Admission chest CT score predicts 5-day outcome in patients with COVID-19.
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ABSTRACT:
SUBMITTER: Mahdjoub E
PROVIDER: S-EPMC8824444 | biostudies-literature | 2020 Aug
REPOSITORIES: biostudies-literature
Publications
Admission chest CT score predicts 5-day outcome in patients with COVID-19.
Mahdjoub Elyas E Mohammad Waqaas W Lefevre Thomas T Debray Marie-Pierre MP Khalil Antoine A
Intensive care medicine 20200528 8
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Project description:BackgroundCOVID-19 may result in multiorgan failure and death. Early detection of patients at risk may allow triage and more intense monitoring. The aim of this study was to develop a simple, objective admission score, based on laboratory tests, that identifies patients who are likely going to deteriorate.MethodsThis is a retrospective cohort study of all COVID-19 patients admitted to a tertiary academic medical center in New York City during the COVID-19 crisis in spring 2020. The primary combined endpoint included intubation, stage 3 acute kidney injury (AKI), or death. Laboratory tests available on admission in at least 70% of patients (and age) were included for univariate analysis. Tests that were statistically or clinically significant were then included in a multivariate binary logistic regression model using stepwise exclusion. 70% of all patients were used to train the model, and 30% were used as an internal validation cohort. The aim of this study was to develop and validate a model for COVID-19 severity based on biomarkers.ResultsOut of 2545 patients, 833 (32.7%) experienced the primary endpoint. 53 laboratory tests were analyzed, and of these, 47 tests (and age) were significantly different between patients with and without the endpoint. The final multivariate model included age, albumin, creatinine, C-reactive protein, and lactate dehydrogenase. The area under the ROC curve was 0.850 (CI [95%]: 0.813, 0.889), with a sensitivity of 0.800 and specificity of 0.761. The probability of experiencing the primary endpoint can be calculated as p=e (-2.4475+0.02492age - 0.6503albumin+0.81926creat+0.00388CRP+0.00143LDH)/1+e (-2.4475+ 0.02492age - 0.6503albumin+0.81926creat+0.00388CRP+0.00143LDH).ConclusionsOur study demonstrated that poor outcome in COVID-19 patients can be predicted with good sensitivity and specificity using a few laboratory tests. This is useful for identifying patients at risk during admission.
| S-EPMC8189812 | biostudies-literature
Project description:ObjectivesChest CT has been widely used to screen and to evaluate the severity of COVID-19 disease in the early stages of infection without severe acute respiratory syndrome, but no prospective data are available to study the relationship between extent of lung damage and short-term mortality. The objective was to evaluate association between standardized simple visual lung damage CT score (vldCTs) at admission, which does not require any software, and 30-day mortality.MethodsIn a single-center prospective cohort of COVID-19 patients included during 4 weeks, the presence and extent of ground glass opacities(GGO), consolidation opacities, or both of them were visually assessed in each of the 5 lung lobes (score from 0 to 4 per lobe depending on the percentage and out of 20 per patient = vldCTs) after the first chest CT performed to detect COVID-19 pneumonia.ResultsAmong 210 confirmed COVID-19 patients, the number of survivors and non-survivors was 162 (77%) and 48 (23%), respectively at 30 days. vldCTs was significantly higher in non-survivors, and the AUC of vldCTs to distinguish survivors and non-survivors was 0.72 (95%CI 0.628-0.807, p < 0.001); the best cut-off vldCTs value was 7. During follow-up, significant differences in discharges and 30-day mortality were observed between patients with vldCTs ≥ 7 versus vldCTs < 7: (98 [85.2%] vs 49 [51.6%]; p < 0.001 and 36 [37.9%] vs 12 [12.4%]; p < 0.001, respectively. The 30-day mortality increased if vldCTs ≥ 7 (HR, 3.16 (1.50-6.43); p = 0.001), independent of age, respiratory rate and oxygen saturation levels, and comorbidities at admission.ConclusionsBy using chest CT in COVID-19 patients, extensive lung damage can be visually assessed with a score related to 30-day mortality independent of conventional risk factors of the disease.Key points• In non-selected COVID-19 patients included prospectively during 4 weeks, the extent of ground glass opacities(GGO) and consolidation opacities evaluated by a simple visual score was related to 30-day mortality independent of age, respiratory rate, oxygen saturation levels, comorbidities, and hs-troponin I level at admission. • This severity score should be incorporated into risk stratification algorithms and in structured chest CT reports requiring a standardized reading by radiologists in case of COVID-19.
