scholarly journals COVID-19 in-hospital mortality and mode of death in a dynamic and non-restricted tertiary care model in Germany

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0242127 ◽  
Author(s):  
Siegbert Rieg ◽  
Maja von Cube ◽  
Johannes Kalbhenn ◽  
Stefan Utzolino ◽  
Katharina Pernice ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Tertiary Care ◽  
Study Entry ◽  
Hospital Death ◽  
Care Model ◽  
Cox Regression Analysis ◽  
Hospitalised Patients

Background Reported mortality of hospitalised Coronavirus Disease-2019 (COVID-19) patients varies substantially, particularly in critically ill patients. So far COVID-19 in-hospital mortality and modes of death under state of the art care have not been systematically studied. Methods This retrospective observational monocenter cohort study was performed after implementation of a non-restricted, dynamic tertiary care model at the University Medical Center Freiburg, an experienced acute respiratory distress syndrome (ARDS) and extracorporeal membrane-oxygenation (ECMO) referral center. All hospitalised patients with PCR-confirmed SARS-CoV-2 infection were included. The primary endpoint was in-hospital mortality, secondary endpoints included major complications and modes of death. A multistate analysis and a Cox regression analysis for competing risk models were performed. Modes of death were determined by two independent reviewers. Results Between February 25, and May 8, 213 patients were included in the analysis. The median age was 65 years, 129 patients (61%) were male. 70 patients (33%) were admitted to the intensive care unit (ICU), of which 57 patients (81%) received mechanical ventilation and 23 patients (33%) ECMO support. Using multistate methodology, the estimated probability to die within 90 days after COVID-19 onset was 24% in the whole cohort. If the levels of care at time of study entry were accounted for, the probabilities to die were 16% if the patient was initially on a regular ward, 47% if in the intensive care unit (ICU) and 57% if mechanical ventilation was required at study entry. Age ≥65 years and male sex were predictors for in-hospital death. Predominant complications–as judged by two independent reviewers–determining modes of death were multi-organ failure, septic shock and thromboembolic and hemorrhagic complications. Conclusion In a dynamic care model COVID-19-related in-hospital mortality remained very high. In the absence of potent antiviral agents, strategies to alleviate or prevent the identified complications should be investigated. In this context, multistate analyses enable comparison of models-of-care and treatment strategies and allow estimation and allocation of health care resources.

scholarly journals COVID-19 in-hospital mortality and mode of death in a dynamic and non-restricted tertiary care model in Germany

2020 ◽  
Author(s):  
Siegbert Rieg ◽  
Maja von Cube ◽  
Johannes Kalbhenn ◽  
Stefan Utzolino ◽  
Katharina Pernice ◽  
...  
Keyword(s):  
Mechanical Ventilation ◽  
Hospital Mortality ◽  
Cox Regression ◽  
Medical Center ◽  
Tertiary Care ◽  
Study Entry ◽  
Hospital Death ◽  
Care Model ◽  
Cox Regression Analysis ◽  
Hospitalised Patients

Abstract BackgroundReported mortality of hospitalised COVID-19 patients varies substantially, particularly in critically ill patients. So far COVID-19 in-hospital mortality and modes of death under optimised care conditions have not been systematically studied.MethodsThis retrospective observational monocenter cohort study was performed after implementation of a non-restricted, dynamic tertiary care model at the University Medical Center Freiburg, an experienced ARDS and ECMO referral center. All hospitalised patients with PCR-confirmed SARS-CoV-2 infection were included. The primary endpoint was in-hospital mortality, secondary endpoints included major complications and modes of death. A multistate analysis and a Cox regression analysis for competing risk models were performed. Modes of death were determined by two independent reviewers.ResultsBetween February 25, and May 8, 213 patients were included in the analysis. The median age was 65 years, 129 patients (61%) were male. 70 patients (33%) were admitted to the intensive care unit (ICU), of which 57 patients (81%) received mechanical ventilation and 23 patients (33%) extracorporeal membrane-oxygenation (ECMO) support. According to the multistate model the probability to die within 90 days after COVID-19 onset was 24% in the whole cohort. If the levels of care at time of study entry were accounted for, the probabilities to die were 16% if the patient was initially on a regular ward, 47% if in the ICU and 57% if mechanical ventilation was required at study entry. Age ≥ 65 years and male sex were predictors for in-hospital death. Predominant complications – as judged by two independent reviewers – determining modes of death were multi-organ failure, septic shock and thromboembolic and hemorrhagic complications.ConclusionIn a dynamic care model COVID-19-related in-hospital mortality remained substantial. In the absence of potent antiviral agents, strategies to alleviate or prevent the identified complications should be investigated. In this context, multistate analyses enable comparison of models-of-care and treatment strategies and allow estimation and allocation of health care resources.RegistrationGerman Clinical Trials Register (identifier DRKS00021775), retrospectively registered June 10, 2020.

