Machine-learning-based COVID-19 mortality prediction model and identification of patients at low and high risk of dying.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic caused by the SARS-Cov2 virus has become the greatest health and controversial issue for worldwide nations. It is associated with different clinical manifestations and a high mortality rate. Predicting mortality and identifying outcome predictors are crucial for COVID patients who are critically ill. Multivariate and machine learning methods may be used for developing prediction models and reduce the complexity of clinical phenotypes. METHODS: Multivariate predictive analysis was applied to 108 out of 250 clinical features, comorbidities, and blood markers captured at the admission time from a hospitalized cohort of patients (N = 250) with COVID-19. Inspired modification of partial least square (SIMPLS)-based model was developed to predict hospital mortality. Prediction accuracy was randomly assigned to training and validation sets. Predictive partition analysis was performed to obtain cutting value for either continuous or categorical variables. Latent class analysis (LCA) was carried to cluster the patients with COVID-19 to identify low- and high-risk patients. Principal component analysis and LCA were used to find a subgroup of survivors that tends to die. RESULTS: SIMPLS-based model was able to predict hospital mortality in patients with COVID-19 with moderate predictive power (Q2 = 0.24) and high accuracy (AUC > 0.85) through separating non-survivors from survivors developed using training and validation sets. This model was obtained by the 18 clinical and comorbidities predictors and 3 blood biochemical markers. Coronary artery disease, diabetes, Altered Mental Status, age > 65, and dementia were the topmost differentiating mortality predictors. CRP, prothrombin, and lactate were the most differentiating biochemical markers in the mortality prediction model. Clustering analysis identified high- and low-risk patients among COVID-19 survivors. CONCLUSIONS: An accurate COVID-19 mortality prediction model among hospitalized patients based on the clinical features and comorbidities may play a beneficial role in the clinical setting to better management of patients with COVID-19. The current study revealed the application of machine-learning-based approaches to predict hospital mortality in patients with COVID-19 and identification of most important predictors from clinical, comorbidities and blood biochemical variables as well as recognizing high- and low-risk COVID-19 survivors.

Fully-automated CT derived body composition analysis reveals sarcopenia in functioning adrenocortical carcinomas.

Determination of body composition (the relative distribution of fat, muscle, and bone) has been used effectively to assess the risk of progression and overall clinical outcomes in different malignancies. Sarcopenia (loss of muscle mass) is especially associated with poor clinical outcomes in cancer. However, estimation of muscle mass through CT scan has been a cumbersome, manually intensive process requiring accurate contouring through dedicated personnel hours. Recently, fully automated technologies that can determine body composition in minutes have been developed and shown to be highly accurate in determining muscle, bone, and fat mass. We employed a fully automated technology, and analyzed images from a publicly available cancer imaging archive dataset (TCIA) and a tertiary academic center. The results show that adrenocortical carcinomas (ACC) have relatively sarcopenia compared to benign adrenal lesions. In addition, functional ACCs have accelerated sarcopenia compared to non-functional ACCs. Further longitudinal research might shed further light on the relationship between body component distribution and ACC prognosis, which will help us incorporate more nutritional strategies in cancer therapy.

Risk of 30-Day All-Cause Readmission in Interstitial Lung Disease Patients after COVID-19: National-Level Data.

