Radiographic Severity Score Research Articles

Post-treatment Radiographic Severity and Mortality in Mycobacterium avium Complex Pulmonary Disease.

Rationale: Imaging studies are widely performed when treating Mycobacterium avium complex pulmonary disease (MAC-PD); however, the clinical significance of post-treatment radiographic change is unknown. Objectives: To determine whether a deep neural network trained with pulmonary tuberculosis could adequately score the radiographic severity of MAC-PD and then to examine relationships between post-treatment radiographic severity and its change from baseline and long-term prognosis. Methods: We retrospectively collected chest radiographs of adult patients with MAC-PD treated for ⩾6 months at baseline and at 3, 6, 9, and 12 months of treatment. We correlated the radiographic severity score generated by a deep neural network with visual and clinical severity as determined by radiologists and mycobacterial culture status, respectively. The associations between the score, improvement from baseline, and mortality were analyzed using Cox proportional hazards regression. Results: In total, 342 and 120 patients were included in the derivation and validation cohorts, respectively. The network's severity score correlated with radiologists' grading (Spearman coefficient, 0.40) and mycobacterial culture results (odds ratio, 1.02; 95% confidence interval [CI], 1.0-1.05). A significant decreasing trend in the severity score was observed over time (P < 0.001). A higher score at 12 months of treatment was independently associated with higher mortality (adjusted hazard ratio, 1.07; 95% CI, 1.03-1.10). Improvements in radiographic scores from baseline were associated with reduced mortality, regardless of culture conversion (adjusted hazard ratio, 0.42; 95% CI, 0.22-0.80). These findings were replicated in the validation cohort. Conclusions: Post-treatment radiographic severity and improvement from baseline in patients with MAC-PD were associated with long-term survival.

Utility of chest radiograph severity scoring in emergency department for predicting outcomes in COVID-19: A study of 1275 patients

ObjectiveTo measure the reliability and reproducibility of a chest radiograph severity score (CSS) in prognosticating patient's severity of disease and outcomes at the time of disease presentation in the emergency department (ED) with coronavirus disease 2019 (COVID-19). Materials and methodsWe retrospectively studied 1275 consecutive RT-PCR confirmed COVID-19 adult patients presenting to ED from March 2020 through June 2020. Chest radiograph severity score was assessed for each patient by two blinded radiologists. Clinical and laboratory parameters were collected. The rate of admission to intensive care unit, mechanical ventilation or death up to 60 days after the baseline chest radiograph were collected. Primary outcome was defined as occurrence of ICU admission or death. Multivariate logistic regression was performed to evaluate the relationship between clinical parameters, chest radiograph severity score, and primary outcome. ResultsCSS of 3 or more was associated with ICU admission (78 % sensitivity; 73.1 % specificity; area under curve 0.81). CSS and pre-existing diabetes were independent predictors of primary outcome (odds ratio, 7; 95 % CI: 3.87, 11.73; p < 0.001 & odds ratio, 2; 95 % CI: 1–3.4, p 0.02 respectively). No significant difference in primary outcome was observed for those with history of hypertension, asthma, chronic kidney disease or coronary artery disease. ConclusionSemi-quantitative assessment of CSS at the time of disease presentation in the ED predicted outcomes in adults of all age with COVID-19.

Role of chest radiograph in predicting the need for ventilator support in COVID-19 patients.

COVID-19 disease, a pandemic for more than two years, has major morbidity and mortality related to pulmonary involvement. Chest radiography is the main imaging tool for critically ill patients. As the availability of arterial blood gas analysis is limited in the Level I and II healthcare centres, which are major partners in providing healthcare in resource-limited times, we planned the present study. To assess the role of chest radiography in predicting the need for oxygen/ventilator support in critically ill COVID-19 patients. This hospital-based, retrospective study included 135 patients who needed oxygen/ventilator support and had optimal-quality chest radiographs at admission. All the chest X-rays were evaluated and a severity score was calculated on a predesigned pro forma. Statistical evaluation of the data obtained was done using appropriate tools and methods. Males outnumbered females, with a mean age of 54.35 ± 14.49 years. More than 72% of patients included in our study needed ventilator support while the rest needed oxygen support. There was a significant statistical correlation between the chest radiograph severity score and SPO2 /PaO2 levels in our study. Using a cut-off value >8 for the chest radiograph severity score in predicting the need for ventilator support in a Covid-19 patient, the sensitivity, specificity and accuracy was 85.7%, 92.5% and 89.5%, respectively. Chest radiography remains the mainstay of imaging in critically ill COVID-19 patients when they are on multiple life-support systems. Though arterial blood gas analysis is the gold standard tool for assessing the need for oxygen/ventilator support in these patients, the severity score obtained from the initial chest radiograph at the time of admission may also be used as a screening tool. Chest radiography may predict the need for oxygen/ventilator support, allowing time for patients to be moved to an appropriate-level healthcare centre, thus limiting morbidity and mortality.