scholarly journals COVID-19 in-hospital mortality and mode of death in a dynamic and non-restricted tertiary care model in Germany

2020 ◽  
Author(s):  
Siegbert Rieg ◽  
Maja von Cube ◽  
Johannes Kalbhenn ◽  
Stefan Utzolino ◽  
Katharina Pernice ◽  
...  
Keyword(s):  
Mechanical Ventilation ◽  
Hospital Mortality ◽  
Cox Regression ◽  
Medical Center ◽  
Tertiary Care ◽  
Study Entry ◽  
Hospital Death ◽  
Care Model ◽  
Cox Regression Analysis ◽  
Hospitalised Patients

Background Reported mortality of hospitalised COVID-19 patients varies substantially, particularly in critically ill patients. So far COVID-19 in-hospital mortality and modes of death under optimised care conditions have not been systematically studied. Methods This retrospective observational monocenter cohort study was performed after implementation of a non-restricted, dynamic tertiary care model at the University Medical Center Freiburg, an experienced ARDS and ECMO referral center. All hospitalised patients with PCR-confirmed SARS-CoV-2 infection were included. The primary endpoint was in-hospital mortality, secondary endpoints included major complications and modes of death. A multistate analysis and a Cox regression analysis for competing risk models were performed. Modes of death were determined by two independent reviewers. Results Between February 25, and May 8, 213 patients were included in the analysis. The median age was 65 years, 129 patients (61%) were male. 70 patients (33%) were admitted to the intensive care unit (ICU), of which 57 patients (81%) received mechanical ventilation and 23 patients (33%) extracorporeal membrane-oxygenation (ECMO) support. According to the multistate model the probability to die within 90 days after COVID-19 onset was 24% in the whole cohort. If the levels of care at time of study entry were accounted for, the probabilities to die were 16% if the patient was initially on a regular ward, 47% if in the ICU and 57% if mechanical ventilation was required at study entry. Age >=65 years and male sex were predictors for in-hospital death. Predominant complications - as judged by two independent reviewers - determining modes of death were multi-organ failure, septic shock and thromboembolic and hemorrhagic complications. Conclusion In a dynamic care model COVID-19-related in-hospital mortality remained substantial. In the absence of potent antiviral agents, strategies to alleviate or prevent the identified complications should be investigated. In this context, multistate analyses enable comparison of models-of-care and treatment strategies and allow estimation and allocation of health care resources.

scholarly journals Hemotransfusion and mechanical ventilation time are associated with intra-hospital mortality in patients with traumatic brain injury admitted to intensive care unit

2016 ◽  
Vol 74 (8) ◽  
pp. 644-649 ◽  
Author(s):  
Kelson James Almeida ◽  
Ânderson Batista Rodrigues ◽  
Luiz Euripedes Almondes Santana Lemos ◽  
Marconi Cosme Soares de Oliveira Filho ◽  
Brisa Fideles Gandara ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Traumatic Brain Injury ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Brain Injury ◽  
Hospital Mortality ◽  
Hospital Death ◽  
Factors Associated ◽  
Ventilation Time ◽  
Mechanical Ventilation Time

