Staging of Acute Exacerbation in Patients with Idiopathic Pulmonary Fibrosis

Mitochondrial DNA in bronchoalveolar lavage fluid is associated with the prognosis of idiopathic pulmonary fibrosis: a single cohort study

BACKGROUND

Extracellular mitochondrial DNA (mtDNA) is released from damaged cells and increases in the serum and bronchoalveolar lavage fluid (BALF) of idiopathic pulmonary fibrosis (IPF) patients. While increased levels of serum mtDNA have been reported to be linked to disease progression and the future development of acute exacerbation (AE) of IPF (AE-IPF), the clinical significance of mtDNA in BALF (BALF-mtDNA) remains unclear. We investigated the relationships between BALF-mtDNA levels and other clinical variables and prognosis in IPF.

METHODS

Extracellular mtDNA levels in BALF samples collected from IPF patients were determined using droplet-digital PCR. Levels of extracellular nucleolar DNA in BALF (BALF-nucDNA) were also determined as a marker for simple cell collapse. Patient characteristics and survival information were retrospectively reviewed.

RESULTS

mtDNA levels in serum and BALF did not correlate with each other. In 27 patients with paired BALF samples obtained in a stable state and at the time of AE diagnosis, BALF-mtDNA levels were significantly increased at the time of AE. Elevated BALF-mtDNA levels were associated with inflammation or disordered pulmonary function in a stable state (n = 90), while being associated with age and BALF-neutrophils at the time of AE (n = 38). BALF-mtDNA ≥ 4234.3 copies/µL in a stable state (median survival time (MST): 42.4 vs. 79.6 months, p < 0.001) and ≥ 11,194.3 copies/µL at the time of AE (MST: 2.6 vs. 20.0 months, p = 0.03) were associated with shorter survival after BALF collection, even after adjusting for other known prognostic factors. On the other hand, BALF-nucDNA showed different trends in correlation with other clinical variables and did not show any significant association with survival time.

CONCLUSIONS

Elevated BALF-mtDNA was associated with a poor prognosis in both IPF and AE-IPF. Of note, at the time of AE, it sharply distinguished survivors from non-survivors. Given the trends shown by analyses for BALF-nucDNA, the elevation of BALF-mtDNA might not simply reflect the impact of cell collapse. Further studies are required to explore the underlying mechanisms and clinical applications of BALF-mtDNA in IPF.

Novel 3D-based deep learning for classification of acute exacerbation of idiopathic pulmonary fibrosis using high-resolution CT

PURPOSE

Acute exacerbation of idiopathic pulmonary fibrosis (AE-IPF) is the primary cause of death in patients with IPF, characterised by diffuse, bilateral ground-glass opacification on high-resolution CT (HRCT). This study proposes a three-dimensional (3D)-based deep learning algorithm for classifying AE-IPF using HRCT images.

MATERIALS AND METHODS

A novel 3D-based deep learning algorithm, SlowFast, was developed by applying a database of 306 HRCT scans obtained from two centres. The scans were divided into four separate subsets (training set, n=105; internal validation set, n=26; temporal test set 1, n=79; and geographical test set 2, n=96). The final training data set consisted of 1050 samples with 33 600 images for algorithm training. Algorithm performance was evaluated using accuracy, sensitivity, specificity, positive predictive value, negative predictive value, receiver operating characteristic (ROC) curve and weighted κ coefficient.

RESULTS

The accuracy of the algorithm in classifying AE-IPF on the test sets 1 and 2 was 93.9% and 86.5%, respectively. Interobserver agreements between the algorithm and the majority opinion of the radiologists were good (κw=0.90 for test set 1 and κw=0.73 for test set 2, respectively). The ROC accuracy of the algorithm for classifying AE-IPF on the test sets 1 and 2 was 0.96 and 0.92, respectively. The algorithm performance was superior to visual analysis in accurately diagnosing radiological findings. Furthermore, the algorithm's categorisation was a significant predictor of IPF progression.

CONCLUSIONS

The deep learning algorithm provides high auxiliary diagnostic efficiency in patients with AE-IPF and may serve as a useful clinical aid for diagnosis.

Machine and deep learning methods for clinical outcome prediction based on physiological data of COVID-19 patients: a scoping review

INTRODUCTION

Since the beginning of the COVID-19 pandemic, numerous machine and deep learning (MDL) methods have been proposed in the literature to analyze patient physiological data. The objective of this review is to summarize various aspects of these methods and assess their practical utility for predicting various clinical outcomes.

METHODS

We searched PubMed, Scopus, and Cochrane Library, screened and selected the studies matching the inclusion criteria. The clinical analysis focused on the characteristics of the patient cohorts in the studies included in this review, the specific tasks in the context of the COVID-19 pandemic that machine and deep learning methods were used for, and their practical limitations. The technical analysis focused on the details of specific MDL methods and their performance.

RESULTS

Analysis of the 48 selected studies revealed that the majority (∼54 %) of them examined the application of MDL methods for the prediction of survival/mortality-related patient outcomes, while a smaller fraction (∼13 %) of studies also examined applications to the prediction of patients' physiological outcomes and hospital resource utilization. 21 % of the studies examined the application of MDL methods to multiple clinical tasks. Machine and deep learning methods have been shown to be effective at predicting several outcomes of COVID-19 patients, such as disease severity, complications, intensive care unit (ICU) transfer, and mortality. MDL methods also achieved high accuracy in predicting the required number of ICU beds and ventilators.

CONCLUSION

Machine and deep learning methods have been shown to be valuable tools for predicting disease severity, organ dysfunction and failure, patient outcomes, and hospital resource utilization during the COVID-19 pandemic. The discovered knowledge and our conclusions and recommendations can also be useful to healthcare professionals and artificial intelligence researchers in managing future pandemics.

Association of the lung immune prognostic index with the survival of patients with idiopathic interstitial pneumonias

BACKGROUND AND OBJECTIVE

The lung immune prognostic index (LIPI), a simple index calculated from the blood lactate dehydrogenase level and derived neutrophil-to-lymphocyte ratio, is thought to be associated with host immune status. However, the utility of LIPI in patients with idiopathic interstitial pneumonias (IIPs) is unknown.

METHODS

In this multicentre, retrospective, observational study, an association between LIPI and the survival of patients with IIPs was evaluated.

RESULTS

Exploratory and validation cohorts consisting of 460 and 414 patients with IIPs, respectively, were included (159 and 159 patients had idiopathic pulmonary fibrosis [IPF], and 301 and 255 had non-IPF, respectively). In the exploratory cohort, patients with IPF and a low LIPI had significantly better survival than those with a high LIPI (median of 5.6 years vs. 3.9 years, p = 0.016). The predictive ability of LIPI for the survival of patients with IPF was validated in the validation cohort (median of 8.5 years vs. 4.4 years, p = 0.003). In a multivariate Cox proportional hazard analysis, LIPI was selected as an independent predictive factor for the survival of IPF patients. There was no significant association between LIPI and survival of non-IPF patients in the exploratory and validation cohorts.

CONCLUSION

The LIPI was a predictive factor for the survival of patients with IPF and could aid the management of IPF.

The Impact of Chronic Comorbidities on Outcomes in Acute Exacerbations of Idiopathic Pulmonary Fibrosis

INTRODUCTION

Idiopathic pulmonary fibrosis is a chronic progressive lung disease of unknown cause with a high associated mortality. We aimed to compare the impact of chronic medical conditions on hospital outcomes of patients with acute exacerbations of idiopathic pulmonary fibrosis (AE-IPF).

METHODS

This was a retrospective cohort study using the NIS database from 2016 to 2018. We included patients aged 60 and older hospitalized in academic medical centers with the diagnoses of IPF and acute respiratory failure. We examined factors associated with hospital mortality and length of stay (LOS) using survey-weighted multivariate logistic and negative binomial regression.

RESULTS

Out of 4975 patients with AE-IPF, 665 (13.4%) did not survive hospitalization. There was no difference in the mean age between survivors and non-survivors. Patients were more likely to be male, predominantly white, and have Medicare coverage. Most non-survivors were from households with higher median income. Hospital LOS was longer among non-survivors than survivors (9.4 days vs. 9.8 days; p < 0.001). After multivariate-logistic regression, diabetes was found to be protective (aOR 0.62, 95% CI 0.50-0.77; p < 0.0001) while chronic kidney disease (CKD) conferred a significantly higher risk of death after AE-IPF (aOR 6.85, 95% CI 1.90-24.7; p = 0.00). Our multivariate adjusted negative binomial regression model for LOS identified obesity (IRR 0.85, 95% CI 0.76-0.94; p ≤ 0.00) and hypothyroidism (IRR 0.90, 95% CI 0.83-0.98; p = 0.02) to be associated with shorter hospital LOS.

CONCLUSIONS

Our results suggest that CKD is a significant contributor to hospital mortality in AE-IPF, and diabetes mellitus may be protective. Obesity and hypothyroidism are linked with shorter hospital LOS among patients hospitalized with AE-IPF in US academic medical centers.

ILD-GAP combined with the monocyte ratio could be a better prognostic prediction model than ILD-GAP in patients with interstitial lung diseases

BACKGROUND

The ILD-GAP scoring system is known to be useful in predicting prognosis in patients with interstitial lung disease (ILD). An elevated monocyte count was associated with increased risks of IPF poor prognosis. We examined whether the ILD-GAP scoring system combined with the monocyte ratio (ILD-GAPM) is superior to the conventional ILD-GAP model in predicting ILD prognosis.

