Development and external validation of the DOAT and DOATS scores: simple decision support tools to identify disease progression among nonelderly patients with mild/moderate COVID-19.

BACKGROUND: During the fifth wave of the coronavirus disease 2019 (COVID-19) pandemic in Japan, which took place between June and September 2021, a significant number of COVID-19 cases with deterioration occurred in unvaccinated individuals < 65 years old. However, the risk factors for COVID-19 deterioration in this specific population have not yet been determined. This study developed a prediction method to identify COVID-19 patients < 65 years old who are at a high risk of deterioration. METHODS: This retrospective study analyzed data from 1,675 patients < 65 years old who were admitted to acute care institutions in Fukushima with mild-to-moderate-1 COVID-19 based on the Japanese disease severity criteria prior to the fifth wave. For validation, 324 similar patients were enrolled from 3 hospitals in Yamagata. Logistic regression analyses using cluster-robust variance estimation were used to determine predictors of disease deterioration, followed by creation of risk prediction scores. Disease deterioration was defined as the initiation of medication for COVID-19, oxygen inhalation, or mechanical ventilation starting one day or later after admission. RESULTS: The patients whose condition deteriorated (8.6%) tended to be older, male, have histories of smoking, and have high body temperatures, low oxygen saturation values, and comorbidities, such as diabetes/obesity and hypertension. Stepwise variable selection using logistic regression to predict COVID-19 deterioration retained comorbidities of diabetes/obesity (DO), age (A), body temperature (T), and oxygen saturation (S). Two predictive scores were created based on the optimism-corrected regression coefficients: the DOATS score, including all of the above risk factors, and the DOAT score, which was the DOATS score without oxygen saturation. In the original cohort, the areas under the receiver operating characteristic curve (AUROCs) of the DOATS and DOAT scores were 0.81 (95% confidence interval [CI] 0.77-0.85) and 0.80 (95% CI 0.76-0.84), respectively. In the validation cohort, the AUROCs for each score were both 0.76 (95% CI 0.69-0.83), and the calibration slopes were both 0.80. A decision curve analysis confirmed the clinical practicability of both scores in the validation cohort. CONCLUSIONS: We established two prediction scores that can quickly evaluate the risk of COVID-19 deterioration in mild/moderate patients < 65 years old.

Efficacy of exponentiation method with a convolutional neural network for classifying lung nodules on CT images by malignancy level.

OBJECTIVES: The aim of this study was to examine the performance of a convolutional neural network (CNN) combined with exponentiating each pixel value in classifying benign and malignant lung nodules on computed tomography (CT) images. MATERIALS AND METHODS: Images in the Lung Image Database Consortium-Image Database Resource Initiative (LIDC-IDRI) were analyzed. Four CNN models were then constructed to classify the lung nodules by malignancy level (malignancy level 1 vs. 2, malignancy level 1 vs. 3, malignancy level 1 vs. 4, and malignancy level 1 vs. 5). The exponentiation method was applied for exponent values of 1.0 to 10.0 in increments of 0.5. Accuracy, sensitivity, specificity, and area under the curve of receiver operating characteristics (AUC-ROC) were calculated. These statistics were compared between an exponent value of 1.0 and all other exponent values in each model by the Mann-Whitney U-test. RESULTS: In malignancy 1 vs. 4, maximum test accuracy (MTA; exponent value = 2.0, 3.0, 3.5, 4.5, 5.0, 5.5, 6.0, 6.5, 7.0, 7.5, 8.0, 8.5, 9.0, 9.5, and 10.0) and specificity (6.5, 7.0, and 9.0) were improved by up to 0.012 and 0.037, respectively. In malignancy 1 vs. 5, MTA (6.5 and 7.0) and sensitivity (1.5) were improved by up to 0.030 and 0.0040, respectively. CONCLUSIONS: The exponentiation method improved the performance of the CNN in the task of classifying lung nodules on CT images as benign or malignant. The exponentiation method demonstrated two advantages: improved accuracy, and the ability to adjust sensitivity and specificity by selecting an appropriate exponent value. CLINICAL RELEVANCE STATEMENT: Adjustment of sensitivity and specificity by selecting an exponent value enables the construction of proper CNN models for screening, diagnosis, and treatment processes among patients with lung nodules. KEY POINTS: • The exponentiation method improved the performance of the convolutional neural network. • Contrast accentuation by the exponentiation method may derive features of lung nodules. • Sensitivity and specificity can be adjusted by selecting an exponent value.

