Dataset Information

Physiological respiratory parameters in pre-hospital patients with suspected COVID-19: A prospective cohort study.

ABSTRACT:

Background

The COVID-19 pandemic has presented emergency medical services (EMS) worldwide with the difficult task of identifying patients with COVID-19 and predicting the severity of their illness. The aim of this study was to investigate whether physiological respiratory parameters in pre-hospital patients with COVID-19 differed from those without COVID-19 and if they could be used to aid EMS personnel in the prediction of illness severity.

Methods

Patients with suspected COVID-19 were included by EMS personnel in Uppsala, Sweden. A portable respiratory monitor based on pneumotachography was used to sample the included patient's physiological respiratory parameters. A questionnaire with information about present symptoms and background data was completed. COVID-19 diagnoses and hospital admissions were gathered from the electronic medical record system. The physiological respiratory parameters of patients with and without COVID-19 were then analyzed using descriptive statistical analysis and logistic regression.

Results

Between May 2020 and January 2021, 95 patients were included, and their physiological respiratory parameters analyzed. Of these patients, 53 had COVID-19. Using adjusted logistic regression, the odds of having COVID-19 increased with respiratory rate (95% CI 1.000-1.118), tidal volume (95% CI 0.996-0.999) and negative inspiratory pressure (95% CI 1.017-1.152). Patients admitted to hospital had higher respiratory rates (p<0.001) and lower tidal volume (p = 0.010) compared to the patients who were not admitted. Using adjusted logistic regression, the odds of hospital admission increased with respiratory rate (95% CI 1.081-1.324), rapid shallow breathing index (95% CI 1.006-1.040) and dead space percentage of tidal volume (95% CI 1.027-1.159).

Conclusion

Patients taking smaller, faster breaths with less pressure had higher odds of having COVID-19 in this study. Smaller, faster breaths and higher dead space percentage also increased the odds of hospital admission. Physiological respiratory parameters could be a useful tool in detecting COVID-19 and predicting hospital admissions, although more research is needed.

SUBMITTER: Malberg J

PROVIDER: S-EPMC8412304 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundThe COVID-19 pandemic is challenging advanced health systems, which are dealing with an overwhelming number of patients in need of intensive care for respiratory failure, often requiring intubation. Prone positioning in intubated patients is known to reduce mortality in moderate-to-severe acute respiratory distress syndrome. We aimed to investigate feasibility and effect on gas exchange of prone positioning in awake, non-intubated patients with COVID-19-related pneumonia.MethodsIn this prospective, feasibility, cohort study, patients aged 18-75 years with a confirmed diagnosis of COVID-19-related pneumonia receiving supplemental oxygen or non-invasive continuous positive airway pressure were recruited from San Gerardo Hospital, Monza, Italy. We collected baseline data on demographics, anthropometrics, arterial blood gas, and ventilation parameters. After baseline data collection, patients were helped into the prone position, which was maintained for a minimum duration of 3 h. Clinical data were re-collected 10 min after prone positioning and 1 h after returning to the supine position. The main study outcome was the variation in oxygenation (partial pressure of oxygen [PaO2]/fractional concentration of oxygen in inspired air [FiO2]) between baseline and resupination, as an index of pulmonary recruitment. This study is registered on ClinicalTrials.gov, NCT04365959, and is now complete.FindingsBetween March 20 and April 9, 2020, we enrolled 56 patients, of whom 44 (79%) were male; the mean age was 57·4 years (SD 7·4) and the mean BMI was 27·5 kg/m2 (3·7). Prone positioning was feasible (ie, maintained for at least 3 h) in 47 patients (83·9% [95% CI 71·7 to 92·4]). Oxygenation substantially improved from supine to prone positioning (PaO2/FiO2 ratio 180·5 mm Hg [SD 76·6] in supine position vs 285·5 mm Hg [112·9] in prone position; p<0·0001). After resupination, improved oxygenation was maintained in 23 patients (50·0% [95% CI 34·9-65·1]; ie, responders); however, this improvement was on average not significant compared with before prone positioning (PaO2/FiO2 ratio 192·9 mm Hg [100·9] 1 h after resupination; p=0·29). Patients who maintained increased oxygenation had increased levels of inflammatory markers (C-reactive protein: 12·7 mg/L [SD 6·9] in responders vs 8·4 mg/L [6·2] in non-responders; and platelets: 241·1 × 103/μL [101·9] vs 319·8 × 103/μL [120·6]) and shorter time between admission to hospital and prone positioning (2·7 days [SD 2·1] in responders vs 4·6 days [3·7] in non-responders) than did those for whom improved oxygenation was not maintained. 13 (28%) of 46 patients were eventually intubated, seven (30%) of 23 responders and six (26%) of 23 non-responders (p=0·74). Five patients died during follow-up due to underlying disease, unrelated to study procedure.InterpretationProne positioning was feasible and effective in rapidly ameliorating blood oxygenation in awake patients with COVID-19-related pneumonia requiring oxygen supplementation. The effect was maintained after resupination in half of the patients. Further studies are warranted to ascertain the potential benefit of this technique in improving final respiratory and global outcomes.FundingUniversity of Milan-Bicocca.

