Xiao Feng Wang

Exhaled breath analysis with a colorimetric sensor array for the identification and characterization of lung cancer.

Introduction: The pattern of exhaled breath volatile organic compounds represents a metabolic biosignature with the potential to identify and characterize lung cancer. Breath biosignature-based classification of homogeneous subgroups of lung cancer may be more accurate than a global breath signature. Combining breath biosignatures with clinical risk factors may improve the accuracy of the signature. Objectives: To develop an exhaled breath biosignature of lung cancer using a colorimetric sensor array and to determine the accuracy of breath biosignatures of lung cancer characteristics with and without the inclusion of clinical risk factors. Methods: The exhaled breath of 229 study subjects, 92 with lung cancer and 137 controls, was drawn across a colorimetric sensor array. Logistic prediction models were developed and statistically validated based on the color changes of the sensor. Age, sex, smoking history, and chronic obstructive pulmonary disease were incorporated in the prediction models. Results: The validated prediction model of the combined breath and clinical biosignature was moderately accurate at distinguishing lung cancer from control subjects (C-statistic 0.811). The accuracy improved when the model focused on only one histology (C-statistic 0.825–0.890). Individuals with different histologies could be accurately distinguished from one another (C-statistic 0.864 for adenocarcinoma versus squamous cell carcinoma). Moderate accuracies were noted for validated breath biosignatures of stage and survival (C-statistic 0.785 and 0.693, respectively). Conclusions: A colorimetric sensor array is capable of identifying exhaled breath biosignatures of lung cancer. The accuracy of breath biosignatures can be optimized by evaluating specific histologies and incorporating clinical risk factors.

Metabolite Profiles of the Serum of Patients with Non–Small Cell Carcinoma

Introduction Alterations of serum metabolites may allow us to identify individuals with lung cancer and advance our understanding of the nature and treatment of their cancer. We aimed to identify serum metabolites that differentiate patients with lung cancer from at‐risk controls. Methods Serum samples from patients with biopsy‐confirmed untreated stage I through stage III non–small cell lung cancer and at‐risk controls were divided into fractions for analysis by ultrahigh‐performance liquid chromatography–tandem mass spectrometry and gas chromatography–mass spectrometry. Compounds were identified by comparison with library entries of purified standards. Differences in concentrations of single metabolites and metabolite ratios were identified. Prediction models were developed. Results Serum samples from 284 subjects was analyzed. The subjects mean age was 67 and 48% were female. Ninety‐four patients had lung cancer (50 had adenocarcinoma and 44 had squamous cell carcinoma), 44% had stage I disease, 17% had stage II disease, and 39% had stage III disease. The patients with cancer were slightly older than the controls (68.7 versus 66.2 years, p = 0.013). A total of 534 metabolites were identified in eight metabolite superpathways and 73 subpathways. The concentrations of 149 metabolites differed significantly (q values <0.05) between the cancer and control groups (70 were lower in the cancer group and 79 were higher), and 9723 metabolite ratios differed significantly (q values <0.001) between the cancer and control groups. The accuracies of the models (cancer and cancer subtypes versus control) trained on 70% of the subjects and tested on 30% (expressed as C‐statistics) ranged from 0.748 to 0.858. Conclusions Differences in the serum metabolite profile exist between patients with stage I through stage III non–small cell lung cancer and matched controls.

Popular on YouTube: a critical appraisal of the educational quality of information regarding asthma.

BACKGROUNDnAsthma affects >300 million people globally, including 25 million in the United States. Patients with asthma frequently use the Internet as a source of information. YouTube is one of the three most popular Web sites.nnnOBJECTIVEnTo determine the educational quality of YouTube videos for asthma.nnnMETHODSnWe performed a YouTube search by using the keyword asthma. The 200 most frequently viewed relevant videos were included in the study. Asthma videos were analyzed for characteristics, source, and content. Source was further classified as asthma health care provider, other health care provider, patient, pharmaceutical company, and professional society and/or media. A scoring system was created to evaluate quality (-10 to 30 points). Negative points were assigned for misleading information.nnnRESULTSnTwo hundred videos were analyzed, with a median of 18,073.5 views, 31.5 likes, and 2 dislikes, which spanned a median of 172 seconds. More video presenters were male (60.5%). The most common type of video source was other health care providers (34.5%). The most common video content was alternative treatments (38.0%), including live-fish ingestion; reflexology; acupressure and/or acupuncture; Ayurveda; yoga; raw food, vegan, gluten-free diets; marijuana; Buteyko breathing; and salt therapy. Scores for videos supplied by asthma health care providers were statistically significantly different from other sources (p < 0.001) and had the highest average score (9.91).nnnCONCLUSIONnYouTube videos of asthma were frequently viewed but were a poor source of accurate health care information. Videos by asthma health care providers were rated highest in quality. The allergy/immunology community has a clear opportunity to enhance the value of educational material on YouTube.

Association of impaired heart rate recovery with cardiopulmonary complications after lung cancer resection surgery.

