratory for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | - Laurent Brochard
- grid.415502.7Keenan Research Centre for Biomedical Research, Li Ka Shing Knowledge Institute, St Michael’s Hospital, Unity Health Toronto, Toronto, Canada ,grid.17063.330000 0001 2157 2938Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Canada
| | - Hannah Wunsch
- grid.418647.80000 0000 8849 1617Institute for Clinical Evaluative Sciences, Toronto, Canada ,grid.17063.330000 0001 2157 2938Institute of Health Policy, Management and Evaluation, University of Toronto, Medical-Surgical ICU, 10th floor, 585 University Avenue, Toronto, ON M5G 1X5 Canada ,grid.413104.30000 0000 9743 1587Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Robert A. Fowler
- grid.17063.330000 0001 2157 2938Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Canada ,grid.17063.330000 0001 2157 2938Department of Medicine, University of Toronto, Toronto, Canada ,grid.418647.80000 0000 8849 1617Institute for Clinical Evaluative Sciences, Toronto, Canada ,grid.17063.330000 0001 2157 2938Institute of Health Policy, Management and Evaluation, University of Toronto, Medical-Surgical ICU, 10th floor, 585 University Avenue, Toronto, ON M5G 1X5 Canada ,grid.413104.30000 0000 9743 1587Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Lillian Sung
- grid.17063.330000 0001 2157 2938Institute of Health Policy, Management and Evaluation, University of Toronto, Medical-Surgical ICU, 10th floor, 585 University Avenue, Toronto, ON M5G 1X5 Canada ,grid.42327.300000 0004 0473 9646Division of Haematology/Oncology, The Hospital for Sick Children, Toronto, Canada
| | - George Tomlinson
- grid.231844.80000 0004 0474 0428Department of Medicine, University Health Network and Sinai Health System, Toronto, Canada ,grid.17063.330000 0001 2157 2938Institute of Health Policy, Management and Evaluation, University of Toronto, Medical-Surgical ICU, 10th floor, 585 University Avenue, Toronto, ON M5G 1X5 Canada
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Factors influencing cancer survivors' experiences with follow-up cancer care: results from the pan-Canadian Experiences of Cancer Patients in Transition Study survey. Support Care Cancer 2022; 30:9559-9575. [PMID: 36123549 DOI: 10.1007/s00520-022-07357-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Accepted: 09/06/2022] [Indexed: 10/14/2022]
Abstract
PURPOSE The purpose of this study was to examine the influence of individual and structural factors on cancer survivors' experiences with follow-up cancer care. METHODS In 2016, the Canadian Partnership Against Cancer collected survey responses from cancer survivors about their experiences with follow-up cancer care. We included respondents from this survey if they were diagnosed with non-metastatic breast, hematologic, colon, melanoma, and prostate cancer. Our primary outcome was cancer survivors' self-reported overall experience with follow-up cancer care. We used multivariable logistic regression to examine the influence of individual and structural factors on cancer survivors' experiences with follow-up cancer care. RESULTS Of the 8402 cancer survivors included in our study, 81.8% (n = 6,875) reported a positive experience with their follow-up cancer care. The individual factors associated with positive overall experiences were more commonly those associated with self-perceptions of respondents' personal health and well-being rather than baseline sociodemographic factors, such as sex, income, or education. For example, respondents were more likely to report a positive experience if they perceived their quality of life as good (OR 1.9, 95% CI 1.0-3.5, p < 0.01) or reported not having an unmet practical concern (OR 1.3, 95% CI 1.1-1.6, p < 0.01). The structural factors most strongly associated with positive overall experiences included respondents perceiving their oncology specialist was in charge of their follow-up cancer care (OR 5.2, 95% CI 3.6-7.5, p < 0.01) and reporting the coordination of their follow-up cancer care among healthcare providers was good or very good (OR 8.4, 95% CI 6.7-10.6, p < 0.01). CONCLUSION While real-world experiences with follow-up cancer care in Canada are reported to be positive by most cancer survivors included in this study, we found differences exist based on individual and structural factors. A better understanding of the reasons for these differences is required to guide the provision of high-quality follow-up care that is adapted to the needs and resources of individuals and contexts.