Rationale: Hospital readmission within 30 days poses challenges for healthcare providers, policymakers, and patients because of its impact on care quality, costs, and outcomes. Patients with interstitial lung disease (ILD) are particularly affected by readmission, which is associated with increased morbidity and mortality and reduced quality of life. Because small sample sizes have hindered previous studies, this study seeks to address this gap in knowledge by examining a large-scale dataset. Objective: To determine the rate and probability of 30-day all-cause readmission and secondary outcomes in patients with coronavirus disease (COVID-19) or ILD admitted to the hospital. Methods: This study is a nested cohort study that used the PearlDiver patient records database. Adult patients (age ⩾18 yr) who were admitted to hospitals in 28 states in the United States with COVID-19 or ILD diagnoses were included. We defined and analyzed two separate cohorts in this study. The first cohort consisted of patients with COVID-19 and was later divided into two groups with or without a history of ILD. The second cohort consisted of patients with ILD and was later divided into groups with COVID-19 or with a non-COVID-19 pneumonia diagnosis at admission. We also studied two other subcohorts of patients with and without idiopathic pulmonary fibrosis within the second cohort. Propensity score matching was employed to match confounders between groups. The Kaplan-Meier log rank test was applied to compare the probabilities of outcomes. Results: We assessed the data of 2,286,775 patients with COVID-19 and 118,892 patients with ILD. We found that patients with COVID-19 with preexisting ILD had an odds ratio of 1.6 for 30-day all-cause readmission. Similarly, an odds ratio of 2.42 in readmission rates was observed among hospitalized individuals with ILD who contracted COVID-19 compared with those who were hospitalized for non-COVID-19 pneumonia. Our study also found a significantly higher probability of intensive care admission among patients in both cohorts. Conclusions: Patients with ILD face heightened rates of hospital readmissions, particularly when ILD is combined with COVID-19, resulting in adverse outcomes such as decreased quality of life and increased healthcare expenses. It is imperative to prioritize preventive measures against COVID-19 and establish effective postdischarge care strategies for patients with ILD.

Complete Genome Sequencing of a Novel Pseudomonas aeruginosa Phage, UF_RH5.

Here, we introduce UF_RH5, a novel lytic phage targeting clinically isolated Pseudomonas aeruginosa. It belongs to the Siphovirus morphology family, Septimatrevirus genus, with a 42,566-bp genome with a GC content of 53.60%, encoding 58 proteins. Under electron microscopy, UF_RH5 exhibits a length of 121 nm and a capsid size of 45 nm.

Role of anti-tumor necrosis factor-alpha agents in treatment of sarcoidosis: A meta-analysis.

IMPORTANCE: Anti-tumor necrosis factor-alpha agent (anti-TNF-α) is considered an effective third-line therapy for refractory sarcoidosis,studies observing the efficacy of anti-TNF-α agents show conflicting results. OBJECTIVE: We performed an up-to-date systemic meta-analysis to determine effectiveness and further elucidate the role of anti-TNF-α in the treatment of sarcoidosis. DATA SOURCES: A systematic search was carried out in PubMed/Medline, EMBASE, and Cochrane Library for studies reporting the therapeutic effects of anti-TNF drugs on patients with pulmonary and extra-pulmonary sarcoidosis, published up to April 10, 2022. The study was registered in the international prospective register of systematic reviews (PROSPERO) under ID: CRD42022364614. STUDY SELECTION: Clinical trials written reporting the therapeutic effects of anti-TNF drugs on patients with pulmonary and extra-pulmonary sarcoidosis were included. DATA EXTRACTION AND SYNTHESIS: Statistical analyses were performed with Comprehensive Meta-Analysis software, and the random-effects model was used. The combined overall treatment success was determined for patients with pulmonary and extrapulmonary sarcoidosis. MAIN OUTCOMES AND MEASURES: Overall treatment success rate wasdefined as no disease progression or improvement in symptoms. RESULTS: Eight clinical trial articles were included in the meta-analysis; four used Infliximab, two Etanercept, one Adalimumab, and one Ustekinumab and Golimumab. The mean age of participants was 48.5 years. The duration of drug therapy ranged from 14 to 45 weeks. We found a combined overall treatment success rate, defined as no disease progression or improvement in symptoms, of 69.9% (95% CI 35.0-90.9, I2: 70%) in the pulmonary sarcoidosis group and 74.5% (95% CI 36.3-93.7, I2: 90%) in the extrapulmonary sarcoidosis group. There was no evidence of publication bias in either group. CONCLUSION AND RELEVANCE: Treatment of refractory sarcoidosis with anti-TNF-α agents was effective in both pulmonary and extrapulmonary sarcoidosis, with a slightly higher efficacy seen in extrapulmonary sarcoidosis. Further randomized controlled trials should be conducted to determine the effects of anti-TNF-α agents as a part of the management strategy of sarcoidosis. Patients with pulmonary sarcoidosis should be studied separately from patients with extrapulmonary sarcoidosis to adjust for confounding results.

