Consolidation Score Research Articles

Value of bronchoalveolar lavage fluid metagenomic next-generation sequencing in acute exacerbation of fibrosing interstitial lung disease: an individualized treatment protocol based on microbiological evidence

BackgroundAcute exacerbation of fibrosing interstitial lung diseases (AE-ILD) is a serious life-threatening event per year. Methylprednisolone and/or immunosuppressive agents (ISA) are a mainstay in any regimen, under the premise that pulmonary infection has been promptly identified and controlled. We investigated the value of bronchoalveolar lavage fluid (BALF) metagenomic next-generation sequencing (mNGS) on the treatment adjustment of AE-ILD.MethodsWe conducted a cross-sectional observational study. All data were collected prospectively and retrospectively analyzed. We included fifty-six patients with AE-ILD and nineteen stable ILD who underwent BALF mNGS at the beginning of admission.ResultsPatients with a variety of ILD classification were included. Connective–tissue disease related ILD (CTD-ILD) occupy the most common underlying non-idiopathic pulmonary fibrosis (non-IPF). The infection-triggered AE accounted for 39.29%, with the majority of cases being mixed infections. The microorganisms load in the AE-ILD group was significantly higher. After adjusted by mNGS, the therapy coverage number of pathogens was significantly higher compared to the initial treatment (p < 0.001). After treatment, the GGO score and the consolidation score were significantly lower during follow up in survivors (1.57 ± 0.53 vs. 2.38 ± 0.83 with p < 0.001, 1.11 ± 0.24 vs. 1.49 ± 0.47 with p < 0.001, respectively). Some detected microorganisms, such as Tropheryma whipplei, Mycobacterium, Aspergillus, and mixed infections were difficult to be fully covered by empirical medication. BALF mNGS was also very helpful for excluding infections and early administration of methylprednisolone and/or ISA.ConclusionsmNGS has been shown to be a useful tool to determine pathogens in patients with AE-ILD, the results should be fully analyzed. The comprehensive treatment protocol based on mNGS has been shown crucial in AE-ILD patients.

Impact of AI-assisted CXR analysis in detecting incidental lung nodules and lung cancers in non-respiratory outpatient clinics.

The use of artificial intelligence (AI) for chest X-ray (CXR) analysis is becoming increasingly prevalent in medical environments. This study aimed to determine whether AI in CXR can unexpectedly detect lung nodule detection and influence patient diagnosis and management in non-respiratory outpatient clinics. In this retrospective study, patients over 18 years of age, who underwent CXR at Yongin Severance Hospital outpatient clinics between March 2021 and January 2023 and were identified to have lung nodules through AI software, were included. Commercially available AI-based lesion detection software (Lunit INSIGHT CXR) was used to detect lung nodules. Out Of 56,802 radiographic procedures, 40,191 were from non-respiratory departments, with AI detecting lung nodules in 1,754 cases (4.4%). Excluding 139 patients with known lung lesions, 1,615 patients were included in the final analysis. Out of these, 30.7% (495/1,615) underwent respiratory consultation and 31.7% underwent chest CT scans (512/1,615). As a result of the CT scans, 71.5% (366 cases) were found to have true nodules. Among these, the final diagnoses included 36 lung cancers (7.0%, 36/512), 141 lung nodules requiring follow-up (27.5%, 141/512), 114 active pulmonary infections (22.3%, 114/512), and 75 old inflammatory sequelae (14.6%, 75/512). The mean AI nodule score for lung cancer was significantly higher than that for other nodules (56.72 vs. 33.44, p < 0.001). Additionally, active pulmonary infection had a higher consolidation score, and old inflammatory sequelae had the highest fibrosis score, demonstrating differences in the AI analysis among the final diagnosis groups. This study indicates that AI-detected incidental nodule abnormalities on CXR in non-respiratory outpatient clinics result in a substantial number of clinically significant diagnoses, emphasizing AI's role in detecting lung nodules and need for further evaluation and specialist consultation for proper diagnosis and management.