Abdominal Imaging Findings on Computed Tomography as a Tool for COVID-19 Mortality Risk Assessment: Comparison With Chest Radiograph Severity Scores.

To quantify the association between computed tomography abdomen and pelvis with contrast (CTAP) findings and chest radiograph (CXR) severity score, and the incremental effect of incorporating CTAP findings into predictive models of COVID-19 mortality. This retrospective study was performed at a large quaternary care medical center. All adult patients who presented to our institution between March and June 2020 with the diagnosis of COVID-19 and had a CXR up to 48 hours before a CTAP were included. Primary outcomes were the severity of lung disease before CTAP and mortality within 14 and 30 days. Logistic regression models were constructed to quantify the association between CXR score and CTAP findings. Penalized logistic regression models and random forests were constructed to identify key predictors (demographics, CTAP findings, and CXR score) of mortality. The discriminatory performance of these models, with and without CTAP findings, was summarized using area under the characteristic (AUC) curves. One hundred ninety-five patients (median age, 63 years; 119 men) were included. The odds of having CTAP findings was 3.89 times greater when a CXR score was classified as severe compared with mild (P = 0.002). When CTAP findings were included in the feature set, the AUCs for 14-day mortality were 0.67 (penalized logistic regression) and 0.71 (random forests). Similar values for 30-day mortality were 0.76 and 0.75. When CTAP findings were omitted, all AUC values were attenuated. The CTAP findings were associated with more severe CXR score and may serve as predictors of COVID-19 mortality.

Multi-population generalizability of a deep learning-based chest radiograph severity score for COVID-19.

To tune and test the generalizability of a deep learning-based model for assessment of COVID-19 lung disease severity on chest radiographs (CXRs) from different patient populations.A published convolutional Siamese neural network-based model previously trained on hospitalized patients with COVID-19 was tuned using 250 outpatient CXRs. This model produces a quantitative measure of COVID-19 lung disease severity (pulmonary x-ray severity (PXS) score). The model was evaluated on CXRs from 4 test sets, including 3 from the United States (patients hospitalized at an academic medical center (N = 154), patients hospitalized at a community hospital (N = 113), and outpatients (N = 108)) and 1 from Brazil (patients at an academic medical center emergency department (N = 303)). Radiologists from both countries independently assigned reference standard CXR severity scores, which were correlated with the PXS scores as a measure of model performance (Pearson R). The Uniform Manifold Approximation and Projection (UMAP) technique was used to visualize the neural network results.Tuning the deep learning model with outpatient data showed high model performance in 2 United States hospitalized patient datasets (R = 0.88 and R = 0.90, compared to baseline R = 0.86). Model performance was similar, though slightly lower, when tested on the United States outpatient and Brazil emergency department datasets (R = 0.86 and R = 0.85, respectively). UMAP showed that the model learned disease severity information that generalized across test sets.A deep learning model that extracts a COVID-19 severity score on CXRs showed generalizable performance across multiple populations from 2 continents, including outpatients and hospitalized patients.

COVID-19 pneumonia chest radiographic severity score: variability assessment among experienced and in-training radiologists and creation of a multireader composite score database for artificial intelligence algorithm development.