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The PANDORA Study: Prevalence and Outcome of Acute Hypoxemic Respiratory Failure in the Pre-COVID-19 Era. Crit Care Explor 2022; 4:e0684. [PMID: 35510152 PMCID: PMC9061169 DOI: 10.1097/cce.0000000000000684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
OBJECTIVES: To establish the epidemiological characteristics, ventilator management, and outcomes in patients with acute hypoxemic respiratory failure (AHRF), with or without acute respiratory distress syndrome (ARDS), in the era of lung-protective mechanical ventilation (MV). DESIGN: A 6-month prospective, epidemiological, observational study. SETTING: A network of 22 multidisciplinary ICUs in Spain. PATIENTS: Consecutive mechanically ventilated patients with AHRF (defined as Pao2/Fio2 ≤ 300 mm Hg on positive end-expiratory pressure [PEEP] ≥ 5 cm H2O and Fio2 ≥ 0.3) and followed-up until hospital discharge. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Primary outcomes were prevalence of AHRF and ICU mortality. Secondary outcomes included prevalence of ARDS, ventilatory management, and use of adjunctive therapies. During the study period, 9,803 patients were admitted: 4,456 (45.5%) received MV, 1,271 (13%) met AHRF criteria (1,241 were included into the study: 333 [26.8%] met Berlin ARDS criteria and 908 [73.2%] did not). At baseline, tidal volume was 6.9 ± 1.1 mL/kg predicted body weight, PEEP 8.4 ± 3.1 cm H2O, Fio2 0.63 ± 0.22, and plateau pressure 21.5 ± 5.4 cm H2O. ARDS patients received higher Fio2 and PEEP than non-ARDS (0.75 ± 0.22 vs 0.59 ± 0.20 cm H2O and 10.3 ± 3.4 vs 7.7 ± 2.6 cm H2O, respectively [p < 0.0001]). Adjunctive therapies were rarely used in non-ARDS patients. Patients without ARDS had higher ventilator-free days than ARDS (12.2 ± 11.6 vs 9.3 ± 9.7 d; p < 0.001). All-cause ICU mortality was similar in AHRF with or without ARDS (34.8% [95% CI, 29.7–40.2] vs 35.5% [95% CI, 32.3–38.7]; p = 0.837). CONCLUSIONS: AHRF without ARDS is a very common syndrome in the ICU with a high mortality that requires specific studies into its epidemiology and ventilatory management. We found that the prevalence of ARDS was much lower than reported in recent observational studies.
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Four consecutive yearly point-prevalence studies in Wales indicate lack of improvement in sepsis care on the wards. Sci Rep 2021; 11:16222. [PMID: 34376757 PMCID: PMC8355110 DOI: 10.1038/s41598-021-95648-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 07/22/2021] [Indexed: 12/15/2022] Open
Abstract
The ‘Sepsis Six’ bundle was promoted as a deliverable tool outside of the critical care settings, but there is very little data available on the progress and change of sepsis care outside the critical care environment in the UK. Our aim was to compare the yearly prevalence, outcome and the Sepsis Six bundle compliance in patients at risk of mortality from sepsis in non-intensive care environments. Patients with a National Early Warning Score (NEWS) of 3 or above and suspected or proven infection were enrolled into four yearly 24-h point prevalence studies, carried out in fourteen hospitals across Wales from 2016 to 2019. We followed up patients to 30 days between 2016–2019 and to 90 days between 2017 and 2019. Out of the 26,947 patients screened 1651 fulfilled inclusion criteria and were recruited. The full ‘Sepsis Six’ care bundle was completed on 223 (14.0%) occasions, with no significant difference between the years. On 190 (11.5%) occasions none of the bundle elements were completed. There was no significant correlation between bundle element compliance, NEWS or year of study. One hundred and seventy (10.7%) patients were seen by critical care outreach; the ‘Sepsis Six’ bundle was completed significantly more often in this group (54/170, 32.0%) than for patients who were not reviewed by critical care outreach (168/1385, 11.6%; p < 0.0001). Overall survival to 30 days was 81.7% (1349/1651), with a mean survival time of 26.5 days (95% CI 26.1–26.9) with no difference between each year of study. 90-day survival for years 2017–2019 was 74.7% (949/1271), with no difference between the years. In multivariate regression we identified older age, heart failure, recent chemotherapy, higher frailty score and do not attempt cardiopulmonary resuscitation orders as significantly associated with increased 30-day mortality. Our data suggests that despite efforts to increase sepsis awareness within the NHS, there is poor compliance with the sepsis care bundles and no change in the high mortality over the study period. Further research is needed to determine which time-sensitive ward-based interventions can reduce mortality in patients with sepsis and how can these results be embedded to routine clinical practice. Trial registration Defining Sepsis on the Wards ISRCTN 86502304 https://doi.org/10.1186/ISRCTN86502304 prospectively registered 09/05/2016.