Analysis of clinical management and radiological affection of coronavirus disease 2019 patients under isolation: an experience from a University Hospital

Background During the coronavirus disease 2019 (COVID-19) pandemic, Egypt was among the minor epidemic areas. COVID-19 has wide variations in the clinical presentation manifesting as a heterogeneous disease severity varying from mild, moderate, and severe to critical illness. Objective This study aimed to identify the potential clinical, radiological, and laboratory characteristics and prognosis of the COVID-19 patients obtained during the first peak of this pandemic at a University Hospital in Egypt, and to provide a reference for the pandemic management in the subsequent peaks. Patients and methods A single-center prospective study was done on patients with COVID-19 admitted to Fayoum University Hospital during the period from May to July 2020. All patients had full medical history taking, clinical examination, laboratory assessment, oxygen-saturation monitoring, chest computed tomography (CT), and reverse transcriptase-PCR testing. All the patients were treated with the treatment protocol accredited by the Egyptian Ministry of Health and accordingly disease outcome was determined. Results The study included 162 COVID-19 patients, 80 (49.4%) had mild cases, 40 (24.7%) had moderate cases, and 26 (16.0%) and 16 (9.9%) had severe and critical cases, respectively. The median CT-severity score was 10 (3.75–11.25). Significantly high serum levels of C-reactive protein, D-dimer, lactate dehydrogenase, and ferritin levels were observed in severe cases (P&lt;0.01 for all) in comparison with mild/moderate cases. By comparing died cases with other severe cases, the proportion of cases with CURB 65 score (comorbidity, confusion, urea, respiratory rate, blood pressure, and 65 years of age or older score) more than or equal to 4, PaO2/FiO2 less than 300, hypoxemia less than 85%, higher levels of ferritin, D-dimer, alanine aminotransferase, aspartate aminotransferase, CT severity, and consolidation score were significantly higher in died cases than other severe cases. By regression analysis, among severe cases, predictors of death were the presence of comorbidity and increased consolidation size. Conclusion All healthcare workers should understand the presentation of the disease, workup, and supportive care experienced from the first outbreak and offer an evidence-based management for succeeding outbreaks in our community.

Development of a new prognostic model to predict pneumonia outcome using artificial intelligence-based chest radiograph results

This study aimed to develop a new simple and effective prognostic model using artificial intelligence (AI)-based chest radiograph (CXR) results to predict the outcomes of pneumonia. Patients aged > 18 years, admitted the treatment of pneumonia between March 2020 and August 2021 were included. We developed prognostic models, including an AI-based consolidation score in addition to the conventional CURB-65 (confusion, urea, respiratory rate, blood pressure, and age ≥ 65) and pneumonia severity index (PSI) for predicting pneumonia outcomes, defined as 30-day mortality during admission. A total of 489 patients, including 310 and 179 patients in training and test sets, were included. In the training set, the AI-based consolidation score on CXR was a significant variable for predicting the outcome (hazard ratio 1.016, 95% confidence interval [CI] 1.001–1.031). The model that combined CURB-65, initial O2 requirement, intubation, and the AI-based consolidation score showed a significantly high C-index of 0.692 (95% CI 0.628–0.757) compared to other models. In the test set, this model also demonstrated a significantly high C-index of 0.726 (95% CI 0.644–0.809) compared to the conventional CURB-65 and PSI (p < 0.001 and 0.017, respectively). Therefore, a new prognostic model incorporating AI-based CXR results along with traditional pneumonia severity score could be a simple and useful tool for predicting pneumonia outcomes in clinical practice.

CT findings as predictive factors for treatment failure in Mycobacterium abscessus complex lung disease: a retrospective cohort study

PurposeMycobacterium abscessus complex (MABC) commonly causes lung disease (LD) and has a high treatment failure rate of around 50%. In this study, our objective is to investigate specific CT patterns for predicting treatment prognosis and monitoring treatment response, thus providing valuable insights for clinical physicians in the management of MABC-LD treatment.MethodsWe retrospectively assessed 34 patients with MABC-LD treated between January 2015 and December 2020. CT scores for bronchiectasis, cellular bronchiolitis, consolidation, cavities, and nodules were measured at initiation and after treatment. The ability of the CT scores to predict treatment outcomes was analyzed in logistic regression analyses.ResultsThe CT scoring system had excellent inter-reader agreement (all intraclass correlation coefficients, > 0.82). The treatment failure (TF) group (17/34; 50%) had higher cavitation diameter (p = 0.049) and extension (p = 0.041) at initial CT and higher cavitation diameter (p = 0.049) and extension (p =0 .045), consolidation (p = 0.022), and total (p = 0.013) scores at follow-up CT than the treatment success (TS) group. The changes of total score and consolidation score (p = 0.049 and 0.024, respectively) increased in the TF group more than the TS group between the initial and follow-up CT. Multivariable logistic regression analysis showed initial cavitation extension, follow-up consolidation extension, and change in consolidation extension (adjusted odds ratio: 2.512, 2.495, and 9.094, respectively, per 1-point increase; all p < 0.05) were significant predictors of treatment failure.ConclusionsA high pre-treatment cavitation extension score and an increase in the consolidation extension score during treatment on CT could be alarm signs of treatment failure requiring tailor the treatment of MABC-LD carefully.