The purpose was to evaluate reader variability between experienced and in-training radiologists of COVID-19 pneumonia severity on chest radiograph (CXR), and to create a multireader database suitable for AI development. In this study, CXRs from polymerase chain reaction positive COVID-19 patients were reviewed. Six experienced cardiothoracic radiologists and two residents classified each CXR according to severity. One radiologist performed the classification twice to assess intraobserver variability. Severity classification was assessed using a 4-class system: normal (0), mild (1), moderate (2), and severe (3). A median severity score (Rad Med) for each CXR was determined for the six radiologists for development of a multireader database (XCOMS). Kendal Tau correlation and percentage of disagreement were calculated to assess variability. A total of 397 patients (1208 CXRs) were included (mean age, 60 years SD ± 1), 189 men). Interobserver variability between the radiologists ranges between 0.67 and 0.78. Compared to the Rad Med score, the radiologists show good correlation between 0.79-0.88. Residents show slightly lower interobserver agreement of 0.66 with each other and between 0.69 and 0.71 with experienced radiologists. Intraobserver agreement was high with a correlation coefficient of 0.77. In 220 (18%), 707 (59%), 259 (21%) and 22 (2%) CXRs there was a 0, 1, 2 or 3 class-difference. In 594 (50%) CXRs the median scores of the residents and the radiologists were similar, in 578 (48%) and 36 (3%) CXRs there was a 1 and 2 class-difference. Experienced and in-training radiologists demonstrate good inter- and intraobserver agreement in COVID-19 pneumonia severity classification. A higher percentage of disagreement was observed in moderate cases, which may affect training of AI algorithms. Most AI algorithms are trained on data labeled by a single expert. This study shows that for COVID-19 X-ray severity classification there is significant variability and disagreement between radiologist and between residents.

COVID-19 in Kidney Transplant Recipient and Waitlist Patients: Implications of Chest Radiographic Severity Score.

Purpose:To evaluate the chest radiographic severity score (CXR-SS) for coronavirus disease 2019 (COVID-19) patients who are kidney transplant recipients compared with patients on the waitlist.Study Design and Methods:This retrospective cohort includes 78 kidney transplant recipients (50 men, mean age 59.9±11.9 y) and 59 kidney transplant waitlist patients (33 men, mean age 58.8±10.8 y) diagnosed with COVID-19 between March 15 and May 30, 2020 with reverse transcriptase-polymerase chain reaction. Patient chest radiographs were divided into 6 zones and examined for consolidation. Primary outcome was mortality. Secondary outcomes included hospital admission, intensive care unit (ICU) admission, and intubation. Predictors of our primary and secondary outcomes were identified by bivariate analysis and multivariate regression analysis.Results:No significant difference was found in CXR-SS between 2 groups (P=0.087). Transplant recipients had significantly higher rates of hospitalization (odds ratio, 6.8; 95% confidence interval: 1.7, 39.3; P<0.001), ICU admission (odds ratio, 6.5; 95% confidence interval [CI]: 1.8-35.9; P=0.002), intubation (odds ratio, 11; 95% CI: 2.4-96.9; P=0.001), and mortality (odds ratio, 17; 95% CI: 3.9-153.1; P<0.001). A higher CXR-SS was not predictive of mortality, intubation, or ICU admission. CXR-SS was associated with hospital admission overall (odds ratio, 1.613; 95% CI: 1.04-2.49; P=0.0314).Conclusion:The CXR-SS was not predictive of mortality, ICU admission or intubation in our population. Kidney transplant patients with COVID-19 had near universal hospital admission, more than one-third mortality and about a quarter were intubated and admitted to the ICU—all significantly worse outcomes than for patients on the transplant waitlist.

Sextus chest radiograph severity score correlates to clinical outcomes in patients with COVID-19: A cross-sectional study.