ABSTRACT Objective To identify the factors associated with the intra-hospital mortality in patients with traumatic brain injury (TBI) admitted to intensive care unit (ICU). Methods The sample included patients with TBI admitted to the ICU consecutively in a period of one year. It was defined as variables the epidemiological characteristics, factors associated with trauma and variables arising from clinical management in the ICU. Results The sample included 87 TBI patients with a mean age of 28.93 ± 12.72 years, predominantly male (88.5%). The intra-hospital mortality rate was of 33.33%. The initial univariate analysis showed a significant correlation of intra-hospital death and the following variables: the reported use of alcohol (p = 0.016), hemotransfusion during hospitalization (p = 0.036), and mechanical ventilation time (p = 0.002). Conclusion After multivariate analysis, the factors associated with intra-hospital mortality in TBI patients admitted to the intensive care unit were the administration of hemocomponents and mechanical ventilation time.

scholarly journals Global Muscle Strength But Not Grip Strength Predicts Mortality and Length of Stay in a General Population in a Surgical Intensive Care Unit

2012 ◽  
Vol 92 (12) ◽  
pp. 1546-1555 ◽  
Author(s):  
Jeanette J. Lee ◽  
Karen Waak ◽  
Martina Grosse-Sundrup ◽  
Feifei Xue ◽  
Jarone Lee ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Length Of Stay ◽  
Hospital Mortality ◽  
Grip Strength ◽  
Muscle Weakness ◽  
Manual Muscle Testing ◽  
Surgical Intensive Care Unit ◽  
Muscle Testing

Background Paresis acquired in the intensive care unit (ICU) is common in patients who are critically ill and independently predicts mortality and morbidity. Manual muscle testing (MMT) and handgrip dynamometry assessments have been used to evaluate muscle weakness in patients in a medical ICU, but similar data for patients in a surgical ICU (SICU) are limited. Objective The purpose of this study was to evaluate the predictive value of strength measured by MMT and handgrip dynamometry at ICU admission for in-hospital mortality, SICU length of stay (LOS), hospital LOS, and duration of mechanical ventilation. Design This investigation was a prospective, observational study. Methods One hundred ten patients were screened for eligibility for testing in the SICU of a large, academic medical center. The Acute Physiology and Chronic Health Evaluation (APACHE) II score, diagnoses, and laboratory data were collected. Measurements were obtained by MMT quantified with the sum (total) score on the Medical Research Council Scale and by handgrip dynamometry. Outcome data, including in-hospital mortality, SICU LOS, hospital LOS, and duration of mechanical ventilation, were collected for all participants. Results One hundred seven participants were eligible for testing; 89% were tested successfully at a median of 3 days (25th–75th percentiles=3–6 days) after admission. Sedation was the most frequent barrier to testing (70.6%). Manual muscle testing was identified as an independent predictor of mortality, SICU LOS, hospital LOS, and duration of mechanical ventilation. Grip strength was not independently associated with these outcomes. Limitations This study did not address whether muscle weakness translates to functional outcome impairment. Conclusions In contrast to handgrip strength, MMT reliably predicted in-hospital mortality, duration of mechanical ventilation, SICU LOS, and hospital LOS.

scholarly journals Clinical course and severity outcome indicators among COVID 19 hospitalized patients in relation to comorbidities distribution Mexican cohort

2020 ◽  
Author(s):  
Genny Carrillo ◽  
Nina Mendez Dominguez ◽  
Kassandra D Santos Zaldivar ◽  
Andrea Rochel Perez ◽  
Mario Azuela Morales ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Respiratory Diseases ◽  
Risk Estimation ◽  
Clinical Manifestations ◽  
Case Fatality ◽  
Hospitalized Patients ◽  
Hospital Death ◽  
Outcome Indicators

Introduction: COVID-19 affected worldwide, causing to date, around 500,000 deaths. In Mexico, by April 29, the general case fatality was 6.52%, with 11.1% confirmed case mortality and hospital recovery rate around 72%. Once hospitalized, the odds for recovery and hospital death rates depend mainly on the patients' comorbidities and age. In Mexico, triage guidelines use algorithms and risk estimation tools for severity assessment and decision-making. The study's objective is to analyze the underlying conditions of patients hospitalized for COVID-19 in Mexico concerning four severity outcomes. Materials and Methods: Retrospective cohort based on registries of all laboratory-confirmed patients with the COVID-19 infection that required hospitalization in Mexico. Independent variables were comorbidities and clinical manifestations. Dependent variables were four possible severity outcomes: (a) pneumonia, (b) mechanical ventilation (c) intensive care unit, and (d) death; all of them were coded as binary Results: We included 69,334 hospitalizations of laboratory-confirmed and hospitalized patients to June 30, 2020. Patients were 55.29 years, and 62.61% were male. Hospital mortality among patients aged<15 was 9.11%, 51.99% of those aged >65 died. Male gender and increasing age predicted every severity outcome. Diabetes and hypertension predicted every severity outcome significantly. Obesity did not predict mortality, but CKD, respiratory diseases, cardiopathies were significant predictors. Conclusion: Obesity increased the risk for pneumonia, mechanical ventilation, and intensive care admittance, but it was not a predictor of in-hospital death. Patients with respiratory diseases were less prone to develop pneumonia, to receive mechanical ventilation and intensive care unit assistance, but they were at higher risk of in-hospital death.