METHODS

In patients with ILD treated between April 2013 and April 2017, we were retrospectively assessed the relationships between baseline clinical parameters, including age, sex, Charlson Comorbidity Index score (CCIS), ILD diagnosis, blood biomarkers, pulmonary function test results, and disease outcomes. In ILD patients were included idiopathic pulmonary fibrosis (IPF), idiopathic nonspecific interstitial pneumonia (iNSIP), collagen vascular disease-related interstitial pneumonia (CVD-IP), chronic hypersensitivity pneumonitis (CHP), and unclassifiable ILD (UC-ILD). We also assessed the ability to predict prognosis was compared between the ILD-GAP and ILD-GAPM models.

RESULTS

A total of 179 patients (mean age, 73 years) were assessed. All of them were taken pulmonary function test, including percentage predicted diffusion capacity for carbon monoxide. ILD patients included 56 IPF cases, 112 iNSIP and CVD-IP cases, 6 CHP cases and 5 UC-ILD cases. ILD-GAPM provided a greater area under the receiver-operating characteristic curve (0.747) than ILD-GAP (0.710) for predicting 3-year ILD-related events. Furthermore, the log-rank test showed that the Kaplan-Meier curves in ILD-GAPM were significantly different by stage (P = 0.015), but not by stage in ILD-GAP (P = 0.074).

CONCLUSIONS

The ILD-GAPM model may be a more accurate predictor of prognosis for ILD patients than the ILD-GAP model.

Myeloid Heterogeneity Mediates Acute Exacerbations of Pulmonary Fibrosis

Epidemiological evidence indicates that exposure to particulate matter is linked to the development of idiopathic pulmonary fibrosis (IPF) and increases the incidence of acute exacerbations of IPF. In addition to accelerating the rate of lung function decline, exposure to fine particulate matter (particulate matter smaller than 2.5 μm [PM2.5]) is a risk factor for increased mortality in subjects with IPF. In this article, we show that exposure to PM2.5 mediates monocyte recruitment and fibrotic progression in mice with established fibrosis. In mice with established fibrosis, bronchoalveolar lavage cells showed monocyte/macrophage heterogeneity after exposure to PM2.5. These cells had a significant inflammatory and anti-inflammatory signature. The mixed heterogeneity of cells contributed to the proinflammatory and anti-inflammatory response. Although monocyte-derived macrophages were recruited to the lung in bleomycin-injured mice treated with PM2.5, recruitment of monocytes expressing Ly6Chi to the lung promoted progression of fibrosis, reduced lung aeration on computed tomography, and impacted lung compliance. Ly6Chi monocytes isolated from PM2.5-exposed fibrotic mice showed enhanced expression of proinflammatory markers compared with fibrotic mice exposed to vehicle. Moreover, IPF bronchoalveolar lavage cells treated ex vivo with PM2.5 showed an exaggerated inflammatory response. Targeting Ly6Chi monocyte recruitment inhibited fibrotic progression in mice. Moreover, the adoptive transfer of Ly6Chi monocytes exacerbated established fibrosis. These observations suggest that enhanced recruitment of Ly6Chi monocytes with a proinflammatory phenotype mediates acute exacerbations of pulmonary fibrosis, and targeting these cells may provide a potential novel therapeutic target to protect against acute exacerbations of IPF.

Efficacy and safety of Kangxian Huanji Granule as adjunctive treatment in acute exacerbation of idiopathic pulmonary fibrosis: An exploratory randomized controlled trial

BACKGROUND

Acute exacerbation of idiopathic pulmonary fibrosis (AE-IPF) is an important occurrence in the natural history of idiopathic pulmonary fibrosis (IPF), associated with high hospitalization rates, high mortality and poor prognosis. At present, there is no effective treatment for AE-IPF. Chinese herbal medicine has some advantages in treating IPF, but its utility in AE-IPF is unclear.

OBJECTIVE

The treatment of AE-IPF with Kangxian Huanji Granule (KXHJ), a compound Chinese herbal medicine, lacks an evidence-based justification. This study explores the efficacy and safety of KXHJ in patients with AE-IPF.

DESIGN, SETTING, PARTICIPANTS AND INTERVENTIONS

We designed a randomized, double-blind, placebo-controlled, exploratory clinical trial. A total of 80 participants diagnosed with AE-IPF were randomly assigned to receive KXHJ or a matching placebo; the treatment included a 10 g dose, administered twice daily for 4 weeks, in addition to conventional treatment. Participants were followed up for 12 weeks after the treatment.

MAIN OUTCOME MEASURES

The primary endpoints were treatment failure rate and all-cause mortality. Secondary endpoints included the length of hospitalization, overall survival, acute exacerbation rate, intubation rate, the modified British Medical Research Council (mMRC) score, and the St George's Respiratory Questionnaire for IPF (SGRQ-I) score.

RESULTS

The rate of treatment failure at 4 weeks was lower in the intervention group compared to the control group (risk ratio [RR]: 0.22; 95% confidence interval [CI]: 0.051 to 0.965, P = 0.023). There was no significant difference in all-cause mortality at 16 weeks (RR: 0.75; 95% CI: 0.179 to 3.138; P > 0.999) or in the acute exacerbation rate during the 12-week follow-up period (RR: 0.69; 95% CI: 0.334 to 1.434; P = 0.317). The intervention group had a shorter length of hospitalization than the control group (mean difference [MD]: -3.30 days; 95% CI, -6.300 to -0.300; P = 0.032). Significant differences in the mean change from baseline in the mMRC (between-group difference: -0.67; 95% CI: -0.89 to -0.44; P < 0.001) and SGRQ-I score (between-group difference: -10.36; 95% CI: -16.483 to -4.228; P = 0.001) were observed after 4 weeks, and also in the mMRC (between-group difference: -0.67; 95% CI: -0.91 to -0.43; P < 0.001) and SGRQ-I (between-group difference: -10.28; 95% CI, -15.838 to -4.718; P < 0.001) at 16 weeks. The difference in the adverse events was not significant.

CONCLUSION

KXHJ appears to be effective and safe for AE-IPF and can be considered a complementary treatment in patients with AE-IPF. As a preliminary exploratory study, our results provide a basis for further clinical research.

TRIAL REGISTRATION

Chinese Clinical Trial Registry (ChiCTR1900026289). Please cite this article as: Li JS, Zhang HL, Guo W, Wang L, Zhang D, Zhao LM, Zhou M. Efficacy and safety of Kangxian Huanji Granule as adjunctive treatment in acute exacerbation of idiopathic pulmonary fibrosis: an exploratory randomized controlled trial. J Integr Med. 2023; 21(6): 543-549.

A Systematic Review and Meta-analysis of Clinical, Respiratory, and Biochemical Risk Factors for Acute Exacerbation of idiopathic Pulmonary Fibrosis

BACKGROUND

A better capacity to identify patients with idiopathic pulmonary fibrosis (IPF) at risk of acute exacerbation (AEIPF) might improve outcomes and reduce healthcare costs.

AIMS

We critically appraised the available evidence of the differences in clinical, respiratory, and biochemical parameters between AEIPF and IPF patients with stable disease (SIPF) by conducting a systematic review and meta-analysis.

METHODS

PubMed, Web of Science and Scopus were reviewed up until August 1, 2022, for studies reporting differences in clinical, respiratory, and biochemical parameters (including investigational biomarkers) between AEIPF and SIPF patients. The Joanna Briggs Institute Critical Appraisal Checklist was used to assess the risk of bias.

RESULTS

Twenty-nine cross-sectional studies published between 2010 and 2022 were identified (all with a low risk of bias). Of the 32 meta-analysed parameters, significant differences were observed between groups, assessed through standard mean differences or relative ratios, with age, forced vital capacity, vital capacity, carbon monoxide diffusion capacity, total lung capacity, oxygen partial pressure, alveolar-arterial oxygen gradient, P/F ratio, 6 min walk test distance, C-reactive protein, lactate dehydrogenase, white blood cell count, albumin, Krebs von den Lungen 6, surfactant protein D, high mobility group box 1 protein, and interleukin-1β, 6, and 8.

CONCLUSIONS

We identified significant differences between AEIPF and SIPF patients in age and specific parameters of respiratory function, inflammation, and epithelial lung damage. Prospective studies are warranted to determine the capacity of these parameters to predict AEIPF more accurately (PROSPERO registration number: CRD42022356640).

[Real-life survival of idiopathic pulmonary fibrosis with anti-fibrotic medication]

INTRODUCTION

Idiopathic pulmonary fibrosis (IPF) is an irreversible fibrosing disease with median survival at diagnosis of 2-5 years. That said, pirfenidone and nintedanib slow down the gradual decline in respiratory function. Clinical trials have shown that while they are not curative, these drugs reduce mortality and increase survival time compared to placebo. This objective of this work was to compare the real-life survival of patients with IPF diagnosed at the Tours University Hospital depending on whether or not they took anti-fibrotic medication.

METHODS

This is a monocentric retrospective study involving 176 patients diagnosed with IPF starting from 1997. Out of these 176 patients, 100 were treated with anti-fibrotic agents and 76 did not receive any anti-fibrotic treatment.

RESULTS

Survival significantly increased in the group with anti-fibrotic medication, with median survival of 59 months [46-87] versus 39 months [29-65] (P=0.022). Predictive factors for death were neoplasia, IPF exacerbation and decreased DLCO.

CONCLUSION

Our study corroborates the beneficial result observed in clinical trials by showing longer survival in patients using anti-fibrotic agents.