The value of chest radiography (CXR) in detection and as an outcome predictor in the management of patients with coronavirus disease-2019 (COVID-19) has not yet been fully understood.To validate a standardized CXR scoring system and assess its prognostic value in hospitalized patients found to have COVID-19 by imaging criteria and to compare it to computed tomography (CT).In this cross-sectional chart review study, patients aged 18-years or older who underwent chest CT at a single institution with an imaging-based diagnosis of COVID-19 between March 15, 2020 to April 15, 2020 were included. Each patient's CXR and coronal CT were analyzed for opacities in a 6-zonal assessment method and aggregated into a "Sextus score." Inter-reader variability and correlation between CXR and coronal CT images were investigated to validate this scoring system. Univariable and multiple logistic regression techniques were used to investigate relationships between CXR scores and clinical parameters in relation to patient outcomes.One hundred twenty-four patients (median [interquartile range] age 58.5 [47.5-69.0] years, 72 [58%] men, 58 [47%] Blacks, and 35 [28%] Hispanics) were included. The CXR Sextus score (range: 0-6) was reliable (inter-rater kappa = 0.76; 95% confidence interval [CI]: 0.69-0.83) and correlated strongly with the CT Sextus score (Spearman correlation coefficient = 0.75, P < .0001). Incremental increases of CXR Sextus scores of 2 points were found to be an independent predictor of intubation (adjusted odds ratio [95% CI]: 4.49 [1.98, 10.20], P = .0003) and prolonged hospitalization (≥10 days) (adjusted odds ratio [95% CI]: 4.06 [1.98, 8.32], P = .0001).The CXR Sextus score was found to be reproducible and CXR-CT severity scores were closely correlated. Increasing Sextus scores were associated with increased risks for intubation and prolonged hospitalization for patients with COVID-19 in a predominantly Black population. The CXR Sextus score may provide insight into identifying and monitoring high-risk patients with COVID-19.

Bacterial infection in dogs with aspiration pneumonia at 2 tertiary referral practices.

BackgroundIn dogs, antimicrobial drugs are widely prescribed for aspiration pneumonia (AP) despite poor documentation of bacterial infection in AP (b‐AP) using bronchoalveolar lavage fluid (BALF) analysis. Interpretating discordant cytology and culture results is challenging, contributing to lack of a criterion standard, and highlighting differences between veterinary and human medical criteria for b‐AP.ObjectivesDetermine how many dogs with AP had BALF collection and differences in diagnosis of b‐AP using veterinary vs human medical criteria. Report findings of noninvasive markers (e.g. fever, band neutrophilia, radiographic severity score) in dogs with and without b‐AP.AnimalsRetrospective cohort study of client‐owned dogs (n = 429) with AP at 2 university veterinary hospitals. Twenty‐four dogs met enrollment criteria.MethodsInclusion criteria were radiographic diagnosis of AP, ≥1 risk factor, CBC findings, and BALF cytology and culture results. Veterinary medical b‐AP criteria were cytology findings compatible with sepsis with or without positive culture, or cytology findings not consistent with sepsis and positive culture (≥1.7 × 103 cfu/mL). Human medical b‐AP criteria required culture with ≥104 cfu/mL or > 7% cells with intracellular bacteria on cytology.ResultsOnly 24/429 dogs met all enrollment criteria; 379/429 dogs lacked BALF collection. Diagnosis of b‐AP differed using veterinary (79%) vs human (29%) medical criteria. Fever, band neutrophils and high radiographic scores were noted in dogs with and without b‐AP.Conclusions and Clinical ImportanceLack of routine BALF collection hampers definitive recognition of bacterial infection in AP. Differences in dogs meeting veterinary vs human medical definitions for b‐AP and usefulness of noninvasive markers warrant further study to improve understanding of the role of bacteria in AP.

Chest X-Ray Findings in COVID-19 Patients Presenting to Primary Care during the Peak of the First Wave of the Pandemic in Qatar: Their Association with Clinical and Laboratory Findings.

When managing coronavirus disease 2019 (COVID-19) patients, radiological imaging complements clinical evaluation and laboratory parameters. We aimed to assess the sensitivity of chest radiography findings in detecting COVID-19, describe those findings, and assess the association of positive chest radiography findings with clinical and laboratory findings. A multicentre, cross-sectional study was conducted involving all primary health care corporation-registered patients (2485 patients) enrolled over a 1-month period during the peak of the 2020 pandemic wave in Qatar. These patients had reverse transcription-polymerase chain reaction-confirmed COVID-19 and underwent chest radiography within 72 hours of the swab test. A positive result on reverse transcription-polymerase chain reaction was the gold standard for diagnosing COVID-19. The sensitivity of chest radiography was calculated. The airspace opacities were mostly distributed in the peripheral and lower lung zones, and most of the patients had bilateral involvement. Pleural effusion was detected in some cases. The risk of having positive chest X-ray findings increased with age, Southeast Asian nationality, fever, or a history of fever and diarrhoea. Patients with cardiac disease, obesity, hypertension, diabetes, and chronic kidney disease were at a higher risk of having positive chest X-ray findings. There was a statistically significant increase in the mean serum albumin, white blood cell count, neutrophil count, and serum C-reactive protein, hepatic enzymes, and total bilirubin with an increase in the radiographic severity score.