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Szakmany T, Tuckwell W, Harte E, Wetherall N, Ramachandran S, Price S, Breen H, Killick C, Cheema Y, King C, Richards O. Differences in Inflammatory Marker Kinetics between the First and Second Wave of COVID-19 Patients Admitted to the ICU: A Retrospective, Single-Center Study. J Clin Med 2021; 10:jcm10153290. [PMID: 34362074 PMCID: PMC8348515 DOI: 10.3390/jcm10153290] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Revised: 07/22/2021] [Accepted: 07/23/2021] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND We sought to determine if there was a difference in the longitudinal inflammatory response measured by white blood cell count (WBC), C-reactive protein (CRP), procalcitonin (PCT), and ferritin levels between the first and the second COVID-19 wave of ICU patients. METHODS In a single-center retrospective observational study, ICU patients were enrolled during the first and second waves of the COVID-19 pandemic. Data were collected on patient demographics, comorbidities, laboratory results, management strategies, and complications during the ICU stay. The inflammatory response was evaluated using WBC count, CRP, PCT, and Ferritin levels on the day of admission until Day 28, respectively. Organ dysfunction was measured by the SOFA score. RESULTS 65 patients were admitted during the first and 113 patients during the second wave. WBC and ferritin levels were higher in the second wave. CRP and PCT showed markedly different longitudinal kinetics up until day 28 of ICU stay between the first and second wave, with significantly lower levels in the second wave. Steroid and immunomodulatory therapy use was significantly greater in the second wave. Mortality was similar in both waves. CONCLUSIONS We found that there was a significantly reduced inflammatory response in the second wave, which is likely to be attributable to the more widespread use of immunomodulatory therapies.
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Affiliation(s)
- Tamas Szakmany
- Critical Care Directorate, Grange University Hospital, Aneurin Bevan University Health Board, Llanyravon, Cwmbran NP44 8YN, UK
- Department of Anaesthesia, Intensive Care and Pain Medicine, Division of Population Medicine, Cardiff University, Cardiff CF14 4XN, UK
| | - William Tuckwell
- Department of Anaesthesia, Intensive Care and Pain Medicine, Division of Population Medicine, Cardiff University, Cardiff CF14 4XN, UK
| | - Elsa Harte
- Department of Anaesthesia, Intensive Care and Pain Medicine, Division of Population Medicine, Cardiff University, Cardiff CF14 4XN, UK
| | - Nick Wetherall
- Department of Anaesthesia, Intensive Care and Pain Medicine, Division of Population Medicine, Cardiff University, Cardiff CF14 4XN, UK
| | - Saraswathi Ramachandran
- Department of Anaesthesia, Intensive Care and Pain Medicine, Division of Population Medicine, Cardiff University, Cardiff CF14 4XN, UK
| | - Shannon Price
- Department of Anaesthesia, Intensive Care and Pain Medicine, Division of Population Medicine, Cardiff University, Cardiff CF14 4XN, UK
| | - Henry Breen
- Department of Anaesthesia, Intensive Care and Pain Medicine, Division of Population Medicine, Cardiff University, Cardiff CF14 4XN, UK
| | - Charlotte Killick
- Department of Anaesthesia, Intensive Care and Pain Medicine, Division of Population Medicine, Cardiff University, Cardiff CF14 4XN, UK
| | - Yusuf Cheema
- Department of Anaesthesia, Intensive Care and Pain Medicine, Division of Population Medicine, Cardiff University, Cardiff CF14 4XN, UK
| | - Charles King
- Department of Anaesthesia, Intensive Care and Pain Medicine, Division of Population Medicine, Cardiff University, Cardiff CF14 4XN, UK
| | - Owen Richards
- Department of Anaesthesia, Intensive Care and Pain Medicine, Division of Population Medicine, Cardiff University, Cardiff CF14 4XN, UK
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