Skeletal muscle atrophy and short-term mortality in patients with acute exacerbation of idiopathic pulmonary fibrosis: an observational cohort study

BACKGROUND

Skeletal muscle atrophy, a common complication of idiopathic pulmonary fibrosis (IPF), and its presence upon diagnosis can indicate a poor prognosis. Patients with IPF frequently experience acute exacerbations (AE), which is associated with a high mortality rate. However, the association between skeletal muscle atrophy and short-term mortality remains unknown.

METHODS

We performed a retrospective, multicenter cohort study of patients admitted for AE-IPF in Japan. The cross-sectional areas of the erector spinae muscle (ESM_CSA) and the pectoralis muscle (PM_CSA) were analyzed via single-slice computed tomography (CT). The primary outcome was 90-day mortality. Survival probability was estimated using the Kaplan-Meier method, and the log-rank test was used between the low and high groups of ESM_CSA and PM_CSA. We used multivariable Cox proportional-hazards models to evaluate the association between ESM_CSA and PM_CSA and prognosis.

RESULTS

Of the 212 patients included, 94 (44%) died during the observation period. The low ESM_CSA group (<25.6 cm²) had a significantly worse prognosis than that of the high ESM_CSA group (≥25.6 cm²) (hazard ratio (HR) [95% confidence interval (CI)]: 1.52 [1.00-2.33], P = 0.049). Multivariable analyses showed that all-cause mortality was associated with low ESM_CSA (model 1, adjusted HR [95% CI]: 1.59 [0.98-2.60]; model 2, 1.55 [0.95-2.56], and model 3, 1.67 [1.00-2.78], respectively). The adjusted HR of low PM_CSA (<20.4 cm²) vs. high PM_CSA (≥20.4 cm²) was 1.39 (95% CI: 0.88-2.20).

CONCLUSIONS

Low ESM_CSA on CT images is associated with a high 90-day mortality rate in patients with AE-IPF.

Combination of computed tomography imaging pattern and severity of respiratory failure as factors associated with prognosis for acute exacerbation of idiopathic chronic fibrosing interstitial pneumonia

BACKGROUND AND OBJECTIVES

The prognosis of idiopathic chronic fibrotic interstitial pneumonitis (CFIP) in patients with acute exacerbation (AE) is variable. We examined whether the imaging pattern on thoracic computed tomography (CT) or the severity of respiratory failure with AE-CFIP is associated with short-term prognosis.

METHODS

Patients admitted to two university hospitals were retrospectively analyzed and divided into derivation and validation cohorts. The distribution of newly appearing parenchymal abnormalities on thoracic CT was classified into peripheral, multifocal, and diffuse patterns. Respiratory failure was defined as severe if a fraction of inspired oxygen ≥ 0.5 was required to maintain percutaneous oxygen saturation ≥ 90% on admission. Factors associated with 90 day-mortality were analyzed using univariate and Cox proportional hazard regression.

RESULTS

In 59 patients with AE-CFIP of the derivation cohort, diffuse pattern on CT was associated with higher mortality within 90 days (43%) than peripheral/multifocal pattern (17%, p = 0.03). Additionally, compared with non-severe failure, severe respiratory failure was associated with higher mortality (47% vs. 21%, p = 0.06). Cox proportional hazard regression analysis demonstrated that a combination of diffuse pattern on CT and severe respiratory failure was associated with the poorest prognosis (hazard ratio [HR] 3.51 [interquartile range 1.26-9.80], p = 0.016) in the derivation cohort, which was confirmed in the validation cohort (n = 31, HR 4.30 [interquartile range 1.51-12.2], p = 0.006).

CONCLUSION

The combination of imaging pattern on thoracic CT and severity of respiratory failure was associated with the prognosis of idiopathic AE-CFIP.

ILD-GAP Combined with the Charlson Comorbidity Index Score (ILD-GAPC) as a Prognostic Prediction Model in Patients with Interstitial Lung Disease

Background

The ILD-GAP scoring system has been widely used to predict the prognosis of patients with interstitial lung disease (ILD). The ability of the ILD-GAP scoring system combined with the Charlson Comorbidity Index score (CCIS) (ILD-GAPC) to predict ILD prognosis was investigated.

Methods

In ILD patients, including idiopathic pulmonary fibrosis (IPF), idiopathic nonspecific interstitial pneumonia (iNSIP), collagen vascular disease-related interstitial pneumonia (CVD-IP), chronic hypersensitivity pneumonitis (CHP), and unclassifiable ILD (UC-ILD), treated between April 2013 and April 2017, the relationships between baseline clinical parameters, including age, sex, CCIS, ILD diagnosis, pulmonary function test results, and disease outcomes, were retrospectively assessed, and the ability to predict prognosis was compared between the ILD-GAP and ILD-GAPC models, respectively.

Results

A total of 185 patients (mean age, 71.9 years), all of whom underwent pulmonary function testing, including percentage predicted diffusion capacity for carbon monoxide, were assessed. ILD diagnosis consisted of IPF in 57 cases, iNSIP and CVD-IP in 117 cases, CHP in 6 cases, and UC-ILD in 5 cases. The ILD-GAPC provided a greater area under the receiver operating characteristic curve (0.758) for predicting 3-year ILD-related events than the ILD-GAP (0.721). In addition, log-rank tests showed that the Kaplan-Meier curves differed significantly among low, middle, and high ILD-GAPC scores (P < 0.001), unlike ILD-GAP scores (P = 0.083).

Conclusions

The ILD-GAPC model could provide more accurate information for predicting prognosis in patients with ILD than the ILD-GAP model.

Serum lactate dehydrogenase is associated with impaired lung function: NHANES 2011-2012

BACKGROUND

Serum lactate dehydrogenase levels reflect disease status in a variety of organs, but its role in indicating pulmonary function is not yet clear. Therefore, this study explored the correlation between pulmonary function and serum lactate dehydrogenase, and investigated thresholds for changes in pulmonary function indicators in the total population as well as in different strata of the population.

METHODS

Based on data from the National Health and Nutrition Examination Survey (NHANES) 2011-2012 (n = 3453), univariate and stratified analyses were performed to investigate factors associated with pulmonary function, and multiple regression analysis was used to further investigate the specific relationship with serum lactate dehydrogenase. Smoothed curve fitting, threshold effect and saturation effect analysis were used to explore the threshold level of serum lactate dehydrogenase at the onset of changes in pulmonary function indicators.

RESULTS

Adjusted smoothed curve fit plots showed a linear relationship between serum lactate dehydrogenase levels and forced vital capacity and forced expiratory volume in one second: for each 1 U/L increase in serum lactate dehydrogenase levels, forced vital capacity decreased by 1.24 mL (95% CI = -2.05, -0.42, P = 0.0030) and forced expiratory volume in one second by 1.11 mL (95% CI = -1.82, -0.39, P = 0.0025).

CONCLUSIONS

Serum lactate dehydrogenase was negatively and linearly correlated with pulmonary function indices in the total population analyzed. Based on the total population and different population stratifications, this study determined the threshold values of serum lactate dehydrogenase at the onset of decline of pulmonary function in different populations. This provides a new serological monitoring indicator for patients suffering from respiratory diseases and has implications for patients with possible clinical impairment of pulmonary function. However, our cross-sectional study was not able to determine a causal relationship between these two factors, and further research is needed.

Ct, IL-18 polymorphism, and laboratory biomarkers for predicting chemosensory dysfunctions and mortality in COVID-19

Aim

Patients with COVID-19 often experience chemosensory dysfunction. This research intends to uncover the association of RT-PCR Ct value with chemosensory dysfunctions and SpO2. This study also aims to investigate Ct, SpO2, CRP, D-dimer, and -607 IL-18 T/G polymorphism in order to find out predictors of chemosensory dysfunctions and mortality.

Materials & methods

This study included 120 COVID-19 patients, of which 54 were mild, 40 were severe and 26 were critical. CRP, D-dimer, RT-PCR, and IL-18 polymorphism were evaluated. Results & conclusion: Low Ct was associated with SpO2 dropping and chemosensory dysfunctions. IL-18 T/G polymorphism did not show an association with COVID-19 mortality; conversely, age, BMI, D-dimer and Ct values did.

Mutations in SARS-CoV-2: Insights on structure, variants, vaccines, and biomedical interventions

COVID-19 is a worldwide pandemic caused by SARS-coronavirus-2 (SARS-CoV-2). Less than a year after the emergence of the Covid-19 pandemic, many vaccines have arrived on the market with innovative technologies in the field of vaccinology. Based on the use of messenger RNA (mRNA) encoding the Spike SARS-Cov-2 protein or on the use of recombinant adenovirus vectors enabling the gene encoding the Spike protein to be introduced into our cells, these strategies make it possible to envisage the vaccination in a new light with tools that are more scalable than the vaccine strategies used so far. Faced with the appearance of new variants, which will gradually take precedence over the strain at the origin of the pandemic, these new strategies will allow a much faster update of vaccines to fight against these new variants, some of which may escape neutralization by vaccine antibodies. However, only a vaccination policy based on rapid and massive vaccination of the population but requiring a supply of sufficient doses could make it possible to combat the emergence of these variants. Indeed, the greater the number of infected individuals, the faster the virus multiplies, with an increased risk of the emergence of variants in these RNA viruses. This review will discuss SARS-CoV-2 pathophysiology and evolution approaches in altered transmission platforms and emphasize the different mutations and how they influence the virus characteristics. Also, this article summarizes the common vaccines and the implication of the mutations and genetic variety of SARS-CoV-2 on the COVID-19 biomedical arbitrations.