Correlation of Chest Radiographic Findings and Coagulation Abnormality with Disease Severity in COVID-19 Positive Patients

Introduction: The pandemic of coronavirus disease 19 (COVID-19) has engulfed most of the world and has constrained already overburdened health care systems, especially in developing countries. There is an urgent need of a rapid investigation to assess disease severity in suspected patients and the baseline chest radiograph may serve as a triage tool. The aim is to correlate chest radiographic findings and coagulation abnormality with disease severity in COVID-19 positive patients. Materials and Methods: This was a retrospective observational study which comprised 100 reverse transcription-polymerase chain reaction positive COVID-19 cases which were clinically stratified into three groups based on clinical parameters. Baseline chest radiograph and serum D-dimer levels at the time of admission for all the patients were reviewed. A radiographic severity score (Radiographic Assessment of Lung Edema [RALE]) was determined for all four quadrants of both lungs. The scores of each quadrant were added to yield the final severity score. Results: Baseline chest radiograph was abnormal in 75% of patients, whereas 25% of patients had normal chest radiograph. Most frequent radiographic abnormality was ground-glass opacity (GGO) (n = 31, 41.3%) followed by lung consolidation (n = 19, 25.3%), while 7 patients (9.3%) had both GGO and consolidation. The most common pattern of disease distribution was bilateral 34 (57.7%) and peripheral in 58 (69%). The optimal cut-off RALE score for identifying symptomatic patients was ≥3 (area under the curve [AUC] 0.760) and for identifying severe cases was ≥7 (AUC 0.870). Similarly, the optimal cut-off D-Dimer value for identifying symptomatic patients was ≥567 ng/ml (AUC 0.836) and for diagnosing severe disease was ≥1200 ng/ml (AUC 0.99). Conclusions: Radiographic RALE score and elevated serum D-Dimer levels correlate strongly with disease severity in COVID-19 patients and can be utilized for early identification of high-risk cases which can ultimately reduce mortality and morbidity.

Predicting outcomes of COVID-19 from admission biomarkers: a prospective UK cohort study

IntroductionCOVID-19 has an unpredictable clinical course, so prognostic biomarkers would be invaluable when triaging patients on admission to hospital. Many biomarkers have been suggested using large observational datasets but sample...

Functional index for hand osteoarthritis (FIHOA) is associated with pain, muscle strength, and EQ-5D in hand osteoarthritis

BackgroundThis study identified whether Functional Index for Hand Osteoarthritis (FIHOA) is associated with pain, hand muscle strength, health-related quality of life, and radiographic severity in hand osteoarthritis (OA).MethodsWe consecutively recruited 95 patients with hand OA. The FIHOA was used to assess questionnaire-based physical function in hand OA. Health-related quality of life was evaluated using EuroQol-5 dimension (EQ-5D). Radiographic changes of hand joints were measured by Kellgren-Lawrence (K-L) grade, which was determined based on total radiographic severity score and number of affected joints. Other measures included patient’s visual analogue scale (VAS) score for pain and performance-based function indexes such as grip and pinch strength. Statistical analysis was performed using Mann-Whitney U test, Spearman’s correlation analysis, and multivariate logistic regression analysis.ResultsFIHOA score was negatively associated with grip and pinch hand strength and EQ-5D and positively correlated to VAS pain (p < 0.05 for all). There were significant differences of grip and pinch strength, VAS pain, EQ-5D index, and EQ-VAS between two FIHOA groups (≤ 4 vs. > 4) (p < 0.05 for all). Multivariate logistic regression analysis showed that higher FIHOA score (FIHOA > 4) was related with increased VAS pain and with lower EQ-5D index (p = 0.008 and p = 0.013, respectively). There was no association between FIHOA score and measures of total radiographic severity score and number of affected joints.ConclusionThis study observes that FIHOA score is associated with patient-reported VAS pain, hand muscle strength indexes, and EQ-5D but not radiographic severity in hand OA.