DECAF score at admission as a tool to predict clinical outcome in acute exacerbation of COPD

Background: The Dyspnea, Eosinopenia, Consolidation, Acidemia, and Atrial Fibrillation (DECAF) score at presentation is designed to predict the risk of death in patients with chronic obstructive pulmonary disease (COPD). Aims and Objectives: To study the DECAF score at admission to predict the clinical outcome of the patients during hospitalization for acute exacerbation of COPD (AE-COPD). Materials and Methods: The study was conducted using a prospective cross-sectional observational study design in a tertiary care center in South India from April 2022 to March 2023. Patients were recruited based on specific inclusion and exclusion criteria. The data corresponding to the five variables of the DECAF score was obtained, and the relation to outcome measures such as survival, ventilation, and duration of stay was measured. Results: Two hundred consecutive patients were assessed. Based on the DECAF score, 102 patients (51%) were classified as low-risk, and this group had no mortalities. In the intermediate-risk group, the mortality rate was 7.4%; in the high-risk group, the observed mortality rate was 38.6%. The differences noted were significant statistically. Higher dyspnea grade as measured by extended Modified Research Council criteria was related to DECAF score was significant and with the outcome. Conclusion: Our study shows that the DECAF score at the initial presentation can be used as a reliable tool to predict the outcome of AE-COPD. Dyspnea grading can be used to predict mortality indirectly.

Clinical validation of the Air-Test for the non-invasive detection of perioperative atelectasis in children.

The incidence of anesthesia-induced atelectasis in children is high and closely related to episodes of hypoxemia. The Air-Test is a simple maneuver to detect lung collapse. By a step-reduction in FiO<inf>2</inf> to 0.21, a fall in pulse-oximetry hemoglobin saturation <97% unmasks the presence of collapse-related shunt in healthy lungs. The aim of this study was to validate the Air-Test as a diagnostic tool to detect perioperative atelectasis in children using lung ultrasound as a reference. We first assessed the Air-Test in a retrospective cohort of 88 anesthetized children (Retrospective study) followed by a prospective study performed in 72 children (45 postconceptional weeks to 16 years old) using a similar protocol (Validation study). We analyzed the performance of the Air-Test to detect atelectasis by an operating characteristic curve (ROC) analysis, using lung ultrasound consolidation score as reference. Preoperative SpO<inf>2</inf> was normal in both studies (retrospective 98.7±0.6%, validation 99.0±0.9%). The Air-Test, with a SpO<inf>2</inf> cut point <97%, resulted positive in 67 patients in the retrospective study (SpO<inf>2</inf> 93.3±2.1%) and in 59 in the validation study (SpO<inf>2</inf> 94.9±1.8%); both P<0.0001. In the validation study, the Air-Test showed a sensitivity of 0.91 (95% CI 0.85-0.92), specificity of 1.00 (95% CI 0.84-1) and an area under the curve (AUC) of 0.98 (95% CI 0.97-1.00). AUC between both studies was similar (P=0.16). The Air-Test is a noninvasive and accurate method to detect atelectasis in healthy anesthetized children. It can be used as a screening tool to individualize patients that can benefit from lung recruitment maneuvers.

An International Validation of the "DECAF Score" to Predict Disease Severity and Hospital Mortality in Acute Exacerbation of COPD in the UAE.