| S-EPMC8083100 | biostudies-literature
Project description: Not available
| S-EPMC7361510 | biostudies-literature
Project description:BackgroundChest CT is prognostic in Covid-19 but there is a lack of consensus on how to report the CT findings. A chest CT scoring system, ÖCoS, was implemented in clinical routine on 1 April 2020, in Örebro Region, Sweden. The ÖCoS-severity score measures the extent of lung involvement. The objective of the study was to evaluate the ÖCoS scores as predictors of the clinical course of Covid-19.MethodsPopulation based study including data from all hospitalized patients with Covid-19 in Örebro Region during March to July 2020. We evaluated the correlations between CT scores at the time of admission to hospital and intensive care in relation to hospital and intensive care length of stay (LoS), intensive care admission and death. C-reactive protein and lymphocyte count were included as covariates in multivariate regression analyses.ResultsIn 381 included patients, the ÖCoS-severity score at admission closely correlated to hospital length of stay, and intensive care admission or death. At admission to intensive care, the ÖCoS-severity score correlated with intensive care length of stay. The ÖCoS-severity score was superior to basic inflammatory biomarkers in predicting clinical outcomes.ConclusionChest CT visual scoring at admission to hospital predicted the clinical course of Covid-19 pneumonia.
| S-EPMC8054497 | biostudies-literature
Project description:ObjectivesTo evaluate the impact of vaccination on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and moreover on coronavirus disease 2019 (COVID-19) pneumonia, by assessing the extent of lung disease using the CT severity score (CTSS).MethodsBetween September 2021 and February 2022, SARS-CoV-2 positive patients who underwent chest CT were retrospectively enrolled. Anamnestic and clinical data, including vaccination status, were obtained. All CT scans were evaluated by two readers using the CTSS, based on a 25-point scale. Univariate and multivariate logistic regression analyses were performed to evaluate the associations between CTSS and clinical or demographic variables. An outcome analysis was used to differentiate clinical outcome between vaccinated and unvaccinated patients.ResultsOf the 1040 patients (537 males, 503 females; median age 58 years), 678 (65.2%) were vaccinated and 362 (34.8%) unvaccinated. Vaccinated patients showed significantly lower CTSS compared to unvaccinated patients (p < 0.001), also when patients without lung involvement (CTSS = 0) were excluded (p < 0.001). Older age, male gender and lower number of doses administered were associated with higher CTSS, however, in the multivariate analysis, vaccination status resulted to be the variable with the strongest association with CTSS. Clinical outcomes were significantly worse in unvaccinated patients, including higher number of ICU admissions and higher mortality rates.ConclusionsLung involvement during COVID-19 was significantly less severe in vaccinated patients compared with unvaccinated patients, who also showed worse clinical outcomes. Vaccination status was the strongest variable associated to the severity of COVID-related, more than age, gender, and number of doses administered.
| S-EPMC10338619 | biostudies-literature
Project description:ObjectiveThe 2019 Coronavirus (COVID-19) results in a wide range of clinical severity and there remains a need for prognostic tools which identify patients at risk of rapid deterioration and who require critical care. Chest radiography (CXR) is routinely obtained at admission of COVID-19 patients. However, little is known regarding correlates between CXR severity and time to intubation. We hypothesize that the degree of opacification on CXR at time of admission independently predicts need and time to intubation.MethodsIn this retrospective cohort study, we reviewed COVID-19 patients who were admitted to an urban medical center during March 2020 that had a CXR performed on the day of admission. CXRs were divided into 12 lung zones and were assessed by two blinded thoracic radiologists. A COVID-19 opacification rating score (CORS) was generated by assigning one point for each lung zone in which an opacity was observed. Underlying comorbidities were abstracted and assessed for association.ResultsOne hundred forty patients were included in this study and 47 (34%) patients required intubation during the admission. Patients with CORS ≥ 6 demonstrated significantly higher rates of early intubation within 48 h of admission and during the hospital stay (ORs 24 h, 19.8, p < 0.001; 48 h, 28.1, p < 0.001; intubation during hospital stay, 6.1, p < 0.0001). There was no significant correlation between CORS ≥ 6 and age, sex, BMI, or any underlying cardiac or pulmonary comorbidities.ConclusionsCORS ≥ 6 at the time of admission predicts need for intubation, with significant increases in intubation at 24 and 48 h, independent of comorbidities.Key points• Chest radiography at the time of admission independently predicts time to intubation within 48 h and during the hospital stay in COVID-19 patients. • More opacities on chest radiography are associated with several fold increases in early mechanical ventilation among COVID-19 patients. • Chest radiography is useful in identifying COVID-19 patients whom may rapidly deteriorate and help inform clinical management as well as hospital bed and ventilation allocation.