Retrospective analysis of the effects of Blastomyces antigen concentration in urine and radiographic findings on survival in dogs with blastomycosis

BackgroundThe Blastomyces antigen concentration in urine (BACU) test is used to diagnose blastomycosis and monitor treatment in dogs. It is unknown if a higher BACU is associated with shorter survival.ObjectivesTo determine if the magnitude of BACU before treatment is associated with survival in dogs with blastomycosis.AnimalsFifty‐two dogs with blastomycosis.MethodsRetrospective case review. BACU, radiographic lung severity (RLS) score (0‐4 scale), and survival time up to 1 year after diagnosis were obtained through medical record review of dogs with Blastomyces dermatitidis.ResultsThe overall survival was: discharge, 87%; 1 week, 85%; 2 months, 74%; and 6 months, 69%. BACU correlated with RLS score (r s = 0.33, P = .02). BACU and RLS scores were lower in survivors to 2 months than nonsurvivors (average BACU difference of 2.5 ng/mL, 95% confidence interval [CI]: 0.2‐4.8 ng/mL, P = .04; median RLS difference of 2; range, 0‐4, P = .02). Dogs with BACU <5 ng/mL and dogs with mild (0‐1) RLS scores had a greater proportion surviving than those with BACU >5 ng/mL (P = .03) and dogs with severe (3‐4) RLS scores (P = .04). All dogs with a BACU <5 ng/mL or mild RLS score were alive at last follow‐up (median, 365 days; range, 44‐365 days). In all, 68.1% of other dogs survived to 2 months (95% CI, 54.8%‐84.8%).Conclusions and Clinical ImportanceDogs with lower BACU and RLS scores have improved survival; however, it is unclear what specific cutoffs should be used for prognosis.

Fluoxetine Might Improve Survival of Patients With COVID-19 Pneumonia: A Retrospective Case-Control Study

Objective: We undertook this study to determine the effect of fluoxetine use on the survival of hospitalised coronavirus disease (COVID-19) pneumonia patients. Methods: This retrospective case–control chart review study used data extracted from the medical records of adults who were hospitalised with moderate or severe COVID-19 pneumonia at the Uzsoki Teaching Hospital of the Semmelweis University in Budapest, Hungary, between 17 March and 22 April 2021, and received anti-COVID-19 therapy including favipiravir, remdesivir, and baricitinib or their combination, in addition to standard medical treatment; 110 patients received 20 mg fluoxetine orally once daily as adjuvant medication. Multivariable logistic regression was used to evaluate the association between fluoxetine use and mortality.Results: Of the 269 participants, 205 (76.2%) survived and 64 (23.8%) died between days 2 and 28 after hospitalisation. Fluoxetine use was associated to a decrease of mortality risk (OR [95% CI] 0.242 [0.111–0.525], pConclusion: Provisional to confirmation in randomised controlled studies, fluoxetine may be a potent treatment for COVID-19 pneumonia.

Ultrasound Findings were Associated With Radiographic Changes, But Not Clinical and Functional Outcomes in Hand Osteoarthritis.

There is a debate over the relevance of ultrasound abnormalities to the pain, functional impairment, and radiologic severity in hand osteoarthritis (OA) This study aims to determine the association between ultrasound abnormalities and clinical, functional, and radiographic measures in hand OA. A total of 66 patients was consecutively enrolled All patients with gray-scale synovitis, joint effusion, and osteophytes were examined by ultrasound for 20 hand joints Radiographic changes in both hands were evaluated by the Kellgren-Lawrence (K-L) grading system and were described as total radiographic severity score and number of affected joints Other measures were also assessed, including each patient's visual analogue scale for pain, the Functional Index for Hand Osteoarthritis for functional disability, and grip and pinch strength for hand muscle strength. In total, 10 patients with gray-scale synovitis, 35 with joint effusion, and 66 with osteophytes were detected in hand OA scans on ultrasound Osteophytes on ultrasound were significantly associated with total radiographic severity score and number of affected joint (r=0293, p=0003 and r=0336, p<0001, respectively) In addition, there were weak associations of synovitis and joint effusion with radiographic changes Patients with higher total radiographic severity score showed larger number of ultrasound-detected abnormalities, such as synovitis, joint effusion, and osteophytes (p=0011, p=0002, and p<0001, respectively). This study shows that ultrasound findings, especially osteophytes, were associated with radiographic changes based on K-L grade, but not clinical and functional status in hand OA.