The DECAF score (the Dyspnea, Eosinopenia, Consolidation, Academia, and Atrial fibrillation score) has been adopted in some hospitals to predict the severity of Acute Exacerbation of Chronic Obstructive Pulmonary Disease (AECOPD). However, DECAF score has not been widely evaluated or used in Middle Eastern countries. The present study aimed to validate the DECAF score for predicting in-hospital mortality in patients with AECOPD in the United Arab Emirates (UAE). This was a retrospective, observational study conducted in 19 hospitals in the UAE. Data were retrieved from the electronic records of patients admitted for AECOPD in 17 hospitals across the country. Patients aged more than 35 years who were diagnosed with AECOPD were included in the study. The validation of the DECAF Score for inpatient death, 30-days death, and 90-day readmission was conducted using the Area Under the Receiver Operator curve (AUROC). The AUROCDECAF curves for inpatient death, 30-days death, and 90-day readmission were 0.8 (95% CI: 0.8-0.9), 0.8 (95% CI: 0.7-0.8), and 0.8 (95% CI: 0.8-0.8), respectively. The model was a satisfactory fit to the data (Hosmer-Lemeshow statistic = 0.195, Nagelkerke R2 = 31.7%). There were significant differences in means of length of stay across patients with different DECAF score (P = .008). Patients with a DECAF score of 6 had the highest mean length of stay, which was 29.8 ± 31.4 days. Patients with a DECAF score of 0 had the lowest mean length of stay, which was 3.6 ± 2.0 days. The DECAF score is a strong predictive tool for inpatient death, 30 days mortality and 90-day readmission in UAE hospital settings. The DECAF score is an effective tool for predicating mortality and other disease outcomes in patients with AECOPD in the UAE; hence, clinicians would be more empowered to make appropriate clinical decisions by using the DECAF score.

Sleep Stage Transitions and Sleep-Dependent Memory Consolidation in Children with Narcolepsy-Cataplexy.

Electroencephalographic sleep stage transitions and altered first REM sleep period transitions have been identified as biomarkers of type 1 narcolepsy in adults, but not in children. Studies on memory complaints in narcolepsy have not yet investigated sleep-dependent memory consolidation. We aimed to explore stage transitions; more specifically altered REM sleep transition and its relationship with sleep-dependent memory consolidation in children with narcolepsy. Twenty-one children with narcolepsy-cataplexy and twenty-three healthy control children completed overnight polysomnography and sleep-dependent memory consolidation tests. Overnight transition rates (number of transitions per hour), global relative transition frequencies (number of transitions between a stage and all other stages/total number of transitions × 100), overnight transitions to REM sleep (transition from a given stage to REM/total REM transitions × 100), and altered first REM sleep period transitions (transitions from wake or N1 to the first REM period) were computed. Narcoleptic children had a significantly higher overnight transition rate with a higher global relative transition frequencies to wake. A lower sleep-dependent memory consolidation score found in children with narcolepsy was associated with a higher overnight transition frequency. As observed in narcoleptic adults, 90.48% of narcoleptic children exhibited an altered first REM sleep transition. As in adults, the altered sleep stage transition is also present in children with narcolepsy-cataplexy, and a higher transition rate could have an impact on sleep-dependent memory consolidation. These potential biomarkers could help diagnose type 1 narcolepsy in children more quickly; however, further studies with larger cohorts, including of those with type 2 narcolepsy and hypersomnia, are needed.

Clinical Implication and Prognostic Value of Artificial-Intelligence-Based Results of Chest Radiographs for Assessing Clinical Outcomes of COVID-19 Patients.

This study aimed to investigate the clinical implications and prognostic value of artificial intelligence (AI)-based results for chest radiographs (CXR) in coronavirus disease 2019 (COVID-19) patients. Patients who were admitted due to COVID-19 from September 2021 to March 2022 were retrospectively included. A commercial AI-based software was used to assess CXR data for consolidation and pleural effusion scores. Clinical data, including laboratory results, were analyzed for possible prognostic factors. Total O2 supply period, the last SpO2 result, and deterioration were evaluated as prognostic indicators of treatment outcome. Generalized linear mixed model and regression tests were used to examine the prognostic value of CXR results. Among a total of 228 patients (mean 59.9 ± 18.8 years old), consolidation scores had a significant association with erythrocyte sedimentation rate and C-reactive protein changes, and initial consolidation scores were associated with the last SpO2 result (estimate -0.018, p = 0.024). All consolidation scores during admission showed significant association with the total O2 supply period and the last SpO2 result. Early changing degree of consolidation score showed an association with deterioration (odds ratio 1.017, 95% confidence interval 1.005-1.03). In conclusion, AI-based CXR results for consolidation have potential prognostic value for predicting treatment outcomes in COVID-19 patients.