| S-EPMC7553374 | biostudies-literature
Project description:BackgroundThe aim of this study was to quantify COVID-19 pneumonia features using CT performed at time of admission to emergency department in order to predict patients' hypoxia during the hospitalization and outcome.MethodsConsecutive chest CT performed in the emergency department between March 1st and April 7th 2020 for COVID-19 pneumonia were analyzed. The three features of pneumonia (GGO, semi-consolidation and consolidation) and the percentage of well-aerated lung were quantified using a HU threshold based software. ROC curves identified the optimal cut-off values of CT parameters to predict hypoxia worsening and hospital discharge. Multiple Cox proportional hazards regression was used to analyze the capability of CT quantitative features, demographic and clinical variables to predict the time to hospital discharge.ResultsSeventy-seven patients (median age 56-years-old, 51 men) with COVID-19 pneumonia at CT were enrolled. The quantitative features of COVID-19 pneumonia were not associated to age, sex and time-from-symptoms onset, whereas higher number of comorbidities was correlated to lower well-aerated parenchyma ratio (rho = -0.234, p = 0.04) and increased semi-consolidation ratio (rho = -0.303, p = 0.008). Well-aerated lung (≤57%), semi-consolidation (≥17%) and consolidation (≥9%) predicted worst hypoxemia during hospitalization, with moderate areas under curves (AUC 0.76, 0.75, 0.77, respectively). Multiple Cox regression identified younger age (p < 0.01), female sex (p < 0.001), longer time-from-symptoms onset (p = 0.049), semi-consolidation ≤17% (p < 0.01) and consolidation ≤13% (p = 0.03) as independent predictors of shorter time to hospital discharge.ConclusionQuantification of pneumonia features on admitting chest CT predicted hypoxia worsening during hospitalization and time to hospital discharge in COVID-19 patients.
| S-EPMC8081746 | biostudies-literature
Project description:ObjectiveNoninvasive positive-pressure ventilation (NPPV) emerged as an efficient tool for treatment of COVID-19 pneumonia. The factors influencing NPPV failure still are elusive. The aim of the study was to investigate the relationships between semiquantitative chest computed tomography (CT) scoring and NPPV failure and mortality in patients with COVID-19.DesignObservational study.SettingNonintensive care setting.ParticipantsA total of 112 patients consecutively admitted for COVID-19 pneumonia.InterventionsUsual care including various degrees of respiratory support.Measurements and main resultsThe semiquantitative CT score was calculated at hospital admission. Subgroups were identified according to the ventilation strategy used (oxygen delivered by Venturi mask n = 53; NPPV-responder n = 38; NPPV-failure n = 21). The study's primary endpoint was the use of NPPV. The secondary endpoints were NPPV failure and in-hospital death, respectively. CT score progressively increased among groups (six v nine v 14, p < 0.05 among all). CT score was an independent predictor of all study endpoints (primary endpoint: 1.25 [95% confidence interval {CI} 1.1-1.4], p = 0.001; NPPV failure: 1.41 [95% CI 1.18-1.69], p < 0.001; in-hospital mortality: 1.21 [95% CI 1.07-1.38], p = 0.003). According to receiver operator characteristics curve analysis, CT score was the most accurate variable for prediction of NPPV failure (area under the curve 0.862 with p < 0.001; p < 0.05 v other variables).ConclusionsThe authors reported the common and effective use of NPPV in patients with COVID-19 pneumonia. In the authors' population, a semiquantitative chest CT analysis at hospital admission accurately identified those patients responding poorly to NPPV.