Combining Initial Radiographs and Clinical Variables Improves Deep Learning Prognostication in Patients with COVID-19 from the Emergency Department.

PurposeTo train a deep learning classification algorithm to predict chest radiograph severity scores and clinical outcomes in patients with coronavirus disease 2019 (COVID-19).Materials and MethodsIn this retrospective cohort study, patients aged 21–50 years who presented to the emergency department (ED) of a multicenter urban health system from March 10 to 26, 2020, with COVID-19 confirmation at real-time reverse-transcription polymerase chain reaction screening were identified. The initial chest radiographs, clinical variables, and outcomes, including admission, intubation, and survival, were collected within 30 days (n = 338; median age, 39 years; 210 men). Two fellowship-trained cardiothoracic radiologists examined chest radiographs for opacities and assigned a clinically validated severity score. A deep learning algorithm was trained to predict outcomes on a holdout test set composed of patients with confirmed COVID-19 who presented between March 27 and 29, 2020 (n = 161; median age, 60 years; 98 men) for both younger (age range, 21–50 years; n = 51) and older (age >50 years, n = 110) populations. Bootstrapping was used to compute CIs.ResultsThe model trained on the chest radiograph severity score produced the following areas under the receiver operating characteristic curves (AUCs): 0.80 (95% CI: 0.73, 0.88) for the chest radiograph severity score, 0.76 (95% CI: 0.68, 0.84) for admission, 0.66 (95% CI: 0.56, 0.75) for intubation, and 0.59 (95% CI: 0.49, 0.69) for death. The model trained on clinical variables produced an AUC of 0.64 (95% CI: 0.55, 0.73) for intubation and an AUC of 0.59 (95% CI: 0.50, 0.68) for death. Combining chest radiography and clinical variables increased the AUC of intubation and death to 0.88 (95% CI: 0.79, 0.96) and 0.82 (95% CI: 0.72, 0.91), respectively.ConclusionThe combination of imaging and clinical information improves outcome predictions.Supplemental material is available for this article.© RSNA, 2020

Chest radiographs may assist in predicting the outcome in the early phase of Covid-19. UK district general hospital experience of Covid-19 first wave

ABSTRACT Objectives: Severe Acute Respiratory Syndrome coronavirus-2 (SARS-CoV-2) has caused enormous strain on health-care systems worldwide. Early recognition of prognostic markers and appropriate management of patients with coronavirus disease 2019 (Covid-19) remains a major global health concern, particularly when resources are limited. We undertook a study to see if basic tests can inform frontline clinicians of disease trajectory in individual patients with COVID-19. Methods: We retrospectively assessed characteristics of the first 50 consecutive patients admitted to district general hospital in the United Kingdom with positive SARS-Cov-2 RNA swabs. Results: Our patient cohort shared broad similarities with previously published data on comorbidities and presenting features. We have found that chest radiographic assessment differed between survivors and non-survivors. Air space shadowing in middle zones were more prevalent in non-survivors (73.3% vs. 35.5% [p = 0.027]). Chest radiograph severity score was also found to be higher in non-survivors compared to survivors (3 vs. 1.5 [p = 0.007]). Conclusions: In this small retrospective study, our results suggest features of chest radiographs at presentation may provide a helpful tool for prognostication. In environments with constrained computed tomography (CT) imaging with serial chest radiographs could be a cost-effective tool in the assessment of Covid-19 patients.