Real-world clinical outcomes of treatment with molnupiravir for patients with mild-to-moderate coronavirus disease 2019 during the Omicron variant pandemic.

It is unclear whether molnupiravir has a beneficial effect on vaccinated patients infected with the Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We here evaluated the efficacy of molnupiravir in patients with mild-to-moderate coronavirus disease 2019 (COVID-19) during the Omicron variant surge in Fukushima Prefecture, Japan. We enrolled patients with mild-to-moderate COVID-19 who were admitted to hospitals between January and April, 2022. Clinical deterioration after admission was compared between molnupiravir users (n = 230) and non-users (n = 690) after 1:3 propensity score matching. Additionally, we performed forward stepwise multivariate logistic regression analysis to evaluate the association between clinical deterioration after admission and molnupiravir treatment in the 1:3 propensity score-matched subjects. The characteristics of participants in both groups were balanced as indicated by covariates with a standardized mean difference of < 0.1. Regarding comorbidities, there was no imbalance between the two groups, except for the presence of hypertension, dyslipidemia, diabetes mellitus, and cardiac disease. The clinical deterioration rate was significantly lower in the molnupiravir users compared to the non-users (3.90% vs 8.40%; P = 0.034). Multivariate logistic regression analysis demonstrated that receiving molnupiravir was a factor for preventing deterioration (odds ratio 0.448; 95% confidence interval 0.206-0.973; P = 0.042), independent of other covariates. This real-world study demonstrates that molnupiravir contributes to the prevention of deterioration in COVID-19 patients after hospitalization during the Omicron variant phase.

Real-world clinical outcomes of treatment with casirivimab-imdevimab among patients with mild-to-moderate coronavirus disease 2019 during the Delta variant pandemic.

Background: Mutations of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may reduce the efficacy of neutralizing monoclonal antibody therapy against coronavirus disease 2019 (COVID-19). We here evaluated the efficacy of casirivimab-imdevimab in patients with mild-to-moderate COVID-19 during the Delta variant surge in Fukushima Prefecture, Japan. Methods: We enrolled 949 patients with mild-to-moderate COVID-19 who were admitted to hospital between July 24, 2021 and September 30, 2021. Clinical deterioration after admission was compared between casirivimab-imdevimab users (n = 314) and non-users (n = 635). Results: The casirivimab-imdevimab users were older (P < 0.0001), had higher body temperature (≥ 38°C) (P < 0.0001) and greater rates of history of cigarette smoking (P = 0.0068), hypertension (P = 0.0004), obesity (P < 0.0001), and dyslipidemia (P < 0.0001) than the non-users. Multivariate logistic regression analysis demonstrated that receiving casirivimab-imdevimab was an independent factor for preventing deterioration (odds ratio 0.448; 95% confidence interval 0.263-0.763; P = 0.0023). Furthermore, in 222 patients who were selected from each group after matching on the propensity score, deterioration was significantly lower among those receiving casirivimab-imdevimab compared to those not receiving casirivimab-imdevimab (7.66% vs 14.0%; p = 0.021). Conclusion: This real-world study demonstrates that casirivimab-imdevimab contributes to the prevention of deterioration in COVID-19 patients after hospitalization during a Delta variant surge.

Combined Application of Nivolumab and Intravesical Bacillus Calmette-Guérin Led to Acute-Onset Type 1 Diabetes.

We report a case of acute-onset type 1 diabetes due to combined application of nivolumab and intravesical Bacillus Calmette-Guérin (BCG). An 84-year-old woman underwent lung resection for pulmonary squamous cell carcinoma. She had been treated for type 2 diabetes and later experienced lung cancer recurrence. She was started on nivolumab treatment, and complete response was achieved for one year. However, during this time, she was diagnosed with superficial bladder cancer and underwent surgery but experienced recurrence. After one month of intravesical BCG instillation, the patient developed acute-onset type 1 diabetes. Thus, we recommend that combined application of nivolumab and intravesical BCG be avoided.