| S-EPMC8434692 | biostudies-literature
Project description:BackgroundChest computed tomography (CT) is a useful tool for the diagnosis of coronavirus disease-2019 (COVID-19), although its exact value for predicting critical illness remains unclear. This study evaluated the efficacy of chest CT to predict disease progression, pulmonary complications, and viral positivity duration.MethodsA single-center cohort study was conducted by consecutively including hospitalized patients with confirmed COVID-19. The chest CT patterns were described and a total severity score was calculated. The predictive accuracy of the severity score was evaluated using the receiver operating characteristic analysis, while a Cox proportional hazards regression model was implemented to identify the radiological features that are linked to prolonged duration of viral positivity.ResultsOverall, 42 patients were included with 10 of them requiring intensive care unit admission. The most common lesions were ground glass opacities (92.9%), consolidation (66.7%), and crazy-paving patterns (61.9%). The total severity score significantly correlated with inflammatory and respiratory distress markers, as well as with admission CURB-65 and PSI/PORT scores. It was estimated to predict critical illness with a sensitivity and specificity of 75% and 70%, respectively. Time-to-event analysis indicated that patients without ground-glass opacities presented significantly shorter median viral positivity (16 vs. 27 days).ConclusionsChest CT severity score positively correlates with markers of COVID-19 severity and presents promising efficacy in predicting critical illness. It is suggested that ground-glass opacities are linked to prolonged viral positivity. Further studies should confirm the efficacy of the severity score and elucidate the long-term pulmonary effects of COVID-19.
| S-EPMC7972804 | biostudies-literature
Project description:ObjectivesEnlarged main pulmonary artery diameter (MPAD) resulted to be associated with pulmonary hypertension and mortality in a non-COVID-19 setting. The aim was to investigate and validate the association between MPAD enlargement and overall survival in COVID-19 patients.MethodsThis is a cohort study on 1469 consecutive COVID-19 patients submitted to chest CT within 72 h from admission in seven tertiary level hospitals in Northern Italy, between March 1 and April 20, 2020. Derivation cohort (n = 761) included patients from the first three participating hospitals; validation cohort (n = 633) included patients from the remaining hospitals. CT images were centrally analyzed in a core-lab blinded to clinical data. The prognostic value of MPAD on overall survival was evaluated at adjusted and multivariable Cox's regression analysis on the derivation cohort. The final multivariable model was tested on the validation cohort.ResultsIn the derivation cohort, the median age was 69 (IQR, 58-77) years and 537 (70.6%) were males. In the validation cohort, the median age was 69 (IQR, 59-77) years with 421 (66.5%) males. Enlarged MPAD (≥ 31 mm) was a predictor of mortality at adjusted (hazard ratio, HR [95%CI]: 1.741 [1.253-2.418], p < 0.001) and multivariable regression analysis (HR [95%CI]: 1.592 [1.154-2.196], p = 0.005), together with male gender, old age, high creatinine, low well-aerated lung volume, and high pneumonia extension (c-index [95%CI] = 0.826 [0.796-0.851]). Model discrimination was confirmed on the validation cohort (c-index [95%CI] = 0.789 [0.758-0.823]), also using CT measurements from a second reader (c-index [95%CI] = 0.790 [0.753;0.825]).ConclusionEnlarged MPAD (≥ 31 mm) at admitting chest CT is an independent predictor of mortality in COVID-19.Key points• Enlargement of main pulmonary artery diameter at chest CT performed within 72 h from the admission was associated with a higher rate of in-hospital mortality in COVID-19 patients. • Enlargement of main pulmonary artery diameter (≥ 31 mm) was an independent predictor of death in COVID-19 patients at adjusted and multivariable regression analysis. • The combined evaluation of clinical findings, lung CT features, and main pulmonary artery diameter may be useful for risk stratification in COVID-19 patients.
| S-EPMC7755582 | biostudies-literature