FRI0426 EMOTIONAL COMPONENTS AND INFLAMMATION ARE HIGHLY RELEVANT IN PAIN REPORTED BY KNEE OSTEOARTHRITIC PATIENTS

Background:Osteoarthritis (OA) is a leading cause of disability in elderly and the most frequent form is knee OA (KOA) (1). Pain is the principal symptom that leads patients to visit clinicians, and it is the main reason, together with functionality, for patients to undergo a total knee replacement (TKR) after apparently unsuccessful conservative (CNV) treatments (2). It is well-known that there is a poor correlation between the radiographic severity (based on Kellgren &amp; Lawrence (KL) score) and the reported pain (3), so other variables may be responsible for the intensity of pain.Objectives:Identifying the leading causes of pain in each patient would improve the management of the disease. In this study we aim to investigate the role of emotional components, nociception process and inflammation in treatment decision, as a global measure of pain suffered by KOA patients, taking into account sex, age and BMI.Methods:KOA patients, carefully selected to be idiopathic, graded 2-3 in KL, were recruited at Hospital del Mar. The following variables were recorded: WOMAC, Hospital Anxiety and Depression Scale (HAD), Pain Catastrophizing Scale (PCS), tender points (TP) (measure with a pressure algometer at points defined in the Arendt-Nielsen extended peripatellar map), synovial hypertrophy (SH) and effusion (SE) (measure by ultrasounds), and PCR and ESR serum levels. Patients were classified according to 4 factors: treatment (CNV/TKR), sex, age (60-67/68-75) and BMI (&lt;30/&gt;30). All groups were balanced. Multivariate and correlations analysis were performed.Results:Eighty-seven patients have been recruited. Patients from the TKR group present significant higher WOMAC (p=0.000), PCS (p=0.002) and SE (p= 0.038) values than CNV ones, without interaction with the other factors, except for SE, that presents interaction with BMI (Fig. 1). Women reported significant upper WOMAC (p=0.001) and HAD rates (p=0.020), but also higher number of TP and ESR levels (p= 0.000 and 0.002, respectively). The level of sensitization was significantly higher in women than in men (p=0.000). Several significant correlations were found, mainly between WOMAC and emotional components, as well as between TP and WOMAC, PCS, and inflammation markers (Table 1).Conclusion:PCS is an emotional component that could explain in part the lack of correlation between joint status and patient’s symptomatology. Working out strategies for pain management could improve this PCS values and therefore reduce the need for TKR. Furthermore, this study also highlights the two mainly types of OA etiology: mechanical and inflammatory. It suggests that inflammation is mostly responsible for OA progression in patients with low BMI, and plays a strong role in women pathology. Finally, specific treatments targeting central pain sensitization could also improve the management of the pathology in women.

Clinical and Chest Radiography Features Determine Patient Outcomes in Young and Middle-aged Adults with COVID-19.

BackgroundChest radiography has not been validated for its prognostic utility in evaluating patients with coronavirus disease 2019 (COVID-19).PurposeTo analyze the prognostic value of a chest radiograph severity scoring system for younger (nonelderly) patients with COVID-19 at initial presentation to the emergency department (ED); outcomes of interest included hospitalization, intubation, prolonged stay, sepsis, and death.Materials and MethodsIn this retrospective study, patients between the ages of 21 and 50 years who presented to the ED of an urban multicenter health system from March 10 to March 26, 2020, with COVID-19 confirmation on real-time reverse transcriptase polymerase chain reaction were identified. Each patient’s ED chest radiograph was divided into six zones and examined for opacities by two cardiothoracic radiologists, and scores were collated into a total concordant lung zone severity score. Clinical and laboratory variables were collected. Multivariable logistic regression was used to evaluate the relationship between clinical parameters, chest radiograph scores, and patient outcomes.ResultsThe study included 338 patients: 210 men (62%), with median age of 39 years (interquartile range, 31–45 years). After adjustment for demographics and comorbidities, independent predictors of hospital admission (n = 145, 43%) were chest radiograph severity score of 2 or more (odds ratio, 6.2; 95% confidence interval [CI]: 3.5, 11; P < .001) and obesity (odds ratio, 2.4 [95% CI: 1.1, 5.4] or morbid obesity). Among patients who were admitted, a chest radiograph score of 3 or more was an independent predictor of intubation (n = 28) (odds ratio, 4.7; 95% CI: 1.8, 13; P = .002) as was hospital site. No significant difference was found in primary outcomes across race and ethnicity or those with a history of tobacco use, asthma, or diabetes mellitus type II.ConclusionFor patients aged 21–50 years with coronavirus disease 2019 presenting to the emergency department, a chest radiograph severity score was predictive of risk for hospital admission and intubation.© RSNA, 2020Online supplemental material is available for this article.