OBJECTIVESnPatients who undergo lung resection surgery are at risk for postoperative morbidity and mortality. Appropriate selection of the surgical candidate is crucial in the treatment of lung cancer. Heart rate recovery is a measure of physical fitness. We aimed to investigate the association of impaired heart rate recovery with cardiopulmonary complications after lung resection surgery for treatment of lung cancer.nnnMETHODSnData from consecutive patients who, between 2009 and 2013, underwent heart rate recovery evaluation after 6-minute walk tests before lung resection surgery were retrospectively reviewed. Impaired heart rate recovery was defined as a 12-beat or less decrease in peak heart rate at 1 minute after the 6-minute walk test. Postoperative cardiopulmonary complications were as defined by the Society of Thoracic Surgeons General Thoracic Surgery Database. Logistic regression was performed, including previously known risk factors for postoperative complications after lung resection surgery.nnnRESULTSnA total of 96 patients had heart rate recovery evaluated within 6 months of lung resection surgery for treatment of lung cancer. Thirty-one patients had impaired heart rate recovery, 17 of whom (55%) had cardiopulmonary complications. A total of 65 patients had normal heart rate recovery, 17 of whom (26%) had cardiopulmonary complications. In multivariable logistic regression analysis, impaired heart rate recovery was significantly associated with postoperative cardiopulmonary complications (odds ratio, 4.97; confidence interval, 1.79-13.8; Pxa0=xa0.002). No patient died within 30 days after surgery.nnnCONCLUSIONSnImpaired heart rate recovery after the 6-minute walk test is associated with postoperative cardiopulmonary complications in patients who underwent lung resection surgery for treatment of lung cancer.

Epidemiology of anaphylaxis at a tertiary care center: A report of 730 cases

BACKGROUNDnRecent data reveal that the rate of anaphylaxis is increasing and suggest that idiopathic anaphylaxis may account for most of these cases.nnnOBJECTIVEnTo determine the pattern of anaphylaxis at a tertiary care referral center.nnnMETHODSnA retrospective electronic medical record review spanning 12 years (2002-2013) identified patients with anaphylaxis.nnnRESULTSnOf the 4,777 records reviewed, 730 patients met our anaphylaxis definition. Median age was 34.0 years; 72.7% were adults, 58.6% were female, and 86.8% were white. Median time to evaluation by an allergist was 8.8 months. Foods were the most common cause (29.9%), followed by Hymenoptera venom (24.6%), idiopathic anaphylaxis (13.7%), and medications (13.3%). The most common foods were peanuts (23.9%), tree nuts (21.6%), shellfish (16.1%), and egg and milk (both 10.1%). The most common cause of anaphylaxis in adults was Hymenoptera venom. The most frequent symptoms were urticaria and/or angioedema, reported in 84.7% of cases. Atopy was present in 43.8%. In 15.4% of cases, anaphylaxis was not the chief reason for the office visit.nnnCONCLUSIONnWe found food allergy was the most common overall cause of anaphylaxis, with peanut the most frequent food trigger. Idiopathic anaphylaxis was not the most common cause but accounted for 13.7% of all cases. Approximately 1 in 6 cases of anaphylaxis may be missed if a comprehensive evaluation is not performed.

Accuracy of volatile urine biomarkers for the detection and characterization of lung cancer

BackgroundThe mixture of volatile organic compounds in the headspace gas of urine may be able to distinguish lung cancer patients from relevant control populations.MethodsSubjects with biopsy confirmed untreated lung cancer, and others at risk for developing lung cancer, provided a urine sample. A colorimetric sensor array was exposed to the headspace gas of neat and pre-treated urine samples. Random forest models were trained from the sensor output of 70xa0% of the study subjects and were tested against the remaining 30xa0%. Models were developed to separate cancer and cancer subgroups from control, and to characterize the cancer. An additional model was developed on the largest clinical subgroup.Results90 subjects with lung cancer and 55 control subjects participated. The accuracies, reported as C-statistics, for models of cancer or cancer subgroups vs. control ranged from 0.795 – 0.917. A model of lung cancer vs. control built using only subjects from the largest available clinical subgroup (30 subjects) had a C-statistic of 0.970. Models developed and tested to characterize cancer histology, and to compare early to late stage cancer, had C-statistics of 0.849 and 0.922 respectively.ConclusionsThe colorimetric sensor array signature of volatile organic compounds in the urine headspace may be capable of distinguishing lung cancer patients from clinically relevant controls. The incorporation of clinical phenotypes into the development of this biomarker may optimize its accuracy.

Compliance with Procalcitonin Algorithm Antibiotic Recommendations for Patients in Medical Intensive Care Unit.

To describe compliance with antibiotic recommendations based on a previously published procalcitonin (PCT)‐guided algorithm in clinical practice, to compare PCT algorithm compliance rates between PCT assays ordered in the antibiotic initiation setting (PCT concentration measured less than 24 hours after antibiotic initiation or before antibiotic initiation) with those in the antibiotic continuation setting (PCT concentration measured 24 hours or more after antibiotic initiation), and to evaluate patient‐ and PCT‐related factors independently associated with algorithm compliance in patients in the medical intensive care unit (MICU).