Nintedanib plus chemotherapy for nonsmall cell lung cancer with idiopathic pulmonary fibrosis: a randomised phase 3 trial

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) is a fatal lung disease implicated as an independent risk factor for lung cancer. However, optimal treatment for advanced lung cancer with IPF remains to be established. We performed a randomised phase 3 trial (J-SONIC) to assess the efficacy and safety of nintedanib plus chemotherapy (experimental arm) compared with chemotherapy alone (standard-of-care arm) for advanced nonsmall cell lung cancer (NSCLC) with IPF.

METHODS

Chemotherapy-naïve advanced NSCLC patients with IPF were allocated to receive carboplatin (area under the curve of 6 on day 1) plus nanoparticle albumin-bound paclitaxel (nab-paclitaxel) (100 mg·m-2 on days 1, 8 and 15) every 3 weeks with or without nintedanib (150 mg twice daily, daily). The primary end-point was exacerbation-free survival (EFS).

RESULTS

Between May 2017 and February 2020, 243 patients were enrolled. Median EFS was 14.6 months in the nintedanib plus chemotherapy group and 11.8 months in the chemotherapy group (hazard ratio (HR) 0.89, 90% CI 0.67-1.17; p=0.24), whereas median progression-free survival was 6.2 and 5.5 months, respectively (HR 0.68, 95% CI 0.50-0.92). Overall survival was improved by nintedanib in patients with nonsquamous histology (HR 0.61, 95% CI 0.40-0.93) and in those at GAP (gender-age-physiology) stage I (HR 0.61, 95% CI 0.38-0.98). Seven (2.9%) out of 240 patients experienced acute exacerbation during study treatment.

CONCLUSIONS

The primary end-point of the study was not met. However, carboplatin plus nab-paclitaxel was found to be effective and tolerable in advanced NSCLC patients with IPF. Moreover, nintedanib in combination with such chemotherapy improved overall survival in patients with nonsquamous histology.

An early novel prognostic model for predicting 80-day survival of patients with COVID-19

The outbreak of the novel coronavirus disease 2019 (COVID-19) has had an unprecedented impact worldwide, and it is of great significance to predict the prognosis of patients for guiding clinical management. This study aimed to construct a nomogram to predict the prognosis of COVID-19 patients. Clinical records and laboratory results were retrospectively reviewed for 331 patients with laboratory-confirmed COVID-19 from Huangshi Hospital of Traditional Chinese Medicine (TCM) (Infectious Disease Hospital) and Third Affiliated Hospital of Sun Yat-sen University. All COVID-19 patients were followed up for 80 days, and the primary outcome was defined as patient death. Cases were randomly divided into training (n=199) and validation (n=132) groups. Based on baseline data, we used statistically significant prognostic factors to construct a nomogram and assessed its performance. The patients were divided into Death (n=23) and Survival (n=308) groups. Analysis of clinical characteristics showed that these patients presented with fever (n=271, 81.9%), diarrhea (n=20, 6.0%) and had comorbidities (n=89, 26.9.0%). Multivariate Cox regression analysis showed that age, UREA and LDH were independent risk factors for predicting 80-day survival of COVID-19 patients. We constructed a qualitative nomogram with high C-indexes (0.933 and 0.894 in the training and validation groups, respectively). The calibration curve for 80-day survival showed optimal agreement between the predicted and actual outcomes. Decision curve analysis revealed the high clinical net benefit of the nomogram. Overall, our nomogram could effectively predict the 80-day survival of COVID-19 patients and hence assist in providing optimal treatment and decreasing mortality rates.

Heme oxygenase-1 as an important predictor of the severity of COVID-19

Background and objective

A cytokine storm is caused by inflammatory cells, including pro-inflammatory macrophage phenotype (M1), and play a critical role in the pathogenesis of COVID-19, in which diffuse alveolar damage occurs in the lungs due to oxidative stress exposure. Heme oxygenase (HO)-1 is a stress-induced protein produced by the anti-inflammatory / anti-oxidative macrophage phenotype (M2), which also produces soluble CD163 (sCD163). In our study, we investigated and determined that serum HO-1 can be a predictive biomarker for assessing both the severity and the outcome of COVID-19 patients.

Method

The serum concentrations of HO-1 and sCD163 of COVID-19 patients were measured on admission. The relationship between these biomarkers and other clinical parameters and outcomes were evaluated.

Results

Sixty-four COVID-19 patients (11 mild, 38 moderate, and 15 severe cases) were assessed. The serum HO-1 tended to increase (11.0 ng/mL vs. 24.3 ng/mL vs. 59.6 ng/mL with severity). Serum HO-1 correlated with serum lactate dehydrogenase (R = 0.422), C-reactive protein (R = 0.463), and the ground glass opacity (GGO) and consolidation score (R = 0.625) of chest computed tomography. The serum HO-1 showed a better area under the curve (AUC) for predicting ICU admission than the serum sCD163 (HO-1; 0.816 and sCD163; 0.743). In addition, composite parameters including serum HO-1 and the GGO and consolidation score showed a higher AUC for predicting ICU admission than the AUC of a single parameter.

Conclusion

Clinically, serum HO-1, reflecting the activation of M2, could be a very useful marker for evaluating disease severity and predicting prognoses for COVID-19 patients. In addition, controlling activated M2 might be a preventative COVID-19 therapeutic target.

Assessment of diagnostic utility of serum hemeoxygenase-1 measurement for acute exacerbation of interstitial pneumonias

The present study aimed to evaluate whether serum heme oxygenase (HO)-1 could be a reliable blood biomarker for diagnosing acute exacerbations (AEs) of both idiopathic interstitial pneumonia (IIP) and secondary interstitial pneumonia (SIP). Serum HO-1 levels of newly diagnosed patients with IP were measured, and the relationships between serum HO-1 and other serum biomarkers and high-resolution CT scores, were evaluated. Blood samples were collected from 90 patients with IIP, including 32 having an AE, and 32 with SIP, including 9 having an AE. The patients having an AE had significantly higher HO-1 levels than those not having an AE (35.2 ng/mL vs. 16.4 ng/mL; p < 0.001). On receiver operating characteristics (ROC) curve analysis for serum HO-1 ability to detect an AE, the area under the ROC curve (AUC) was 0.87 in patients with IIPs and 0.86 in those with SIPs. Also, in patients with both IIPs and SIPs, the combination of the serum HO-1 level and the GGO score showed favorable AUCs (IIPs: 0.92, SIPs: 0.83), though HO-1-not-including model (combination of LDH and GGO) also showed acceptable AUCs. Serum HO-1 could be a clinically useful biomarker for the accurate diagnosis of patients with AEs.

Chest CT Total Severity Score on Admission to Predict In-Hospital Mortality in COVID-19 Patients with Acute and Chronic Renal Impairment

Aim: To identify the predictors of in-hospital mortality in patients with coronavirus disease of 2019 (COVID-19) and acute renal impairment (ARI) or chronic kidney disease (CKD), and to evaluate the performance and inter-reader concordance of chest CT total severity scores (TSSs). Methods: This retrospective single-center study was conducted on symptomatic COVID-19 patients with renal impairment (either acute or chronic) and a serum creatinine of >2 mg/dL at the time of admission. The patients’ demographic characteristics, clinical data, and laboratory data were extracted from the clinical computerized medical records. All chest CT images obtained at the time of hospital admission were analyzed. Two radiologists independently assessed the pulmonary abnormalities and scored the severity using CT chest total severity score (TSS). Univariate logistic regression analysis was used to determine factors associated with in-hospital mortality. A receiver operating characteristic (ROC) curve analysis was performed for the TSS in order to identify the cut-off point that predicts mortality. Bland−Altman plots were used to evaluate agreement between the two radiologists assessing TSS. Results: A total of 100 patients were included, with a mean age of 60 years, 54 were males, 53 had ARI, and 47 had CKD. In terms of in-hospital mortality, 60 patients were classified in the non-survivor group and 40 were classified in the survivor group. The mortality rate was higher for those with ARI compared to those with CKD (p = 0.033). The univariate regression analysis showed an increasing odds of in-hospital mortality associated with higher respiratory rate (OR 1.149, 95% CI 1.057−1.248, p = 0.001), total bilirubin (OR 2.532, 95% CI 1.099−5.836, p = 0.029), lactate dehydrogenase (LDH) (OR 1.001, 95% CI 1.000−1.003, p = 0.018), CRP (OR 1.010, 95% CI 1.002−1.017, p = 0.012), invasive mechanical ventilation (MV) (OR 7.667, 95% CI 2.118−27.755, p = 0.002), a predominant pattern of pulmonary consolidation (OR 21.714, 95% CI 4.799−98.261, p < 0.001), and high TSS (OR 2.082, 95% CI 1.579−2.745, p < 0.001). The optimum cut-off value of TSS used to predict in-hospital mortality was 8.5 with a sensitivity of 86.7% and a specificity of 87.5%. There was excellent interobserver agreement (ICC > 0.9) between the two independent radiologists in their quantitative assessment of pulmonary changes using TSS. Conclusions: In-hospital mortality is high in COVID-19 patients with ARI/CKD, especially for those with ARI. High serum bilirubin, a predominant pattern of pulmonary consolidation, and TSS are the most significant predictors of mortality in these patients. Patients with a higher TSS may require more intensive hospital care. TSS is a reliable and helpful auxiliary tool for risk stratification among COVID-19 patients with ARI/CKD.

