Be realistic in the conclusion. Perform a careful spell and language check , especially if you are not writing in your native language. Avoid or minimize abbreviations. Readers can feel frustrated when they have to go back to remember what an abbreviation stands for e. Get feedback from your coauthors, mentor, and colleagues outside your team. The goal is to use their help to identify unclear sentences and missing or inaccurate information, as well as to make sure that the writing is high quality.
They can also help you to make sure that the title, objectives, methods, results, and conclusion are all aligned with the research question. Do NOT wait until the last minute to write and proofread the content. Writing and reviewing the abstract for quality always takes more time than you initially thought it would.
Moreover, glitches in the submission process are always possible, so you want to give yourself time to contact the conference staff for help, if necessary. The ventilator compatible version of the device can generate NO from ambient air on demand for delivery to the lungs at concentrations ranging from 1 part per million ppm to 80 ppm. COVID, bronchiolitis and chronic, refractory lung infections in the home setting e.
With the elimination of cylinders, Beyond Air intends to offer NO treatment in the home setting. Beyond Air is not suggesting NO use over 80 ppm or use at home. About Bronchiolitis The majority of hospital admissions of infants with bronchiolitis are caused by respiratory syncytial virus RSV.
RSV is a common and highly transmissible virus that infects the respiratory tract of most children before their second birthday. While most infants with RSV present with minor respiratory symptoms, a small percentage develop serious lower airway infections, termed bronchiolitis, which can become life-threatening.
The absence of treatment options for bronchiolitis limits the care of these sick infants to largely supportive measures. About Acute Viral Pneumonia In adults, viruses have been identified as the causative agents in approximately million cases of community-acquired pneumonia per year. Five of these were volume-time curves curves 1—4 and 12 , and 4 of these were flow-time curves curves 2, 8, 9, and In addition to these standard curves, we also selected 6 flow-time curves obtained with subjects: one volunteer, 3 subjects with stage IV COPD, and 2 subjects with restrictive lung disease Fig.
Flow, time, and integrated volume signals were recorded at a sampling rate of Hz, saved in an Excel sheet, and subsequently downloaded on the Hans Rudolph simulator. Human flow-volume curves used with the flow-volume simulator. For the sake of clarity, only one COPD curve is represented. This setup allowed us to mimic human conditions without exceeding 2 min between each of the different maneuvers.
The readings provided by the different spirometers with the 3-L syringe at 3 different flows were individually compared with the expected values. To investigate repeatability, we computed the span between the maximum and minimum values for the 3 variables in each of the 15 curves. The average is the mean of 3 successive maneuvers. The accuracy of the spirometers was assessed in different ways. The average is the mean of 3 successive maneuvers, and the standard is the value of the standard ATS curve.
We took the average of 3 measurements for each parameter for the Bland-Altman analysis. We calculated the bias, which was defined as the mean difference between the volume or flow measured by a spirometer and the volume or flow generated by the simulator virtually the target value of the ATS and subject curves for each curve and each spirometer.
The bias or mean difference between the spirometers and the Hans Rudolph simulator was calculated separately for the ATS and subject curves. A positive bias means that, on average, the tested spirometer overestimates the measurements with respect to the simulator and vice versa.
Table 3 presents the volumes measured by the different spirometers after injection of 3 L of air with the calibration syringe at different flows under ambient conditions. Volume measurements were slightly affected by air flow but remained within the calibration limits of 3.
Figure 2 shows the resistance values of each spirometer for different flows. Resistance increased with flow except for the PocketSpiro, which uses a variable orifice membrane sensor. The MicroLoop presented a resistance exceeding 1. Resistance of the spirometers in relation to flow.
The results of the 9 ATS and 6 subject curves were analyzed separately. In fact, almost all spirometers had a significant bias, so they have a tendency to overestimate or to underestimate the values. The subject curves in BTPS are also represented. The dashed line shows the bias or mean difference calculated for both ATS and subject curves. A large difference in bias appeared to exist between the ATS curves and the subject curves, with the biases of the ATS curves remaining more within acceptable limits.
Moreover, the biases of the curves originating from subjects with COPD exceeded those originating from healthy subjects and subjects with restrictive disorders, as illustrated with the Bland-Altman plot see Fig. The arrow indicates a FVC value largely out of range. In this study, an independent test of 5 office spirometers using a validated flow-volume simulator revealed significant accuracy issues with some devices under BTPS conditions. Moreover, we highlighted some important disagreements in volumes and flows between the simulator and the office spirometers, which became apparent with curves obtained from subjects with severe COPD but remained unnoticed with the currently recommended ATS curves.
This study has some limitations that have to be addressed before any further discussion and contextualization of the data. First, we tested only one device for each model of spirometer, except for the MicroLoop, for which we requested another flow sensor to double-check the unexpected high resistance.
Future studies could answer this question by testing several spirometers instead of only one. We followed scrupulously the recommendations of the manufacturers in performing a true calibration of the devices that require it and only a calibration check if this was recommended or feasible, mimicking real-life conditions as much as possible.
Another limitation is that we did not update the software of the devices during the course of the study; the new devices that reached the market after the start of the study were not included.
The 9 selected curves were among the most complex and extreme curves found in the ATS set. If our data are not ideally suited to make true comparisons between office spirometers, they are still exploitable from a methodological point of view because the spirometers were tested with a sample of curves representing patients currently seen in daily practice, in addition to the recommended ATS curves. Admittedly, it might have been interesting to extend the present observations to a wider range of subject curves.
Indeed, the characteristics of the curves obtained from our subjects with COPD were similar to each other in terms of FEV 1 , precluding any generalization of our conclusions. Nevertheless, with only 3 COPD subjects randomly selected from a database of an out-patient clinic, we identified problems in 3 spirometers, which were partly or completely overlooked with the conventional ATS curves.
We observed that both the simulator and the spirometers provided highly reproducible results and that the calibration check with the 3-L syringe remained within the expected limits. Conversely, none of the devices tested was perfect in terms of accuracy for volumes and flows during a forced expiratory maneuver. To date, the company has discovered more than mitochondrial derived peptides and generated over 1, analogs.
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