Inflammatory Serum Biomarker Pattern in Emphysema and Chronic Bronchitis Phenotypes of Acute Exacerbation of Chronic Obstructive Pulmonary Disease.

Background: COPD exacerbation is characterized by both airway and systemic inflammation. The present study aimed to investigate the relationship between serum levels of some inflammatory biomarkers and the phenotypes of COPD exacerbation. Materials and Methods: This study includes known COPD patients, presenting to a hospital with acute exacerbation of COPD. Serum levels of CRP, ESR, CBC, TNF-α, IL-8, and IL-6 were measured at the time of admission. According to the previously done HRCT, the patients were divided into two groups including emphysema and chronic bronchitis. Levels of serum biomarkers were compared in the two groups. The relationships between biomarkers and duration of hospitalization were assessed too. Results: Comparison of quantitative CRP levels, WBC, and platelet counts did not show a statistically significant difference between emphysema and chronic bronchitis but it was significantly higher than control subjects. Although not statistically significant, ESR level was higher in emphysema. TNF-alpha was 6.0±1.5 ng / ml and 1.5 ng / ml in the emphysema and chronic bronchitis groups, respectively. TNF-α had no significant difference compared to the groups. Although higher than the control group, IL-6 and IL-8 did not show significant differences between emphysema and chronic bronchitis. The two groups did not statistically differ in terms of hospital stay but patients with higher serum TNF-α tended to have longer hospitalization and ICU admission. Conclusion: The present study showed predictably higher inflammatory biomarkers in COPD exacerbation but no significant difference between the two phenotypes of COPD and these two entities could not be discriminated based on inflammatory bio-factors.

Cortisol values during the standard-dose cosyntropin stimulation test: Personal experience with Elecsys cortisol II assay.

Purpose: There has been debate regarding the appropriate cortisol cutoff during the cosyntropin stimulation test (CST) when newer cortisol assays are used. We aimed to evaluate the proper cortisol values during the standard dose CST in patients with normal hypothalamic-pituitary-adrenal (HPA) axis when the Elecsys® Cortisol II assay from Roche Diagnostics is used. Methods: We retrospectively reviewed the medical records of patients evaluated for possible adrenal insufficiency using the standard-dose (250 mcg) CST from January 2018 to December 2020 and eventually judged to have a normal HPA axis. All the CSTs were done in the outpatient setting. Evaluation by an endocrinologist, restrictive exclusion criteria including prior glucocorticoid and opioid use, and lack of glucocorticoid treatment for at least 6 months after the CST was used to define normal HPA axis. The results are reported in the median (range). Results: We identified 63 patients who met the inclusion criteria and were considered to have a normal HPA axis. The median age was 54.7 (27.6-89.1) years; 32 (51%) were female, and 27 (43%) were white. The duration of follow-up after the CST without any glucocorticoid replacement was 13.9 (6.3-43.9) months. Cortisol levels were 21.7 (15.7-29.1) µg/dl and 24.4 (17.9-35.8) µg/dl at 30- and 60-minutes after cosyntropin administration, respectively. The lowest cortisol levels at 30 and 60 minutes for patients with either normal TSH or gonadal axis (n=47) or in whom both axes were normal (n=18) were similar to the ones of the entire cohort. Conclusion: Our study supports using a lower than previously recommended cortisol cutoff value at 30 minutes after Cosyntropin using the Roche Elecsys® Cortisol II assay. The lowest cortisol levels in our cohort were 15.7 and 17.9 µg/dL at 30 and 60 minutes after the CST, respectively. Therefore, it is essential to consider the time of cortisol draw after cosyntropin administration.

Incidence, Time Trends and Geographical Distribution of Leukemia and Multiple Myeloma in Golestan Province, Northern Iran, 2004-2017.