scholarly journals Intensive Care Unit Outcomes Among Patients With Lung Cancer in the Surveillance, Epidemiology, and End Results–Medicare Registry

2012 ◽  
Vol 30 (14) ◽  
pp. 1686-1691 ◽  
Author(s):  
Christopher G. Slatore ◽  
Laura M. Cecere ◽  
Jennifer L. LeTourneau ◽  
Maya E. O'Neil ◽  
Jonathan P. Duckart ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Intensive Care Unit ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Surgical Resection ◽  
Cox Regression ◽  
Patient Characteristics ◽  
Patient Centered ◽  
End Results

Purpose Lung cancer is the leading cause of cancer-related mortality. Intensive care unit (ICU) use among patients with cancer is increasing, but data regarding ICU outcomes for patients with lung cancer are limited. Patients and Methods We used the Surveillance, Epidemiology, and End Results (SEER) –Medicare registry (1992 to 2007) to conduct a retrospective cohort study of patients with lung cancer who were admitted to an ICU for reasons other than surgical resection of their tumor. We used logistic and Cox regression to evaluate associations of patient characteristics and hospital mortality and 6-month mortality, respectively. We calculated adjusted associations for mechanical ventilation receipt with hospital and 6-month mortality. Results Of the 49,373 patients with lung cancer admitted to an ICU for reasons other than surgical resection, 76% of patients survived the hospitalization, and 35% of patients were alive 6 months after discharge. Receipt of mechanical ventilation was associated with increased hospital mortality (adjusted odds ratio, 6.95; 95% CI, 6.89 to 7.01; P < .001), and only 15% of these patients were alive 6 months after discharge. Of all ICU patients with lung cancer, the percentage of patients who survived 6 months from discharge was 36% for patients diagnosed in 1992 and 32% for patients diagnosed in 2005, whereas it was 16% and 11% for patients who received mechanical ventilation, respectively. Conclusion Most patients with lung cancer enrolled in Medicare who are admitted to an ICU die within 6 months of admission. To improve patient-centered care, these results should guide shared decision making between patients with lung cancer and their clinicians before an ICU admission.

scholarly journals Prediction of early unplanned intensive care unit readmission in a UK tertiary care hospital: a cross-sectional machine learning approach

BMJ Open ◽  
2017 ◽  
Vol 7 (9) ◽  
pp. e017199 ◽  
Author(s):  
Thomas Desautels ◽  
Ritankar Das ◽  
Jacob Calvert ◽  
Monica Trivedi ◽  
Charlotte Summers ◽  
...  
Keyword(s):  
Machine Learning ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Tertiary Care Hospital ◽  
Tertiary Care ◽  
Value Added ◽  
Secondary Outcome ◽  
Hospital Death ◽  
Care Hospital ◽  
Icu Discharge