Quantitative inspiratory-expiratory chest CT findings in COVID-19 survivors at the 6-month follow-up

We evaluated pulmonary sequelae in COVID-19 survivors by quantitative inspiratory-expiratory chest CT (QCT) and explored abnormal pulmonary diffusion risk factors at the 6-month follow-up. This retrospective study enrolled 205 COVID-19 survivors with baseline CT data and QCT scans at 6-month follow-up. Patients without follow-up pulmonary function tests were excluded. All subjects were divided into group 1 (carbon monoxide diffusion capacity [DL_CO] < 80% predicted, n = 88) and group 2 (DL_CO ≥ 80% predicted, n = 117). Clinical characteristics and lung radiological changes were recorded. Semiquantitative total CT score (0-25) was calculated by adding five lobes scores (0-5) according to the range of lesion involvement (0: no involvement; 1: < 5%; 2: 5-25%; 3: 26-50%; 4: 51-75%; 5: > 75%). Data was analyzed by two-sample t-test, Spearman test, etc. 29% survivors showed air trapping by follow-up QCT. Semiquantitative CT score and QCT parameter of air trapping in group 1 were significantly greater than group 2 (p < 0.001). Decreased DL_CO was negatively correlated with the follow-up CT score for ground-glass opacity (r = - 0.246, p = 0.003), reticulation (r = - 0.206, p = 0.002), air trapping (r = - 0.220, p = 0.002) and relative lung volume changes (r = - 0.265, p = 0.001). COVID-19 survivors with lung diffusion deficits at 6-month follow-up tended to develop air trapping, possibly due to small-airway impairment.

Changes in blood Krebs von den Lungen-6 predict the mortality of patients with acute exacerbation of interstitial lung disease

Acute exacerbation (AE) significantly affects the prognosis of patients with interstitial lung disease (ILD). This study aimed to investigate the best prognostic biomarker for patients with AE-ILD. Clinical data obtained during hospitalization were retrospectively analyzed for 96 patients with AE-ILD at three tertiary hospitals. The mean age of all subjects was 70.1 years; the percentage of males was 66.7%. Idiopathic pulmonary fibrosis accounted for 60.4% of the cases. During follow-up (median: 88 days), in-hospital mortality was 24%. Non-survivors had higher lactate dehydrogenase and C-reactive protein (CRP) levels, lower ratio of partial pressure of oxygen to the fraction of inspiratory oxygen (P/F ratio), and higher relative change in Krebs von den Lungen-6 (KL-6) levels over 1 week after hospitalization than survivors. In multivariable analysis adjusted by age, the 1-week change in KL-6-along with baseline P/F ratio and CRP levels-was an independent prognostic factor for in-hospital mortality (odds ratio 1.094, P = 0.025). Patients with remarkable increase in KL-6 (≥ 10%) showed significantly worse survival (in-hospital mortality: 63.2 vs. 6.1%) than those without. In addition to baseline CRP and P/F ratio, the relative changes in KL-6 over 1 week after hospitalization might be useful for predicting in-hospital mortality in patients with AE-ILD.

In hospital risk factors for acute kidney injury and its burden in patients with Sars-Cov-2 infection: a longitudinal multinational study

Acute kidney injury (AKI) is associated with increased mortality in most critical settings. However, it is unclear whether its mild form (i.e. AKI stage 1) is associated with increased mortality also in non-critical settings. Here we conducted an international study in patients hospitalized with SARS-CoV-2 infection aiming 1. to estimate the incidence of AKI at each stage and its impact on mortality 2. to identify AKI risk factors at admission (susceptibility) and during hospitalization (exposures) and factors contributing to AKI-associated mortality. We included 939 patients from medical departments in Moscow (Russia) and Padua (Italy). In-hospital AKI onset was identified in 140 (14.9%) patients, mainly with stage 1 (65%). Mortality was remarkably higher in patients with AKI compared to those without AKI (55 [39.3%] vs. 34 [4.3%], respectively). Such association remained significant after adjustment for other clinical conditions at admission (relative risk [RR] 5.6; CI 3.5- 8.8) or restricting to AKI stage 1 (RR 3.2; CI 1.8-5.5) or to subjects with AKI onset preceding deterioration of clinical conditions. After hospital admission, worsening of hypoxic damage, inflammation, hyperglycemia, and coagulopathy were identified as hospital-acquired risk factors predicting AKI onset. Following AKI onset, the AKI-associated worsening of respiratory function was identified as the main contributor to AKI-induced increase in mortality risk. In conclusion, AKI is a common complication of Sars-CoV2 infection in non-intensive care settings where it markedly increases mortality risk also at stage 1. The identification of hospital-acquired risk factors and exposures might help prevention of AKI onset and of its complications.

New risk scoring system for predicting 3-month mortality after acute exacerbation of idiopathic pulmonary fibrosis

Acute exacerbation of idiopathic pulmonary fibrosis (AE-IPF) is often fatal. A straightforward staging system for AE-IPF would improve prognostication, guide patient management, and facilitate research. The aim of study is to develop a multidimensional prognostic AE-IPF staging system that uses commonly measured clinical variables. This retrospective study analyzed data from 353 consecutive patients with IPF admitted to our hospital during the period from January 2008 through January 2018. Multivariate analysis of information from a database of 103 recorded AE-IPF cases was used to identify factors associated with 3-month mortality. A clinical prediction model for AE-IPF was developed by using these retrospective data. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance of this model. Logistic regression analysis showed that PaO₂/FiO₂ ratio, diffuse HRCT pattern, and serum C-reactive protein (CRP) were significantly associated with 3-month mortality; thus, PaO₂/FiO₂ ratio < 250 (P), CRP ≥ 5.5 (C), and diffuse HRCT pattern (radiological) (R) were included in the final model. A model using continuous predictors and a simple point-scoring system (PCR index) was developed. For the PCR index, the area under the ROC curve was 0.7686 (P < 0.0001). The sensitivity of the scoring system was 78.6% and specificity was 67.8%. The PCR index identified four severity grades (0, 1, 2, and 3), which were associated with a 3-month mortality of 7.7%, 29.4%, 54.8%, and 80%, respectively. The present PCR models using commonly measured clinical and radiologic variables predicted 3-month mortality in patients with AE-IPF.

Acute Exacerbation of Idiopathic Pulmonary Fibrosis

Acute exacerbation is a major cause of morbidity and mortality in patients with idiopathic pulmonary fibrosis. Although the real nature of it is still not clear and there is no proven effective therapy, progress has been made since the consensus definition and diagnostic criteria were proposed. The trial results of several new innovative therapies in idiopathic pulmonary fibrosis have suggested a potential for benefit in acute exacerbation of idiopathic pulmonary fibrosis, leading to double blind randomized clinical trials in this area. This article reviews the present knowledge on acute exacerbation of idiopathic pulmonary fibrosis, focusing on the triggering factors and treatment.

Finding of the factors affecting the severity of COVID-19 based on mathematical models

Since 2019, a large number of people worldwide have been infected with severe acute respiratory syndrome coronavirus 2. Among those infected, a limited number develop severe coronavirus disease 2019 (COVID-19), which generally has an acute onset. The treatment of patients with severe COVID-19 is challenging. To optimize disease prognosis and effectively utilize medical resources, proactive measures must be adopted for patients at risk of developing severe COVID-19. We analyzed the data of COVID-19 patients from seven medical institutions in Tokyo and used mathematical modeling of patient blood test results to quantify and compare the predictive ability of multiple prognostic indicators for the development of severe COVID-19. A machine learning logistic regression model was used to analyze the blood test results of 300 patients. Due to the limited data set, the size of the training group was constantly adjusted to ensure that the results of machine learning were effective (e.g., recognition rate of disease severity > 80%). Lymphocyte count, hemoglobin, and ferritin levels were the best prognostic indicators of severe COVID-19. The mathematical model developed in this study enables prediction and classification of COVID-19 severity.

Comparison of Clinical Features between the High and Low Serum KL-6 Patients with Acute Exacerbation of Interstitial Lung Diseases

Background

Serum Krebs von den Lungen-6 (KL-6) measurement is widely used to assess disease activity or prognosis in patients with interstitial lung diseases (ILDs). However, the clinical differences between high and low serum KL-6 levels at the time of acute exacerbation (AE) of ILD are not well known.

Methods

Clinical parameters including age, sex, Charlson Comorbidity Index score (CCIS), blood biomarkers, high-resolution CT findings, and disease mortality were retrospectively compared between high and low KL-6 (cutoff value: 1000 U/mL) patients at the time of diagnosis of AE of ILDs.

Results

Thirty-eight high serum KL-6 and 57 low serum KL-6 patients were included. There was no significant difference in 6-month mortality between them (P = 0.685), whereas serum lactate dehydrogenase was a significant predictor of 6-month mortality in the high serum KL-6 patients (odds ratio (OR): 1.006; 95% confidence interval (CI): 1.003–1.009; P < 0.001), and CCIS (OR: 1.502; 95% CI: 1.242–1.838; P < 0.001) and sex (OR: 5.751; 95% CI: 1.121–105.163; P = 0.033) were significant predictors in low serum KL-6 patients. In addition, the incidences of congestive heart failure, symptomatic chronic pulmonary disease, cerebrovascular disease, and second metastatic solid tumours were significantly higher in nonsurvivors with low serum KL-6 than in other groups (P < 0.05).

Conclusions

The clinical features in patients with AEs of ILDs may differ depending on the serum KL-6 level, and clinicopathological examination according to this subtyping guided by the serum KL-6 level is essential.

Factors Affecting the Incidence, Progression, and Severity of COVID-19 in Type 1 Diabetes Mellitus

Objectives

This study screened for factors affecting coronavirus disease 2019 (COVID-19) incidence in type 1 diabetes mellitus (T1DM) patients, appraised vitamin D's efficacy in preventing COVID-19, and assessed the effects of clinical characteristics, glycemic status, vitamin D, and hydroxychloroquine administration on COVID-19's progression and severity in T1DM patients.