Project description:ObjectivesTo derive and validate risk prediction algorithms to estimate the risk of covid-19 related mortality and hospital admission in UK adults after one or two doses of covid-19 vaccination.DesignProspective, population based cohort study using the QResearch database linked to data on covid-19 vaccination, SARS-CoV-2 results, hospital admissions, systemic anticancer treatment, radiotherapy, and the national death and cancer registries.SettingsAdults aged 19-100 years with one or two doses of covid-19 vaccination between 8 December 2020 and 15 June 2021.Main outcome measuresPrimary outcome was covid-19 related death. Secondary outcome was covid-19 related hospital admission. Outcomes were assessed from 14 days after each vaccination dose. Models were fitted in the derivation cohort to derive risk equations using a range of predictor variables. Performance was evaluated in a separate validation cohort of general practices.ResultsOf 6 952 440 vaccinated patients in the derivation cohort, 5 150 310 (74.1%) had two vaccine doses. Of 2031 covid-19 deaths and 1929 covid-19 hospital admissions, 81 deaths (4.0%) and 71 admissions (3.7%) occurred 14 days or more after the second vaccine dose. The risk algorithms included age, sex, ethnic origin, deprivation, body mass index, a range of comorbidities, and SARS-CoV-2 infection rate. Incidence of covid-19 mortality increased with age and deprivation, male sex, and Indian and Pakistani ethnic origin. Cause specific hazard ratios were highest for patients with Down's syndrome (12.7-fold increase), kidney transplantation (8.1-fold), sickle cell disease (7.7-fold), care home residency (4.1-fold), chemotherapy (4.3-fold), HIV/AIDS (3.3-fold), liver cirrhosis (3.0-fold), neurological conditions (2.6-fold), recent bone marrow transplantation or a solid organ transplantation ever (2.5-fold), dementia (2.2-fold), and Parkinson's disease (2.2-fold). Other conditions with increased risk (ranging from 1.2-fold to 2.0-fold increases) included chronic kidney disease, blood cancer, epilepsy, chronic obstructive pulmonary disease, coronary heart disease, stroke, atrial fibrillation, heart failure, thromboembolism, peripheral vascular disease, and type 2 diabetes. A similar pattern of associations was seen for covid-19 related hospital admissions. No evidence indicated that associations differed after the second dose, although absolute risks were reduced. The risk algorithm explained 74.1% (95% confidence interval 71.1% to 77.0%) of the variation in time to covid-19 death in the validation cohort. Discrimination was high, with a D statistic of 3.46 (95% confidence interval 3.19 to 3.73) and C statistic of 92.5. Performance was similar after each vaccine dose. In the top 5% of patients with the highest predicted covid-19 mortality risk, sensitivity for identifying covid-19 deaths within 70 days was 78.7%.ConclusionThis population based risk algorithm performed well showing high levels of discrimination for identifying those patients at highest risk of covid-19 related death and hospital admission after vaccination.

Project description:ObjectivesOne major goal of the emergency department (ED) is to decide, whether patients need to be hospitalised or can be sent home safely. We aim at providing criteria for these decisions without knowing the SARS-CoV-2 test result in suspected cases.SettingTertiary emergency medicine.ParticipantsAll patients were treated at the ED of the Charité during the pandemic peak and underwent SARS-CoV-2 testing. Patients with positive test results were characterised in detail and underwent a 14-day-follow-up.Primary and secondary outcome measuresLogistic regression and classification and regression tree (CART) analyses were performed to identify predictors (primary endpoint), which confirm safe discharge. The clinical endpoint was all-cause mortality or need for mechanical ventilation during index stay or after readmission.ResultsThe primary test population of suspected COVID-19 consisted of n=1255 cases, 45.2% were women (n=567). Of these, n=110 tested positive for SARS-CoV-2 (8.8%). The median age of SARS-CoV-2-positive cases was 45 years (IQR: 33-66 years), whereas the median age of the group tested negative for SARS-CoV-2 was 42 years (IQR: 30-60 years) (p=0.096). 43.6% were directly admitted to hospital care.CART analysis identified the variables oxygen saturation (<95%), dyspnoea and history of cardiovascular (CV) disease to distinguish between high and low-risk groups. If all three variables were negative, most patients were discharged from ED, and the incidence of the clinical endpoint was 0%. The validation cohort confirmed the safety of discharge using these variables and revealed an incidence of the clinical endpoint from 14.3% in patients with CV disease, 9.4% in patients with dyspnoea and 18.2% in patients with O2 satuaration below 95%.ConclusionsBased on easily available variables like dyspnoea, oxygen saturation, history of CV disease, approximately 25% of patients subsequently confirmed with COVID-19 can be identified for safe discharge.Trial registration numberDRKS00023117.