Effect of Tricalcium Phosphate on Healing of Non-Unions: An Observational Study of over 400 Non-Unions.

A central aspect of the treatment of non-unions is the filling of bone defects. The quantity of available autologous bone for this purpose is limited. Alternatively, or additionally, bone substitutes may be used. The aim of this retrospective, single-center study including 404 non-unions in 393 patients is to investigate the effect of tricalcium phosphate (TCP) on the healing of non-unions. Furthermore, the influence of gender, age, smoking status, comorbidities, type of surgical procedure, presence of infection, and length of treatment was investigated. We evaluated three groups of patients. Group 1 received TCP + BG, group 2 received BG alone and group 3 received no augmentation. Bone stability was assessed 1 and 2 years after non-union revision surgery through analysis of radiographs using the Lane Sandhu Score. Scores ≥3 were rated as stable Other influencing factors were collected from the electronic medical record. In 224 non-unions, bone defects were filled with autologous bone and TCP (TCP+BG). In 137 non-unions, bone defects were filled with autologous bone (BG), and in 43 non-unions presenting non-relevant defects, neither autologous bone nor TCP were used (NBG). After 2 years, 72.7% of the TCP+BG patients, 90.1% of the BG patients and 84.4% of the NBG patients achieved a consolidation score ≥3. Advanced age, presence of comorbidities and longer treatment period had a significantly negative effect on consolidation 1 year after surgery. Longer treatment periods also showed a negative significant effect after 2 years. It is notable that larger defects, mainly treated with the combination of autologous bone and TCP, showed similar healing rates to that of smaller defects after 2 years. The combination of TCP and autologous bone-grafts shows good results in the reconstruction of complicated bone-defects, but patience is required since the healing period exceeds 1 year in most patients.

Effect of ultrasound-guided lung recruitment manoeuvre on perioperative atelectasis during laparoscopy in young infants: A randomised controlled trial

BackgroundPneumoperitoneum is a risk factor for perioperative atelectasis in infants. This research aimed to investigate whether lung recruitment manoeuvres guided by ultrasound are more effective for young infants (<3 months) during laparoscopy under general anaesthesia. MethodsYoung infants (<3 months) undergoing general anaesthesia during laparoscopic surgery (>2 h) were randomised to either conventional lung recruitment (control group) or ultrasound-guided lung recruitment (ultrasound group) once per hour. Mechanical ventilation was started with a tidal volume of 8 mL·kg−1, positive end-expiratory pressure of 6 cm H2O and 40% inspired oxygen fraction. Lung ultrasound (LUS) was performed four times (T1 was performed 5 min after intubation and before pneumoperitoneum set, T2 was performed after pneumoperitoneum, T3 was performed 1 min after surgery, and T4 was performed before being discharged from post-anaesthesia care unit [PACU]) in each infant. The primary outcome was the incidence of significant atelectasis at T3 and T4 (defined by LUS consolidation score ≥ 2 in any region). Results62 babies were enrolled in the experiment and 60 infants were included in the analysis. Before the recruitment, atelectasis was similar between infants randomised to the control or ultrasound group at T1 (83.3% vs 80.0%; P = 0.500) and T2 (83,3% vs 76.7%; P = 0.519). The incidence of atelectasis at T3 and T4 were lower in the ultrasound group (26.7% and 33.3%), compared with infants randomised to conventional lung recruitment (66.7% and 70%) (P = 0.002; P = 0.004; respectively). ConclusionsUltrasound-guided alveolar recruitment reduced the perioperative incidence of atelectasis in infants <3 months during laparoscopy under general anaesthesia.

Comparison of two scores for short-term outcomes in patients with COPD exacerbation in the emergency department: the Ottawa COPD Risk Scale and the DECAF score.