Methods

This retrospective research on 150 adults was conducted at Security Forces Hospital, Riyadh, KSA. Participants were allocated to three groups (50/group): control, T1DM, and T1DM with COVID-19. Participants' fasting blood glucose (FBG), glycated hemoglobin (HbA1c), complete blood count, vitamin D, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), ferritin, lactate dehydrogenase (LDH), prothrombin time, activated partial thromboplastin time, D-dimer, liver and kidney function, and hydroxychloroquine treatment were retrieved and analyzed.

Results

The percentages of comorbidities and not taking hydroxychloroquine were significantly higher among T1DM patients with COVID-19 than patients with T1DM only. Mean vitamin D level was significantly lower in T1DM with COVID-19 patients than in the other two groups. Vitamin D showed a significant negative correlation with LDH, CRP, ESR, ferritin, and D-dimer, which was the most reliable predictor of COVID-19 severity in T1DM patients.

Conclusion

Comorbidities and vitamin D deficiency are risk factors for COVID-19 in patients with T1DM. Patients who do not take hydroxychloroquine and have higher FBG and HbA1c levels are vulnerable to COVID-19. Vitamin D may be useful for preventing COVID-19 in T1DM patients. Comorbidities, higher FBG and HbA1c levels, not taking hydroxychloroquine, and vitamin D inadequacy elevate COVID-19 progression and severity in patients with T1DM.

The Extent of Honeycombing on Computed Tomography Cannot Predict the Treatment Outcome of Patients with Acute Exacerbations of Interstitial Lung Disease

Background

The purpose of this retrospective study was to clarify whether the presence of honeycombing on computed tomography (CT) can affect the prognosis of patients with acute exacerbations (AEs) of interstitial lung diseases (ILDs).

Methods

Clinical parameters including age, sex, Charlson Comorbidity Index Score (CCIS), blood biomarkers, and 3-month mortality were retrospectively compared between the CT honeycombing present and absent groups at the diagnosis of AEs of ILDs.

Results

Ninety-five patients who were on corticosteroid pulse therapy were assessed. Though log-rank tests showed that Kaplan–Meier survival curves of the high and low ground-glass opacity (GGO) score groups differed significantly in 3-month mortality in patients with AEs of idiopathic ILDs (P = 0.007) and overall patients (P = 0.045), there was no significant difference between the CT honeycombing present and absent groups in patients with AEs of idiopathic ILDs (P = 0.472) and AEs of secondary ILDs (P = 0.905), as well as of overall patients (P = 0.600). In addition, whereas CCIS (OR, 1.436; 95% CI, 1.156–1.842; P < 0.001) was a significant predictor of 3-month mortality in the CT honeycombing absent group, serum LDH (OR, 1.005; 95% CI, 1.002–1.007; P = 0.001) was a significant predictor in the CT honeycombing present group.

Conclusions

The clinical features of patients with or without honeycombing may differ due to the difference in prognostic factors, but these groups were found to have similar prognoses 3 months after AE onset, and clinicopathological examinations according to these groups are essential.

Follow-up study of pulmonary sequelae in discharged COVID-19 patients with diabetes or secondary hyperglycemia

Purpose

To determine chest CT changes 6 months and 12 months after the onset of coronavirus disease 2019 (COVID-19) in patients with diabetes or hyperglycemia and the risk factors for these residual lung abnormalities.

Methods

In total, 141 COVID-19 patients were assigned to group 1 (diabetes), group 2 (secondary hyperglycemia) or group 3 (controls). Initial and six- and twelve-month follow-up computed tomography (CT) scans were performed 16 days, 175 days and 351 days after symptom onset, respectively. CT findings and clinical and peak laboratory parameters were collected and compared. Univariable and multivariable logistic regression analyses were performed to identify the independent predictors for the presence of residual lung abnormalities at the 6-month follow-up exam. Seven variables (age; the presence of acute respiratory distress syndrome; the duration of hospitalization; the peak levels of lactate dehydrogenase (LDH) and C-reactive protein; and the initial total CT score) were chosen in the final multivariable models.

Results

At the six-month follow-up, abnormalities were still observed on chest CT in 77/141 (54.6%) patients. Reticular patterns (40/141, 28.4%) and ground-glass opacities (GGOs) (29/141, 20.6%) were the most common CT abnormalities on the follow-up CT scans. Patients in Groups 1 and 2 had significantly higher incidences of residual lung abnormalities than those in Group 3 (65.4% and 58.3%, respectively vs. 36.6%; p < 0.05). Twelve months after disease onset, the chest CT changes persisted in 13/25 (52.0%) patients. A duration of hospitalization > 20 days (OR: 5.630, 95% CI: 1.394–22.744, p = 0.015), an LDH level ≥ 317 U/L (OR: 7.020, 95% CI: 1.032–47.743, p = 0.046) and a total CT score > 15 (OR: 9.919, 95% CI: 1.378–71.415, p = 0.023) were independent predictors of residual pulmonary abnormalities in patients with diabetes or secondary hyperglycemia.

Conclusions

A considerable proportion of surviving COVID-19 patients with diabetes or secondary hyperglycemia had residual pulmonary abnormalities six months after disease onset, and we found evidence of persistent chest CT changes at the one-year follow-up. Residual lung abnormalities were associated with longer hospital stays, higher peak LDH levels and higher initial total CT scores.

Reliable and Interpretable Mortality Prediction With Strong Foresight in COVID-19 Patients: An International Study From China and Germany

Cohort-independent robust mortality prediction model in patients with COVID-19 infection is not yet established. To build up a reliable, interpretable mortality prediction model with strong foresight, we have performed an international, bi-institutional study from China (Wuhan cohort, collected from January to March) and Germany (Würzburg cohort, collected from March to September). A Random Forest-based machine learning approach was applied to 1,352 patients from the Wuhan cohort, generating a mortality prediction model based on their clinical features. The results showed that five clinical features at admission, including lymphocyte (%), neutrophil count, C-reactive protein, lactate dehydrogenase, and α-hydroxybutyrate dehydrogenase, could be used for mortality prediction of COVID-19 patients with more than 91% accuracy and 99% AUC. Additionally, the time-series analysis revealed that the predictive model based on these clinical features is very robust over time when patients are in the hospital, indicating the strong association of these five clinical features with the progression of treatment as well. Moreover, for different preexisting diseases, this model also demonstrated high predictive power. Finally, the mortality prediction model has been applied to the independent Würzburg cohort, resulting in high prediction accuracy (with above 90% accuracy and 85% AUC) as well, indicating the robustness of the model in different cohorts. In summary, this study has established the mortality prediction model that allowed early classification of COVID-19 patients, not only at admission but also along the treatment timeline, not only cohort-independent but also highly interpretable. This model represents a valuable tool for triaging and optimizing the resources in COVID-19 patients.

Clinical characteristics and a decision tree model to predict death outcome in severe COVID-19 patients

Background

The novel coronavirus disease 2019 (COVID-19) spreads rapidly among people and causes a pandemic. It is of great clinical significance to identify COVID-19 patients with high risk of death.

Methods

A total of 2169 adult COVID-19 patients were enrolled from Wuhan, China, from February 10th to April 15th, 2020. Difference analyses of medical records were performed between severe and non-severe groups, as well as between survivors and non-survivors. In addition, we developed a decision tree model to predict death outcome in severe patients.

Results

Of the 2169 COVID-19 patients, the median age was 61 years and male patients accounted for 48%. A total of 646 patients were diagnosed as severe illness, and 75 patients died. An older median age and a higher proportion of male patients were found in severe group or non-survivors compared to their counterparts. Significant differences in clinical characteristics and laboratory examinations were found between severe and non-severe groups, as well as between survivors and non-survivors. A decision tree, including three biomarkers, neutrophil-to-lymphocyte ratio, C-reactive protein and lactic dehydrogenase, was developed to predict death outcome in severe patients. This model performed well both in training and test datasets. The accuracy of this model were 0.98 in both datasets.

Conclusion

We performed a comprehensive analysis of COVID-19 patients from the outbreak in Wuhan, China, and proposed a simple and clinically operable decision tree to help clinicians rapidly identify COVID-19 patients at high risk of death, to whom priority treatment and intensive care should be given.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-06478-w.

Virus load and incidence of olfactory, gustatory, respiratory, gastrointestinal disorders in COVID-19 patients: A retrospective cohort study

Objectives

This study investigated the relationship between viral load and the incidence of olfactory and gustatory dysfunction (OD and GD), the incidence of respiratory and gastrointestinal symptoms and the recovery of OD and GD in COVID‐19 patients.

Design

A retrospective cohort study.

Setting and Participants

This study was conducted on 599 outpatients' cases in Golestan province between February and June 2020.

Main Outcome Measures

The incidence, severity (complete or partial) and recovery time of OD and GD and their associations with cycle threshold (CT) values of SARS‐CoV‐2 polymerase chain reaction were assessed.

Results

The mean age of patients was 38.27 ± 13.62 years. The incidence of general symptoms included myalgia 70.1%, headache 51.8%, fever 47.7% and dyspnoea 21.4%. 41.9% of patients had gastrointestinal symptoms, including abdominal pain 26.5%, diarrhoea 25.2%, nausea 20.5% and vomiting 12.9%. 12.2% of patients had comorbidity. The trimester recovery rates of OD and GD were 93.94% and 94.74% respectively. The mean recovery time of OD and GD was 14.56 ± 13.37 and 13.8 ± 3.77 days respectively. The mean CT value in all patients was 27.45 ± 4.55. There were significant associations between the mean of CT value with headache (p = 0.04), GD (p = 0.002) and OD (p = 0.001).