BACKGROUND: Leukemia and multiple myeloma (MM) are the most common hematologic malignancies in Iran. This paper describes the geographic and temporal changes in their incidence in Golestan, northern Iran. METHODS: Data on cases of leukemia and MM during 2004-2017 were obtained from the Golestan Population-based Cancer Registry (GPCR). The GPCR is a dynamic database of Golestan residents diagnosed with primary cancers. Age-standardized incidence rates (ASRs) (per 100000) of leukemia and MM were calculated using direct standardization method considering the world standard population. We used Joinpoint regression to assess incidence trends using the average annual percent change (AAPC). RESULTS: In total, 2119 new cases of leukemia and MM were registered by the GPCR during 2004-2017. The ASRs of leukemia were 9.71 and 6.70 in males and females, respectively, while the rates were lower for MM: 2.66 and 1.97 in males and females, respectively. The incidence rates of leukemia suggested an increasing trend in urban population (AAPC=2.73; P value=0.154), while in rural area, the incidence rates were slightly decreasing (AAPC=- 0.73; P value=0.658). There were high incidence areas of leukemia in the central and western regions of Golestan. CONCLUSION: Our results suggested high incidence rates of leukemia and MM in the Golestan province. We also found geographical diversities and increasing trends in the incidence of leukemia in the urban population. Exposure to occupational and environmental carcinogens including pesticides may partly explain high rates and the observed trends. Further investigations should be considered to clarify these points in our population.

Antifibrotic and Anti-Inflammatory Actions of α-Melanocytic Hormone: New Roles for an Old Player.

The melanocortin system encompasses melanocortin peptides, five receptors, and two endogenous antagonists. Besides pigmentary effects generated by α-Melanocytic Hormone (α-MSH), new physiologic roles in sexual activity, exocrine secretion, energy homeostasis, as well as immunomodulatory actions, exerted by melanocortins, have been described recently. Among the most common and burdensome consequences of chronic inflammation is the development of fibrosis. Depending on the regenerative capacity of the affected tissue and the quality of the inflammatory response, the outcome is not always perfect, with the development of some fibrosis. Despite the heterogeneous etiology and clinical presentations, fibrosis in many pathological states follows the same path of activation or migration of fibroblasts, and the differentiation of fibroblasts to myofibroblasts, which produce collagen and α-SMA in fibrosing tissue. The melanocortin agonists might have favorable effects on the trajectories leading from tissue injury to inflammation, from inflammation to fibrosis, and from fibrosis to organ dysfunction. In this review we briefly summarized the data on structure, receptor signaling, and anti-inflammatory and anti-fibrotic properties of α-MSH and proposed that α-MSH analogues might be promising future therapeutic candidates for inflammatory and fibrotic diseases, regarding their favorable safety profile.

Cement pulmonary embolism after percutaneous vertebroplasty in a patient with cushing's syndrome: A case report.

BACKGROUND: Vertebroplasty is a procedure most commonly used for vertebral compression fractures. Although it is a relatively safe procedure, complications have been reported. Cement embolism is seen in 2.1%-26% of patients after percutaneous vertebroplasty. CASE PRESENTATION: a 38-year-old male who was diagnosed with cushing's syndrome, underwent percutaneous vertebroplasty for his thoracic osteoporotic compression fractures. 24-hours following vertebroplasty, he presented to emergency department with acute-onset dyspnea and chest pain. Chest radiography showed an opaque linear lesion in left pulmonary artery which was suggestive of cement embolism. Pulmonary spiral CT-scan further confirmed the diagnosis. The patient's symptoms improved over time, and warfarin was started with close cardiopulmonary assessments for indicators of cement embolus removal. CONCLUSION: in patients with pulmonary cement embolism, conservative treatment may be recommended rather than a surgical removal except when the obstruction is extensive enough to cause hemodynamic changes. Given that all the related studies have suggested that pulmonary thromboembolism can occur as a complication due to bone cement leakage, discovering new cement alternatives and/or injection devices, seems beneficial.