While clinical decision rules have been developed to evaluate exacerbations and decisions on hospitalisation and discharge in emergency departments (EDs) in patients with chronic obstructive pulmonary disease (COPD), these rules are not widely used in EDs. In this study, we compare the predictive efficacy of the Ottawa Chronic Obstructive Pulmonary Disease Risk Scale (OCRS) and the Dyspnea, Eosinopenia, Consolidation, Acidemia, and Atrial Fibrillation (DECAF) score in estimating the short-term poor outcome of patients in our ED with exacerbations of COPD. This single-centre prospective observational study was conducted over 6 months. Patients with acute exacerbations of COPD admitted to the ED during the study period were included in the study. A poor outcome was defined as any of the following: readmission and requiring hospitalisation within 14 days of discharge, requiring mechanical ventilation on the first admission, hospitalisation for longer than 14 days on the first admission, or death within 30 days. The sensitivity and specificity of the OCRS and the DECAF score for a poor outcome and for mortality were calculated. Of the 385 patients who participated in the study, 85 were excluded based on the exclusion criteria. 66% of the patients were male, and the mean age was 70.15±10.36 years. A total of 20.7% of all patients (n=62) experienced poor outcomes. The sensitivity of an OCRS score <1 for predicting a poor outcome in patients was 96.8% (95% CI 88.8-99.6%) and the specificity was 18.5% (95% CI 13.8-24.0%). The sensitivity and specificity of an OCRS score <2 were 83.3% (95% CI 35.9-99.6%) and 65.5% (95% CI 59.6-70.7%), respectively. The sensitivity and specificity of a DECAF score <1 were 88.7% (95% CI 78.1-95.3%) and 34.5% (95% CI 28.4-40.9%), respectively. When the DECAF score was <2, sensitivity and specificity were 69.3% (95% CI 56.4-80.4%) and 74.8% (95% CI 68.8-80.2%), respectively. Our physicians achieved high specificity but low sensitivity in predicting a poor outcome. The OCRS is the more sensitive of the two tools, while the DECAF score is more specific in predicting a poor outcome when all threshold values are evaluated. While both tools may results in unnecessary hospitalisation, they can reduce the incidence of hospital discharge of patients with exacerbations of COPD who will develop poor outcomes in the ED.

Effects of a Multimodal Approach Using Buprenorphine with/without Meloxicam on Food Intake, Body Weight, Nest Consolidating Behavior, Burrowing Behavior, and Gastrointestinal Tissues in Postoperative Male Mice.

Distress affects animal welfare and scientific data validity. There is a lack of reports on the effects of multimodal analgesic approaches in mice. In this study, under the hypothesis that a multimodal analgesic protocol using buprenorphine with meloxicam has analgesic effects, we evaluated the effects of a multimodal analgesic protocol using buprenorphine with meloxicam on the well-being of mice during analgesic administration by changing the dosage of meloxicam. A total of 42 Slc:ICR male mice were categorized into nonsurgical and surgical groups (7 mice per group) and treated with an anesthetic (isoflurane) and analgesics (buprenorphine ± meloxicam). Analgesics were administered for 48 h after treatment. Buprenorphine (subcutaneous; 0.1 mg/kg/8 h) and meloxicam (subcutaneous; 0, 2.5, or 5 mg/kg/24 h) were administered twice. Body weight, food intake, nest consolidation score, and latency to burrow were evaluated. A significant decrease in food intake was observed 24 h after treatment, while a significant increase was observed 48 h post-treatment in all groups. Body weight showed a decreasing trend but was not significantly reduced. Furthermore, stomach, duodenum, and jejunum tissues showed no morphological abnormalities. Significant differences in burrow diving scores and the latency to burrow were observed between some groups, but these were not regarded as a consequence of the surgery and/or the meloxicam dose. When buprenorphine and meloxicam were combined, administering up to 5 mg/kg/day of meloxicam for 48 h to male mice after abdominal surgery had no significant negative effects on any tested parameters. In conclusion, a multimodal analgesic protocol of buprenorphine with meloxicam is among the options for increasing well-being in mice following abdominal surgery.