Conclusions

The finding of this study indicates a possible association between viral load with incidence of OD and GD in COVID‐19 patient's cases and assures the recovery of OD/GD in these patients.

Predictive Modeling of Morbidity and Mortality in Patients Hospitalized With COVID-19 and its Clinical Implications: Algorithm Development and Interpretation

Background

The COVID-19 pandemic began in early 2021 and placed significant strains on health care systems worldwide. There remains a compelling need to analyze factors that are predictive for patients at elevated risk of morbidity and mortality.

Objective

The goal of this retrospective study of patients who tested positive with COVID-19 and were treated at NYU (New York University) Langone Health was to identify clinical markers predictive of disease severity in order to assist in clinical decision triage and to provide additional biological insights into disease progression.

Methods

The clinical activity of 3740 patients at NYU Langone Hospital was obtained between January and August 2020; patient data were deidentified. Models were trained on clinical data during different parts of their hospital stay to predict three clinical outcomes: deceased, ventilated, or admitted to the intensive care unit (ICU).

Results

The XGBoost (eXtreme Gradient Boosting) model that was trained on clinical data from the final 24 hours excelled at predicting mortality (area under the curve [AUC]=0.92; specificity=86%; and sensitivity=85%). Respiration rate was the most important feature, followed by SpO₂ (peripheral oxygen saturation) and being aged 75 years and over. Performance of this model to predict the deceased outcome extended 5 days prior, with AUC=0.81, specificity=70%, and sensitivity=75%. When only using clinical data from the first 24 hours, AUCs of 0.79, 0.80, and 0.77 were obtained for deceased, ventilated, or ICU-admitted outcomes, respectively. Although respiration rate and SpO₂ levels offered the highest feature importance, other canonical markers, including diabetic history, age, and temperature, offered minimal gain. When lab values were incorporated, prediction of mortality benefited the most from blood urea nitrogen and lactate dehydrogenase (LDH). Features that were predictive of morbidity included LDH, calcium, glucose, and C-reactive protein.

Conclusions

Together, this work summarizes efforts to systematically examine the importance of a wide range of features across different endpoint outcomes and at different hospitalization time points.

High flow nasal cannula for adult acute hypoxemic respiratory failure in the ED setting: A narrative review

Introduction

High flow nasal cannula (HFNC) is a noninvasive ventilation (NIV) system that has demonstrated promise in the emergency department (ED) setting.

Objective

This narrative review evaluates the utility of HFNC in adult patients with acute hypoxemic respiratory failure in the ED setting.

Discussion

HFNC provides warm (37 °C), humidified (100% relative humidity) oxygen at high flows with a reliable fraction of inspired oxygen (FiO₂). HFNC can improve oxygenation, reduce airway resistance, provide humidified flow that can flush anatomical dead space, and provide a low amount of positive end expiratory pressure. Recent literature has demonstrated efficacy in acute hypoxemic respiratory failure, including pneumonia, acute respiratory distress syndrome (ARDS), coronavirus disease 2019 (COVID-19), interstitial lung disease, immunocompromised states, the peri-intubation state, and palliative care, with reduced need for intubation, length of stay, and mortality in some of these conditions. Individual patient factors play an important role in infection control risks with respect to the use of HFNC in patients with COVID-19. Appropriate personal protective equipment, adherence to hand hygiene, surgical mask placement over the HFNC device, and environmental controls promoting adequate room ventilation are the foundation for protecting healthcare personnel. Frequent reassessment of the patient placed on HFNC is necessary; those with severe end organ dysfunction, thoracoabdominal asynchrony, significantly increased respiratory rate, poor oxygenation despite HFNC, and tachycardia are at increased risk of HFNC failure and need for further intervention.

Conclusions

HFNC demonstrates promise in several conditions requiring respiratory support. Further randomized trials are needed in the ED setting.

Efficacy of recombinant thrombomodulin for poor prognostic cases of acute exacerbation in idiopathic interstitial pneumonia: secondary analysis of the SETUP trial

Background

Acute exacerbation (AE) in idiopathic pulmonary fibrosis and other idiopathic interstitial pneumonias (IIPs) are poor prognostic events although they are usually treated with conventional therapy with corticosteroids and immunosuppressants. Previously, we demonstrated the safety and efficacy of recombinant human soluble thrombomodulin (rhTM) for AE-IIP in the SETUP trial. Here, we aimed to clarify the efficacy of rhTM for poor-prognosis cases of AE-IIP.

Methods

In this study, we included 85 patients, in whom fibrin degradation product (FDP)/d-dimer was evaluated at AE, from the 100 patients in the SETUP trial. The AE-IIP patients in the rhTM arm (n=39) were diagnosed using the Japanese criteria from 2014 to 2016 and treated with intravenous rhTM for 6 days in addition to the conventional therapy. The AE-IIP patients in the control arm (n=46) were treated with the conventional therapy without rhTM between 2011 and 2013. The subjects were classified into higher and lower FDP/d-dimer groups based on the Japanese Association for Acute Medicine Disseminated Intravascular Coagulation scoring system. A multivariate Cox proportional hazard regression analysis with stepwise selection was performed to reveal the prognostic factors of AE-IIP.

Results

We developed a prognostic scoring system using two significant prognostic factors, higher FDP/d-dimer at AE and prednisolone therapy before AE, with 3 and 2 points assigned for each parameter, respectively. The prognostic scores ranged from 0 to 5. Survival of AE-IIP patients with a prognostic score=0 was significantly better than that of patients with score ≥2. Survival was improved with the rhTM therapy (p<0.05) in the poor prognostic cases (score ≥2), but not in the good prognostic cases (score=0).

Conclusions

Treatment with rhTM might improve survival in AE-IIP cases with poor prognoses.

Trial registration number

UMIN000014969, date: 28 August 2014.

Pulse oximetric saturation to fraction of inspired oxygen (SpO2/FIO2) ratio 24 hours after high-flow nasal cannula (HFNC) initiation is a good predictor of HFNC therapy in patients with acute exacerbation of interstitial lung disease

BACKGROUND

High-flow nasal cannula (HFNC) oxygen therapy provides effective respiratory management in patients with hypoxemic respiratory failure. However, the efficacy and tolerability of HFNC for patients with acute exacerbation of interstitial lung disease (AE-ILD) have not been established. This study was performed to assess the efficacy and tolerability of HFNC for patients with AE-ILD and identify the early predictors of the outcome of HFNC treatment.

METHODS

We retrospectively reviewed the records of patients with AE-ILD who underwent HFNC. Overall survival, the success rate of HFNC treatment, adverse events, temporary interruption of treatment, discontinuation of treatment at the patient's request, and predictors of the outcome of HFNC treatment were evaluated.

RESULTS

A total of 66 patients were analyzed. Of these, 26 patients (39.4%) showed improved oxygenation and were successfully withdrawn from HFNC. The 30-day survival rate was 48.5%. No discontinuations at the patient's request were observed, and no serious adverse events occurred. The pulse oximetric saturation to fraction of inspired oxygen (SpO₂/FIO₂) ratio 24 h after initiating HFNC showed high prediction accuracy (area under the receiver operating characteristic curve, 0.802) for successful HFNC treatment. In the multivariate logistic regression analysis, an SpO₂/FIO₂ ratio of at least 170.9 at 24 h after initiation was significantly associated with successful HFNC treatment (odds ratio, 51.3; 95% confidence interval, 6.13-430; p < 0.001).

CONCLUSIONS

HFNC was well tolerated in patients with AE-ILD, suggesting that HFNC is a reasonable respiratory management for these patients. The SpO₂/FIO₂ ratio 24 h after initiating HFNC was a good predictor of successful HFNC treatment. The reviews of this paper are available via the supplemental material section.

Acute exacerbation of fibrotic hypersensitivity pneumonitis: incidence and outcomes

BACKGROUND

Patients with fibrotic hypersensitivity pneumonitis (HP) show variable clinical courses, and some experience rapid deterioration (RD), including acute exacerbation (AE). However, little is known about AE in fibrotic HP. Here, we retrospectively examined the incidence, risk factors, and outcomes of AE in fibrotic HP.

METHODS

The incidence rates of AE were calculated in 101 patients with biopsy-proven HP. AE was defined as the worsening of dyspnoea within 30 days, with new bilateral lung infiltration and no evidence of infection or other causes of dyspnoea.

RESULTS

During follow-up (median: 30 months), 18 (17.8%) patients experienced AE. The 1, 3, and 5 year incidence rates of AE were 6.0, 13.6, and 22.8%, respectively. Lower diffusing capacity of the lung for carbon monoxide (DL_CO) and a radiologic usual interstitial pneumonia (UIP)-like pattern were risk factors for AE. In-hospital mortality after AE was 44.4%. Median survival from diagnosis was significantly shorter in patients with AE (26.0 months) than in those with no-AE RD (55.0 months; p = 0.008) or no RD (not reached; p < 0.001). AE remained a significant predictor of all-cause mortality (hazard ratio, 8.641; 95% confidence interval, 3.388-22.040; p < 0.001) after adjustment for age, body mass index, lung function, lymphocyte levels in bronchoalveolar lavage fluid, and the presence of a UIP-like pattern.

CONCLUSIONS

AE was not uncommon among patients with fibrotic HP and significantly affected prognosis. A lower DL_CO value and radiologic UIP-like pattern at diagnosis were associated with the development AE in patients with fibrotic HP.