Six-Minute Walk Test as a Predictor of Diagnosis, Disease Severity, and Clinical Outcomes in Scleroderma-Associated Pulmonary Hypertension: The DIBOSA Study

BackgroundPulmonary hypertension (PH) is a common complication of scleroderma (SSc) and is a leading cause of morbidity and mortality.ObjectivesTo explore the utility of the 6MWT in the prediction of SSc-PH and to assess its prognostic implications.MethodsA retrospective review of SSc patients from 2003 to 2013, with 6MWT and echocardiogram (nxa0=xa0286), was conducted. Presence of PH was defined by right heart catheterization. Patients were randomized into development and validation cohorts. Using regression techniques, we developed a scoring system to predict the presence of SSc-PH and tested it in our validation cohort. Trends of mortality and disease severity were studied for incremental scores.ResultsThe DIBOSA scoring system includes DIstance walked in 6xa0min, BOrg dyspnea index, and SAturation of oxygen at 6xa0min. The DIBOSA score in the development cohort ranged from 0 to 3, resulting in an area of 0.858 (Pxa0<xa00.0001) under the ROC curve. A score of 0 had a NPV of 100% and a score of 3 had a PPV of 86.58%. The validation cohort had an area under the ROC curve of 0.842. The DIBOSA score correlated with both pulmonary artery pressures and mortality. The 3-year survival rates for DIBOSA scores of 0, 1, 2, and 3 were 100, 100, 87.67, and 66.67%, respectively (HRxa0=xa03.92, Pxa0<xa00.0001).ConclusionsDIBOSA score is a sensitive tool for the prediction of SSc-PH. The DIBOSA score is a direct predictor of mortality in SSc-PH and strongly correlates with pulmonary pressures. 6MWT can be used to predict clinical outcomes in SSc-PH.

Interhospital transfers of the critically ill: Time spent at referring institutions influences survival

Objective: To determine if the length of stay at a referring institution intensive care unit (ICU) before transfer to a tertiary/quaternary care facility is a risk factor for mortality. Design: We performed a retrospective chart review of patients transferred to our ICU from referring institution ICUs over a 3‐year period. Logistical regression analysis was performed to determine which factors were independently associated with increased mortality. The primary outcomes were ICU and hospital mortality. Main results: A total of 1248 patients were included in our study. Length of stay at the referring institution was an independent risk factor for both ICU and hospital mortality (P < .0001), with increasing lengths of stay correlating with increased mortality. Each additional day at the referring institution was associated with a 1.04 increase in likelihood of ICU mortality (95% confidence interval, 1.02‐1.06; P =0.001) and a 1.029 (95% confidence interval, 1.01‐1.05; P .005) increase in likelihood of hospital mortality. Conclusions: Length of stay at the referring institution before transfer is a risk factor for worse outcomes, with longer stays associated with increased likelihood of mortality. Further studies delineating which factors most affect length of stay at referring institutions, though a difficult task, should be pursued.

Non-invasive positive pressure ventilation in lung transplant recipients with acute respiratory failure: Beyond the perioperative period

Purpose: The purpose of this study is to evaluate outcomes in MICU lung transplant recipients with acute respiratory failure treated with non‐invasive positive pressure ventilation (NPPV) and identify factors associated with NPPV failure (need for intubation). Methods: Retrospective chart review of all lung transplant recipients who were admitted with acute respiratory failure to the MICU from January 2009–August 2016 was completed. Logistic regression analysis was performed to determine which factors were independently associated with NPPV failure. Results: Of 156 patients included in the study, 125 (80.1%) were tried on NPPV. Sixty‐eight (54.4%) were managed successfully with NPPV with a hospital survival rate of 94.1%. Subjects who failed NPPV had higher hospital mortality, similar to those intubated from the outset (15 [48.3%]; 22 [38.6%], p = .37). In multivariate analyses, APACHE III scores >78 (9.717 [3.346, 28.22]) and PaO2/FiO2 ≤ 151 (4.54 [1.72, 11.99]) were associated with greater likelihood of NPPV failure. There was no difference in NPPV failure based on the presence of BOS. In patients with high severity of illness, there was no difference in mortality between initial IMV and NPPV failure when stratified on the basis of hypoxemia (PaO2/FiO2 > 151, p‐value 0.34; PaO2/FiO2 ≤ 151, p‐value 0.99). Conclusions: NPPV is a viable option for lung transplant recipients with acute respiratory failure. Extreme caution should be exercised when used in patients with high severity of illness (APACHE III >78) and/or severe hypoxemia (PaO2/FiO2 ≤ 151). HighlightsLung transplant recipients with acute respiratory failure are at high risk of death.NPPV is a viable option for lung transplant recipients with acute respiratory failure.NPPV should be used sparingly in lung transplant recipients on vasopressors, with high severity of illness (APACHE III score > 78) and/or severe hypoxemia (PaO2/FiO2 ≤ 151).