Decaf Score in Predicting Prognosis of Acute Exacerbation of Copd in Patient Required Hospital and ICU Admission

Introduction: Exacerbation refers to deterioration of patient’s respiratory indications and requires a robust scoring tool for subjects suffering from Chronic Obstructive Pulmonary Disease (COPD) undergoing acute exacerbation. The Dyspnoea, Eosinopenia, Consolidation, Acidaemia, and atrial Fibrillation (DECAF) score can be utilized bedside and predicts in-hospital mortality using indices. The study aimed at assessing the prognostic standards (of duration of ICU stay, hospital stay and mortality) and the sensitivity and specificity of acute exacerbation of COPD patients based on DECAF score. Methods: This prospective study was carried out in a tertiary hospital with 84 patients between October 2016 to September 2018. On admission, DECAF score of all patients with acute exacerbation of COPD was noted and admitted to ICU. The mean duration of stay in ICU and hospital were compared. Various components of APACHE II, BAP 65, CURB 65 were also noted on admission. Results: Mean age of population was 68.29±11.80 with male predominance (68%). The study observed mortality in 6% of patients with mean ICU stay of 3.65±2.21 days and mean hospital stay of 6.45±3.28 days. For a score of 5 and 6 mean DECAF score could not be calculated as the mortality rate was 100%. ROC of DECAF score was 0.81 which was more than APACHE II (0.72) and BAP 65 (0.69) (p-value 0.07 and 0.056 suggested significance). Conclusion: The DECAF Score has been observed to be a stronger predictor for hospital mortality. Higher the DECAF score, higher is the in-hospital death rate. The DECAF score also helps in forecasting the duration of ICU stay and hospital stay.

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

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. 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. 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. 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.

QoS-aware and multi-objective virtual machine dynamic scheduling for big data centers in clouds

Efficient resource scheduling is one of the most critical issues for big data centers in clouds to provide continuous services for users. Many existing scheduling schemes based on tasks on virtual machine (VM), pursued either load balancing or migration cost under certain response time or energy efficiency, which cannot meet the true balance of the supply and demand between users and cloud providers. The paper focuses on the following multi-objective optimization problem: how to pay little migration cost as much as possible to keep system load balancing under meeting certain quality of service (QoS) via dynamic VM scheduling between limited physical nodes in a heterogeneous cloud cluster. To make these conflicting objectives coexist, a joint optimization function is designed for an overall evaluation on the basis of a load balancing estimation method, a migration cost estimation method and a QoS estimation method. To optimize the consolidation score, an array mapping and a tree crossover model are introduced, and an improved genetic algorithm (GA) based on them is proposed. Finally, empirical results based on Eucalyptus platform demonstrate the proposed scheme outperforms exiting VM scheduling models.

High-resolution computed tomography (HRCT) analysis in anti-synthase antibody syndrome with organizing pneumonia

ObjectiveThe organizing pneumonia (OP) pattern is the second most common finding in anti-synthase antibody syndrome (ASS), and nonspecific interstitial pneumonia (NSIP) is the most common finding. This study analysed the OP score changes by semiquantitative and quantitative analysis methods and the correlation between the high-resolution computed tomography (HRCT) indexes and the pulmonary function test parameters (PFTs) in ASS patients. MethodsData from ASS-OP patients admitted to the respiratory department of Ping Jin Hospital from October 2014 to June 2020 were retrospectively reviewed and analysed. ResultsFourteen ASS-OP patients were recruited for this study. (1) In method-1, the consolidation (CO) score and the mean lung attenuation (MA) of poorly aerated and fibrosis lung fields (MAfibrosis) (r=0.56, P=0.04), the ground-glass opacity (GGO) score and the MA of non-aerated lung fields (MAnonaerated) (r=−0.64, P=0.01), and the CO plus the GGO (CG) score and the MAnonaerated (r=−0.59, P=0.03) of the lung fields had liner correlations. In method-2, the GGO score to the MAnonaerated (r=−0.58, P=0.03), and the CG (r=−0.68, P=0.01) score to the MAnonaerated had liner correlations. The FVC% (r=0.68, P=0.01) and FEV1% (r=0.64, P=0.01) to the MAfibrosis had good linear correlations. (2) Compared to the values before treatment, the CO pattern score, volume and weight percentages of the extracted whole lung volume with attenuation values of the nonaerated area (Vnonated%, Wnonaerated%), the volume of poorly aerated and fibrosis lung tissue (Vfibrosis%, Wfibrosis%), the weight percentages of normal aerated lung (Wnormal%), and the MAfibrosis exhibited significant differences during the 3–6 month follow-up period. ConclusionThe GGO and CO scored by the semiquantitative or quantitative analysis methods was similar. The HRCT quantitative analysis parameters showed a good correlation with the PFTs in ASS-OP patients, can provide an accurate OP pattern interpretation, and may be used as a monitoring and therapeutic indicator for ASS-OP patients.