High-flow nasal cannula therapy for acute respiratory failure in patients with interstitial pneumonia: a retrospective observational study

High-flow nasal cannula (HFNC) oxygen is a therapy that has demonstrated survival benefits in acute respiratory failure (ARF). However, the role of HFNC in ARF due to interstitial pneumonia (IP) is unknown. The aim of this study was to compare the effects of HFNC therapy and non-invasive positive pressure ventilation (NPPV) in ARF due to IP. This retrospective observational study included 32 patients with ARF due to IP who were treated with HFNC (n = 13) or NPPV (n = 19). The clinical characteristics, intubation rate and 30-day mortality were analyzed and compared between the HFNC group and the NPPV group. Predictors of 30-day mortality were evaluated using a logistic regression model. HFNC group showed higher mean arterial blood pressure (median 92 mmHg; HFNC group vs 74 mmHg; NPPV group) and lower APACHEII score (median 22; HFNC group vs 27; NPPV group) than NPPV group. There was no significant difference in the intubation rate at day 30 between the HFNC group and the NPPV group (8% vs 37%: p = 0.069); the mortality rate at 30 days was 23% and 63%, respectively. HFNC therapy was a significant determinant of 30-day mortality in univariate analysis, and was confirmed to be an independent significant determinant of 30-day mortality in multivariate analysis (odds ratio, 0.148; 95% confidence interval, 0.025–0.880; p = 0.036). Our findings suggest that HFNC therapy can be a possible option for respiratory management in ARF due to IP. The results observed here warrant further investigation of HFNC therapy in randomized control trials.

Prognostic classification in acute exacerbation of idiopathic pulmonary fibrosis: a multicentre retrospective cohort study

Acute exacerbation (AE) in idiopathic pulmonary fibrosis (IPF) is a major prognostic determinant. However, evidence for its prognostic strength is mainly based on the results of small cohort studies with statistical limitations. This retrospective study, which included 108 patients with a first episode of AE-IPF, aimed to identify prognostic factors and to develop prognostic classification models. Multivariate Cox regression analysis revealed that a lower percent-predicted forced vital capacity within 12 months before AE onset (baseline %FVC) and a lower PaO₂/FiO₂ ratio at AE onset were independent mortality predictors. If the value of each predictor was lower than the cutoff determined by receiver-operating characteristic analysis, 1 point was assigned. Classification of patients into mild, moderate, and severe groups based on total score showed post-AE 90-day cumulative survival rates of 83.3%, 66.2%, and 22.2%, respectively (model 1: C-index 0.702). Moreover, a decision tree-based model was created with the recursive partitioning method using baseline %FVC and PaO₂/FiO₂ ratio at AE onset from among multivariable; accordingly, patients were classified into 3 groups with post-AE 90-day cumulative survival rates of 84.1%, 64.3%, and 24.0%, respectively (model 2: C-index 0.735). These models can guide clinicians in determining therapeutic strategies and help design future studies on AE-IPF.

Ground-glass opacity (GGO): a review of the differential diagnosis in the era of COVID-19

Thoracic imaging is fundamental in the diagnostic route of Coronavirus disease 2019 (COVID-19) especially in patients admitted to hospitals. In particular, chest computed tomography (CT) has a key role in identifying the typical features of the infection. Ground-glass opacities (GGO) are one of the main CT findings, but their presence is not specific for this viral pneumonia. In fact, GGO is a radiological sign of different pathologies with both acute and subacute/chronic clinical manifestations. In the evaluation of a subject with focal or diffuse GGO, the radiologist has to know the patient’s medical history to obtain a valid diagnostic hypothesis. The authors describe the various CT appearance of GGO, related to the onset of symptoms, focusing also on the ancillary signs that can help radiologist to obtain a correct and prompt diagnosis.

An Early Warning Tool for Predicting Mortality Risk of COVID-19 Patients Using Machine Learning

COVID-19 pandemic has created an extreme pressure on the global healthcare services. Fast, reliable, and early clinical assessment of the severity of the disease can help in allocating and prioritizing resources to reduce mortality. In order to study the important blood biomarkers for predicting disease mortality, a retrospective study was conducted on a dataset made public by Yan et al. in [1] of 375 COVID-19 positive patients admitted to Tongji Hospital (China) from January 10 to February 18, 2020. Demographic and clinical characteristics and patient outcomes were investigated using machine learning tools to identify key biomarkers to predict the mortality of individual patient. A nomogram was developed for predicting the mortality risk among COVID-19 patients. Lactate dehydrogenase, neutrophils (%), lymphocyte (%), high-sensitivity C-reactive protein, and age (LNLCA)-acquired at hospital admission-were identified as key predictors of death by multi-tree XGBoost model. The area under curve (AUC) of the nomogram for the derivation and validation cohort were 0.961 and 0.991, respectively. An integrated score (LNLCA) was calculated with the corresponding death probability. COVID-19 patients were divided into three subgroups: low-, moderate-, and high-risk groups using LNLCA cutoff values of 10.4 and 12.65 with the death probability less than 5%, 5-50%, and above 50%, respectively. The prognostic model, nomogram, and LNLCA score can help in early detection of high mortality risk of COVID-19 patients, which will help doctors to improve the management of patient stratification.

Prognostic role of Krebs von den Lungen-6 (KL-6) measurement in idiopathic pulmonary fibrosis: a systematic review and meta-analysis

OBJECTIVES

Idiopathic pulmonary fibrosis (IPF) is a progressive interstitial disease with limited therapeutic options. The measurement of Krebs von den Lungen-6 (KL-6) glycoprotein has been proposed for evaluating the risk of IPF progression and predicting patient prognosis, but the robustness of available evidence is unclear.

METHODS

We searched Medline and Embase databases for peer-reviewed literature from inception to April 2020. Original articles investigating KL-6 as prognostic marker for IPF were retrieved. Considered outcomes were the risk of developing acute exacerbation (AE) and patient survival. Meta-analysis of selected studies was conducted, and quantitative data were uniformed as odds ratio (OR) or hazard ratio (HR) estimates, with corresponding 95% confidence intervals (CI).

RESULTS

Twenty-six studies were included in the systematic review and 14 were finally meta-analysed. For AE development, the pooled OR (seven studies) for KL-6 was 2.72 (CI 1.22-6.06; p=0.015). However, a high degree of heterogeneity (I²=85.6%) was found among selected studies. Using data from three studies reporting binary data, a pooled sensitivity of 72% (CI 60-82%) and a specificity of 60% (CI 52-68%) were found for KL-6 measurement in detecting insurgence of AE in IPF patients. Pooled HR (seven studies) for mortality prediction was 1.009 (CI 0.983-1.036; p=0.505).

CONCLUSIONS

Although our meta-analysis suggested that IPF patients with increased KL-6 concentrations had a significant increased risk of developing AE, the detection power of the evaluated biomarker is limited. Furthermore, no relationship between biomarker concentrations and mortality was found. Caution is also needed when extending obtained results to non-Asian populations.

Predictive modeling of morbidity and mortality in COVID-19 hospitalized patients and its clinical implications

Clinical activity of 3740 de-identified COVID-19 positive patients treated at NYU Langone Health (NYULH) were collected between January and August 2020. XGBoost model trained on clinical data from the final 24 hours excelled at predicting mortality (AUC=0.92, specificity=86% and sensitivity=85%). Respiration rate was the most important feature, followed by SpO2 and age 75+. Performance of this model to predict the deceased outcome extended 5 days prior with AUC=0.81, specificity=70%, sensitivity=75%. When only using clinical data from the first 24 hours, AUCs of 0.79, 0.80, and 0.77 were obtained for deceased, ventilated, or ICU admitted, respectively. Although respiration rate and SpO2 levels offered the highest feature importance, other canonical markers including diabetic history, age and temperature offered minimal gain. When lab values were incorporated, prediction of mortality benefited the most from blood urea nitrogen (BUN) and lactate dehydrogenase (LDH). Features predictive of morbidity included LDH, calcium, glucose, and C-reactive protein (CRP). Together this work summarizes efforts to systematically examine the importance of a wide range of features across different endpoint outcomes and at different hospitalization time points.

Early prediction model for progression and prognosis of severe patients with coronavirus disease 2019

Coronavirus disease 2019 (COVID-19) has been a rampant worldwide health threat and we aimed to develop a model for early prediction of disease progression.This retrospective study included 124 adult inpatients with COVID-19 who presented with severe illness at admission and had a definite outcome (recovered or progressed to critical illness) during February 2020. Eighty-four patients were used as training cohort and 40 patients as validation cohort. Logistic regression analysis and receiver operating characteristic curve (ROC) analysis were used to develop and evaluate the prognostic prediction model.In the training cohort, the mean age was 63.4 ± 1.5 years, and male patients (48, 57%) were predominant. Forty-three (52%) recovered, and 41 (49%) progressed to critical. Decreased lymphocyte count (LC, odds ratio [OR] = 4.40, P = .026), elevated lactate dehydrogenase levels (LDH, OR = 4.24, P = .030), and high-sensitivity C-reactive protein (hsCRP, OR = 1.01, P = .025) at admission were independently associated with higher odds of deteriorated outcome. Accordingly, we developed a predictive model for disease progression based on the levels of the 3 risk factors (LC, LDH, and hsCRP) with a satisfactory performance in ROC analysis (area under the ROC curve [AUC] = 0.88, P < .001) and the best cut-off value was 0.526 with the sensitivity and specificity of 75.0% and 90.7%, respectively. Then, the model was internally validated by leave-one-out cross-validation with value of AUC 0.85 (P < .001) and externally validated in another validation cohort (26 recovered patients and 14 progressed patients) with AUC 0.84 (P < .001).We identified 3 clinical indicators of risk of progression and developed a severe COVID-19 prognostic prediction model, allowing early identification and intervention of high-risk patients being critically illness.