ObjectivesUnplanned readmissions to the intensive care unit (ICU) are highly undesirable, increasing variance in care, making resource planning difficult and potentially increasing length of stay and mortality in some settings. Identifying patients who are likely to suffer unplanned ICU readmission could reduce the frequency of this adverse event.SettingA single academic, tertiary care hospital in the UK.ParticipantsA set of 3326 ICU episodes collected between October 2014 and August 2016. All records were of patients who visited an ICU at some point during their stay. We excluded patients who were ≤16 years of age; visited ICUs other than the general and neurosciences ICU; were missing crucial electronic patient record measurements; or had indeterminate ICU discharge outcomes or very early or extremely late discharge times. After exclusion, 2018 outcome-labelled episodes remained.Primary and secondary outcome measuresArea under the receiver operating characteristic curve (AUROC) for prediction of unplanned ICU readmission or in-hospital death within 48 hours of first ICU discharge.ResultsIn 10-fold cross-validation, an ensemble predictor was trained on data from both the target hospital and the Medical Information Mart for Intensive Care (MIMIC-III) database and tested on the target hospital’s data. This predictor discriminated between patients with the unplanned ICU readmission or death outcome and those without this outcome, attaining mean AUROC of 0.7095 (SE 0.0260), superior to the purpose-built Stability and Workload Index for Transfer (SWIFT) score (AUROC=0.6082, SE 0.0249; p=0.014, pairwise t-test).ConclusionsDespite the inherent difficulties, we demonstrate that a novel machine learning algorithm based on transfer learning could achieve good discrimination, over and above that of the treating clinicians or the value added by the SWIFT score. Accurate prediction of unplanned readmission could be used to target resources more efficiently.

scholarly journals Prognostic factors and outcome of Post-Neonatal Tetanus in an intensive care unit of a Tertiary Care Hospital

2019 ◽  
Vol 35 (5) ◽  
Author(s):  
Nighat Sultana ◽  
Attia Bari ◽  
Mehwish Faizan ◽  
Muhammad Sarwar
Keyword(s):  
Risk Factors ◽  
Intensive Care Unit ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Prognostic Factors ◽  
Tertiary Care Hospital ◽  
Tertiary Care ◽  
Neonatal Tetanus ◽  
P Value ◽  
Care Hospital

Objective: To determine the prognostic factors and outcome of tetanus in children of post-neonatal age admitted in the intensive care unit (ICU) of a tertiary care hospital. Methods: This prospective cross sectional study, carried out in the Pediatric ICU of The Children’s Hospital Lahore from Jan 2013 to March 2017. Children of both genders with age range of two months to 16 years diagnosed clinically as tetanus were included. All 132 patients were scrutinized for all possible risk factors, need for mechanical ventilation and outcome. Data was analyzed by SPSS version 20. Results: Mean age of children was 7.5±3.4 years with male predominance (70.5%). Only (38.6%) received three doses of vaccination but none had booster dose. Trauma (43.2%) encompassed maximum predisposing factor followed by ear or nose prick and ear discharge. Mean duration of ICU stay was 20±13.3 days. Mortality rate was (17.4%). Ventilator support was given to (78.8%). Neurological outcome was normal in (82.6%). Trauma, ear or nose prick in girls and ear discharge were significantly associated with poor outcome and death with p-value of <0.001, 0.011 and <0.001 respectively. Other factors associated with poor outcome were need for mechanical ventilation and neurological impairment with p-value of 0.001 and <0.001 respectively. Conclusion: Tetanus is causing our children to suffer from devastating disease. Vaccination status is not satisfactory and along with trauma, ear discharge and ear or nose prick are identifiable risk factors. To combat these issues large scale vaccination and booster doses remains promising option. doi: https://doi.org/10.12669/pjms.35.5.656 How to cite this:Sultana N, Bari A, Faizan M, Sarwar M. Prognostic factors and outcome of Post-Neonatal Tetanus in an intensive care unit of a Tertiary Care Hospital. Pak J Med Sci. 2019;35(5):---------. doi: https://doi.org/10.12669/pjms.35.5.656 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

scholarly journals A study on symptoms of children mechanically ventilated in a paediatric intensive care unit of a minimum resource setting in tertiary care centre

2019 ◽  
Vol 6 (2) ◽  
pp. 574
Author(s):  
Korisipati Ankireddy ◽  
Aruna Jyothi K.
Keyword(s):  
Intensive Care Unit ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Critically Ill ◽  
Tertiary Care ◽  
Limited Resource ◽  
Critically Ill Children ◽  
Invasive Ventilation ◽  
Ventilator Support ◽  
Mechanically Ventilated