Construction and Verification of a Predictive Model for Risk Factors in Children With Severe Adenoviral Pneumonia.

ObjectiveTo construct and validate a predictive model for risk factors in children with severe adenoviral pneumonia based on chest low-dose CT imaging and clinical features.MethodsA total of 177 patients with adenoviral pneumonia who underwent low-dose CT examination were collected between January 2019 and August 2019. The assessment criteria for severe pneumonia were divided into mild group (N = 125) and severe group (N = 52). All cases divided into training cohort (N = 125) and validation cohort (N = 52). We constructed a prediction model by drawing a nomogram and verified the predictive efficacy of the model through the ROC curve, calibration curve and decision curve analysis.ResultsThe difference was statistically significant (P < 0.05) between the mild adenovirus pneumonia group and the severe adenovirus pneumonia group in gender, age, weight, body temperature, L/N ratio, LDH, ALT, AST, CK-MB, ADV DNA, bronchial inflation sign, emphysema, ground glass sign, bronchial wall thickening, bronchiectasis, pleural effusion, consolidation score, and lobular inflammation score. Multivariate logistic regression analysis showed that gender, LDH value, emphysema, consolidation score, and lobular inflammation score were severe independent risk factors for adenovirus pneumonia in children. Logistic regression was employed to construct clinical model, imaging semantic feature model, and combined model. The AUC values of the training sets of the three models were 0.85 (0.77–0.94), 0.83 (0.75–0.91), and 0.91 (0.85–0.97). The AUC of the validation set was 0.77 (0.64–0.91), 0.83 (0.71–0.94), and 0.85 (0.73–0.96), respectively. The calibration curve fit good of the three models. The clinical decision curve analysis demonstrates the clinical application value of the nomogram prediction model.ConclusionThe prediction model based on chest low-dose CT image characteristics and clinical characteristics has relatively clear predictive value in distinguishing mild adenovirus pneumonia from severe adenovirus pneumonia in children and might provide a new method for early clinical prediction of the outcome of adenovirus pneumonia in children.

Clinical Outcome Discrimination in Pediatric ARDS by Chest Radiograph Severity Scoring.

Background There is no accurate radiological measurement to estimate the severity of pediatrics acute respiratory distress syndrome (PARDS). We validated the effectiveness of an adult radiographic assessment of lung edema (RALE) score in PARDS. Aim To assess the severity and prognosis of PARDS based on a chest radiograph (CXR) RALE scoring method. Methods Pediatric Acute Lung Injury Consensus Conference (PALICC) criteria were used to diagnose PARDS. General demographics, pulmonary complications, and 28‐day mortality of the patients were recorded. Subgroups were compared by prognosis (survive and death) and etiology (infection and noninfection). Two observers calculated RALE independently. Each quadrant of CXR was scored by consolidation scores 0 (none alveolar opacity), 1 (extent <25%), 2 (extent 25%–50%), 3 (50%–75%), and 4 (>75%) and density scores 1 (hazy), 2 (moderate), and 3 (dense). Quadrant score equals consolidation score times density score. Total score equals to the sum of four quadrants scores. The ROC curve and survival curve were established, and the optimal cutoff score for discrimination prognosis was set. Results 116 PARDS (72 boys and 44 girls) and 463 CXRs were enrolled. The median age was 25 months (5 months, 60.8 months) and with a mortality of 37.9% (44/116). The agreement between two independent observers was excellent (ICC = 0.98, 95% CI: 0.97–0.99). Day 3 score was independently associated with better survival (p < 0.001). The area under the curve of ROC was 0.773 (95% CI: 0.709–0.838). The cutoff score was 21 (sensitivity 71.7%, specificity 76.5%), and the hazard ratio (HR) was 9.268 (95% CI: 1.257–68.320). The pulmonary complication showed an HR of 3.678 (95% CI: 1.174–11.521) for the discrimination. Conclusion CXR RALE score can be used in PARDS for discriminating the prognosis and has a better agreement among radiologist and pediatrician. PARDS with pulmonary complications, day 3 score whether greater than 21 points, have a better predictive effectiveness.