Rapid breath analysis for acute respiratory distress syndrome diagnostics using a portable two-dimensional gas chromatography device.

Acute respiratory distress syndrome (ARDS) is the most severe form of acute lung injury, responsible for high mortality and long-term morbidity. As a dynamic syndrome with multiple etiologies, its timely diagnosis is difficult as is tracking the course of the syndrome. Therefore, there is a significant need for early, rapid detection and diagnosis as well as clinical trajectory monitoring of ARDS. Here, we report our work on using human breath to differentiate ARDS and non-ARDS causes of respiratory failure. A fully automated portable 2-dimensional gas chromatography device with high peak capacity (> 200 at the resolution of 1), high sensitivity (sub-ppb), and rapid analysis capability (~ 30 min) was designed and made in-house for on-site analysis of patients' breath. A total of 85 breath samples from 48 ARDS patients and controls were collected. Ninety-seven elution peaks were separated and detected in 13 min. An algorithm based on machine learning, principal component analysis (PCA), and linear discriminant analysis (LDA) was developed. As compared to the adjudications done by physicians based on the Berlin criteria, our device and algorithm achieved an overall accuracy of 87.1% with 94.1% positive predictive value and 82.4% negative predictive value. The high overall accuracy and high positive predicative value suggest that the breath analysis method can accurately diagnose ARDS. The ability to continuously and non-invasively monitor exhaled breath for early diagnosis, disease trajectory tracking, and outcome prediction monitoring of ARDS may have a significant impact on changing practice and improving patient outcomes. Graphical abstract.

Few-Layer MoS2 Photodetector Arrays for Ultrasensitive On-Chip Enzymatic Colorimetric Analysis.

Enzymatic colorimetric analysis of metabolites provides signatures of energy conversion and biosynthesis associated with disease onsets and progressions. Miniaturized photodetectors based on emerging two-dimensional transition metal dichalcogenides (TMDCs) promise to advance point-of-care diagnosis employing highly sensitive enzymatic colorimetric detection. Reducing diagnosis costs requires a batched multisample assay. The construction of few-layer TMDC photodetector arrays with consistent performance is imperative to realize optical signal detection for a miniature batched multisample enzymatic colorimetric assay. However, few studies have promoted an optical reader with TMDC photodetector arrays for on-chip operation. Here, we constructed 4 × 4 pixel arrays of miniaturized molybdenum disulfide (MoS2) photodetectors and integrated them with microfluidic enzyme reaction chambers to create an optoelectronic biosensor chip device. The fabricated device allowed us to achieve arrayed on-chip enzymatic colorimetric detection of d-lactate, a blood biomarker signifying the bacterial translocation from the intestine, with a limit of detection that is 1000-fold smaller than the clinical baseline, a 10 min assay time, high selectivity, and reasonably small variability across the entire arrays. The enzyme (Ez)/MoS2 optoelectronic biosensor unit consistently detected d-lactate in clinically important biofluids, such as saliva, urine, plasma, and serum of swine and humans with a wide detection range (10-3-103 µg/mL). Furthermore, the biosensor enabled us to show that high serum d-lactate levels are associated with the symptoms of systemic infection and inflammation. The lensless, optical waveguide-free device architecture should readily facilitate development of a monolithically integrated hand-held module for timely, cost-effective diagnosis of metabolic disorders in near-patient settings.

Resonance Raman Spectroscopy Derived Tissue Hemoglobin Oxygen Saturation in Critically Ill and Injured Patients.

BACKGROUND: In this study, we examined the ability of resonance Raman spectroscopy to measure tissue hemoglobin oxygenation (R-StO2) noninvasively in critically ill patients and compared its performance with conventional central venous hemoglobin oxygen saturation (ScvO2). METHODS: Critically ill patients (n = 138) with an indwelling central venous or pulmonary artery catheter in place were consented and recruited. R-StO2 measurements were obtained by placing a sensor inside the mouth on the buccal mucosa. R-StO2 was measured continuously for 5 min. Blood samples were drawn from the distal port of the indwelling central venous catheter or proximal port of the pulmonary artery catheter at the end of the test period to measure ScvO2 using standard co-oximetry analyzer. A regression algorithm was used to calculate the R-StO2 based on the observed spectra. RESULTS: Mean (SD) of pooled R-StO2 and ScvO2 were 64(7.6) % and 65(9.2) % respectively. A paired t test showed no significant difference between R-StO2 and ScvO2 with a mean(SD) difference of -1(7.5) % (95% CI: -2.2, 0.3%) with a Clarke Error Grid demonstrating 84.8% of the data residing within the accurate and acceptable grids. Area under the receiver operator curve for R-StO2's was 0.8(0.029) (95% CI: 0.7, 0.9 P < 0.0001) at different thresholds of ScvO2 (≤60%, ≤65%, and ≤70%). Clinical adjudication by five clinicians to assess the utility of R-StO2 and ScvO2 yielded Fleiss' Kappa agreement of 0.45 (P < 0.00001). CONCLUSIONS: R-StO2 has the potential to predict ScvO2 with high precision and might serve as a faster, safer, and noninvasive surrogate to these measures.

Dynamic Limb Bioimpedance and Inferior Vena Cava Ultrasound in Patients Undergoing Hemodialysis.

Assessment of volume status in critically ill patients poses a challenge to clinicians. Measuring changes in the inferior vena cava (IVC) diameter using ultrasound is becoming a standard tool to assess volume status. Ultrasound requires physicians with significant training and specialized expensive equipment. It would be of significant value to be able to obtain this measurement continuously without physician presence. We hypothesize that dynamic changes in limb's bioimpedance in response to respiration could be used to predict changes in IVC. Forty-six subjects were tested a hemodialysis session. Impedance was measured via electrodes placed on the arm. Simultaneously, the IVC diameter was assessed by ultrasound. Subjects were asked to breathe spontaneously and perform respiratory maneuvers using a respiratory training device. Impedance (dz) was determined and compared with change in IVC diameter (dIVC; r = 0.76, p < 0.0001). There was significant relationship between dz and dIVC (p< 0.0001). Receiver-operator curves for dz at thresholds of dIVC (20% to70%) demonstrated high predictive power with areas under the curves (0.87-0.99, p < 0.0001). This evaluation suggests that real-time dynamic changes in limb impedance are capable of tracking a wide range of dynamic dIVC. This technique might be a suitable surrogate for monitoring real-time changes in dIVC to assess intravascular volume status.