Background: Mechanical ventilation, a lifesaving intervention in a critical care unit is under continuous evolution in modern era. Despite this, the management of children with invasive ventilation in developing countries with limited resources is challenging. The study analyses the clinical profile, indications, complications and duration of ventilator care in limited resource settings. Methods: A retrospective study of critically ill children mechanically ventilated in an intensive care unit of a tertiary care government hospital.   Results: A total of 120 children required invasive ventilation during the study period of 1 year. Infants constituted the majority (70%), and males (65%) were marginally more than female children (35%). Respiratory failure was the most common indication for invasive ventilation (55%). The major underlying etiology for invasive ventilation was bronchopneumonia associated with septic shock (30%); and the same also required a prolonged duration of ventilation of >72 hours (35%). Prolonged ventilator support of >72 hours predisposed to more complications as well as a prolonged hospital stay of >2 weeks and above, which was statistically significant. Upper lobe atelectasis (50%) and ventilator associated pneumonia (25%) were the major complications. The mortality rate of present study population was 40% as opposed to the overall mortality of 10%.   Conclusions: Present study highlights that critically ill children can be managed with mechanical ventilation even in limited resource settings. The child should be assessed clinically regarding the tolerance to extubation every day, to minimise the complications associated with prolonged ventilator support.

scholarly journals The Impact of Hyperoxia on Outcome of Patients Treated with Noninvasive Respiratory Support

2020 ◽  
Vol 2020 ◽  
pp. 1-6
Author(s):  
Seyhan Pala Cifci ◽  
Yasemin Urcan Tapan ◽  
Bengu Turemis Erkul ◽  
Yusuf Savran ◽  
Bilgin Comert
Keyword(s):  
Intensive Care Unit ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Length Of Stay ◽  
Hospital Mortality ◽  
Oxygen Therapy ◽  
Invasive Mechanical Ventilation ◽  
Respiratory Support ◽  
High Flow Oxygen ◽  
The Impact

Objective. Oxygen therapy is one of the most common treatment modalities for hypoxemic patients, but target goals for normoxemia are not clearly defined. Therefore, iatrogenic hyperoxia is a very common situation. The results from the recent clinical researches about hyperoxia indicate that hyperoxia can be related to worse outcomes than expected in some critically ill patients. According to our literature knowledge, there are not any reports researching the effect of hyperoxia on clinical course of patients who are not treated with invasive mechanical ventilation. In this study, we aimed to determine the effect of hyperoxia on mortality, and length of stay and also possible side effects of hyperoxia on the patients who are treated with oxygen by noninvasive devices. Materials and Methods. One hundred and eighty-seven patients who met inclusion criteria, treated in Dokuz Eylul University Medical Intensive Care Unit between January 1, 2016, and October 31, 2018, were examined retrospectively. These patients’ demographic data, oxygen saturation (SpO2) values for the first 24 hours, APACHE II (Acute Physiology and Chronic Health Evaluation II) scores, whether they needed intubation, if they did how many days they got ventilated, length of stay in intensive care unit and hospital, maximum PaO2 values of the first day, oxygen treatment method of the first 24 hours, and the rates of mortality were recorded. Results. Hyperoxemia was determined in 62 of 187 patients who were not treated with invasive mechanic ventilation in the first 24 hours of admission. Upon further investigation of the relation between comorbid situations and hyperoxia, hyperoxia frequency in patients with COPD was detected to be statistically low (16% vs. 35%, p<0.008). Hospital mortality was significantly high (51.6% vs. 35.2%, p<0.04) in patients with hyperoxia. When the types of oxygen support therapies were investigated, hyperoxia frequency was found higher in patients treated with supplemental oxygen (nasal cannula, oronasal mask, high flow oxygen therapy) than patients treated with NIMV (44.2% vs. 25.5%, p<0.008). After exclusion of 56 patients who were intubated and treated with invasive mechanical ventilation after the first 24 hours, hyperoxemia was determined in 46 of 131 patients. Mortality in patients with hyperoxemia who were not treated with invasive mechanical ventilation during hospital stay was statistically higher when compared to normoxemic patients (41.3% vs 15.3%, p<0.001). Conclusion. We report that hyperoxemia increases the hospital mortality in patients treated with noninvasive respiratory support. At the same time, we determined that hyperoxemia frequency was lower in COPD patients and the ones treated with NIMV. Conservative oxygen therapy strategy can be suggested to decrease the hyperoxia prevalence and mortality rates.

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