A Predictive Nomogram for Predicting Improved Clinical Outcome Probability in Patients with COVID-19 in Zhejiang Province, China.

The aim of this research was to develop a quantitative method for clinicians to predict the probability of improved prognosis in patients with coronavirus disease 2019 (COVID-19). Data on 104 patients admitted to hospital with laboratory-confirmed COVID-19 infection from 10 January 2020 to 26 February 2020 were collected. Clinical information and laboratory findings were collected and compared between the outcomes of improved patients and non-improved patients. The least absolute shrinkage and selection operator (LASSO) logistics regression model and two-way stepwise strategy in the multivariate logistics regression model were used to select prognostic factors for predicting clinical outcomes in COVID-19 patients. The concordance index (C-index) was used to assess the discrimination of the model, and internal validation was performed through bootstrap resampling. A novel predictive nomogram was constructed by incorporating these features. Of the 104 patients included in the study (median age 55 years), 75 (72.1%) had improved short-term outcomes, while 29 (27.9%) showed no signs of improvement. There were numerous differences in clinical characteristics and laboratory findings between patients with improved outcomes and patients without improved outcomes. After a multi-step screening process, prognostic factors were selected and incorporated into the nomogram construction, including immunoglobulin A (IgA), C-reactive protein (CRP), creatine kinase (CK), acute physiology and chronic health evaluation II (APACHE II), and interaction between CK and APACHE II. The C-index of our model was 0.962 (95% confidence interval (CI), 0.931-0.993) and still reached a high value of 0.948 through bootstrapping validation. A predictive nomogram we further established showed close performance compared with the ideal model on the calibration plot and was clinically practical according to the decision curve and clinical impact curve. The nomogram we constructed is useful for clinicians to predict improved clinical outcome probability for each COVID-19 patient, which may facilitate personalized counselling and treatment.

Patients' perspective on supposedly patient-relevant process and outcome parameters: a cross-sectional survey within the 'PRO patients study'.

BACKGROUND: To be able to make informed choices based on their individual preferences, patients need to be adequately informed about treatment options and their potential outcomes. This implies that studies measure the effects of care based on parameters that are relevant to patients. In a previous scoping review, we found a wide variety of supposedly patient-relevant parameters that equally addressed processes and outcomes of care. We were unable to identify a consistent understanding of patient relevance and therefore aimed to develop an empirically based concept including a generic set of patient-relevant parameters. As a first step we evaluated the process and outcome parameters identified in the scoping review from the patients' perspective. METHODS: We conducted a cross-sectional survey among German general practice patients. Ten research practices of Witten/Herdecke University supported the study. During a two-week period in the fall of 2020, patients willing to participate self-administered a short questionnaire. It evaluated the relevance of the 32 parameters identified in the scoping review on a 5-point Likert scale and offered a free-text field for additional parameters. These free-text answers were inductively categorized by two researchers. Quantitative data were analyzed using descriptive statistics. Bivariate analyses were performed to determine whether there are any correlations between rating a parameter as highly relevant and patients' characteristics. RESULTS: Data from 299 patients were eligible for analysis. All outcomes except 'sexuality' and 'frequency of healthcare service utilization' were rated important. 'Confidence in therapy' was rated most important, followed by 'prevention of comorbidity' and 'mobility'. Relevance ratings of five parameters were associated with patients' age and gender, but not with their chronic status. The free-text analysis revealed 15 additional parameters, 12 of which addressed processes of care, i.e., 'enough time in physician consultation'. CONCLUSION: Patients attach great value to parameters addressing processes of care. It appears as though the way in which patients experience the care process is not less relevant than what comes of it. Relevance ratings were not associated with chronic status, but few parameters were gender- and age-related. TRIAL REGISTRATION: Core Outcome Measures in Effectiveness Trials Initiative, registration number: 1685.

Abdominal gastrointestinal imaging findings on computed tomography in patients with COVID-19 and correlation with clinical outcomes.

PURPOSE: Pulmonary imaging finding of Coronavirus disease 2019 (COVID-19) has been widely described, but until now few studies have been published about abdominal radiological presentation. The aim of this study was to provide an overview of abdominal imaging findings in patients with COVID-19 in a multicenter study and correlate them with worse clinical outcomes. MATERIALS AND METHODS: This retrospective study included adult COVID-positive patients with abdominal CT performed from 4/1/2020 to 5/1/2020 from two institutions. Demographic, laboratory and clinical data were recorded, including clinical outcomes. RESULTS: Of 81 COVID-positive patients, the average age was 61 years, 42 (52%) women and 45 (55%) had positive abdominopelvic findings. The most common abdominal imaging features were intestinal imaging findings (20/81, 24%), including colorectal (4/81, 5%) and small bowel thickening (10/81, 12%), intestinal distension (15/81, 18%), pneumatosis (1/81, 1%) and intestinal perforation (1/81, 1%). On multivariate analysis, intestinal imaging findings were associated with higher risk of worse outcome (death or invasive mechanical ventilation) (RR = 2.6, p = 0.04) and higher risk of invasive mechanical ventilation alone (RR = 6.2, p = 0.05). CONCLUSION: Intestinal abnormalities were common findings in COVID-19 patients who underwent abdominal CT and were significantly correlated to worse outcomes in the clinical follow-up.