Investigating the relationship between peak inspiratory flow rate and volume of inhalation from a Diskus™ Inhaler and baseline spirometric parameters: a cross-sectional study

Drug delivery from a Dry Powder Inhaler (DPI) is dependent on the peak inspiratory flow rate (PIFR) generated. Currently available methods for estimating PIFR from most DPIs are limited and mainly rely on subjective assessment. We aim to show that spirometric and Diskus™ PIFR and Inspiratory Vital Capacity (IVC) are related to the underlying respiratory condition and that spirometric PIFR can be used to assess whether Diskus™ PIFR will be adequate when using this DPI. Healthy volunteers and patients with asthma, COPD, neuromuscular disease and non-respiratory disorders were recruited (n = 85). Demographics and baseline lung function by spirometry were recorded. Flow and volume readings were taken while patients used a Diskus™ DPI, housed in an airtight container connected to a spirometer. T-tests were performed to compare mean spirometric and Diskus™ PIFR/ IVC between groups. Stepwise regression analysis of Diskus™ PIFR versus spirometric PIFR, spirometric IVC, age, gender, condition, BMI, FEV1 and FVC was performed. The Diskus™ PIFR for the COPD and Neuromuscular Disease group was more than 10 L/min lower than the Healthy or Asthma groups (p \u3c 0.05). The mean spirometric and Diskus™ IVC of the Healthy group was significantly (\u3e0.75 L) higher than the mean for the other three groups (p \u3c 0.05). Diskus™ PIFR was moderately correlated with spirometric PIFR and age (Adjusted R2 = 0.58, p \u3c 0.0001). PIFR generated using a Diskus™ DPI is dependent on the underlying disease and age. A spirometric PIFR of less than 196 L/min should prompt further investigation into the suitability of a patient for a Diskus™ DPI, with possible consideration of alternate devices

Artificial Intelligence Enhances Diagnostic Flow Cytometry Workflow in the Detection of Minimal Residual Disease of Chronic Lymphocytic Leukemia

Flow cytometric (FC) immunophenotyping is critical but time-consuming in diagnosing minimal residual disease (MRD). We evaluated whether human-in-the-loop artificial intelligence (AI) could improve the efficiency of clinical laboratories in detecting MRD in chronic lymphocytic leukemia (CLL). We developed deep neural networks (DNN) that were trained on a 10-color CLL MRD panel from treated CLL patients, including DNN trained on the full cohort of 202 patients (F-DNN) and DNN trained on 138 patients with low-event cases (MRD < 1000 events) (L-DNN). A hybrid DNN approach was utilized, with F-DNN and L-DNN applied sequentially to cases. “Ground truth” classification of CLL MRD was confirmed by expert analysis. The hybrid DNN approach demonstrated an overall accuracy of 97.1% (95% CI: 84.7–99.9%) in an independent cohort of 34 unknown samples. When CLL cells were reported as a percentage of total white blood cells, there was excellent correlation between the DNN and expert analysis [r > 0.999; Passing–Bablok slope = 0.997 (95% CI: 0.988–0.999) and intercept = 0.001 (95% CI: 0.000–0.001)]. Gating time was dramatically reduced to 12 s/case by DNN from 15 min/case by the manual process. The proposed DNN demonstrated high accuracy in CLL MRD detection and significantly improved workflow efficiency. Additional clinical validation is needed before it can be fully integrated into the existing clinical laboratory practice

Trends in platelet distributions from 2008 to 2017: a survey of twelve national and regional blood collectors

Background: This multi-national study evaluated changes in platelet (PLT) unit distributions at 12 national or regional blood collectors over a 10-year period. Methods: Data on the total number of PLT distributions, the collection method, that is apheresis vs whole blood-derived (WBD), the PLT unit characteristics and post-collection modifications were obtained from 12 national or regional blood collectors from 2008 through 2017. Individual WBD PLT units were converted to apheresis equivalent units (i.e. a dose of PLTs) by dividing by 4, the typical pool size; WBD units that were pooled before distribution were counted as a single dose. Results: Overall at these 12 blood collectors, the total number of PLTs distributed in 2008 was 1 373 200, which rose by 10·2% to 1 513 803 in 2017. The Japanese Red Cross, which distributes only apheresis PLTs, had a 13·4% increase in the number of distributions between the years 2008 and 2017, while the other 11 blood collectors combined demonstrated a 6·8% increase in distributions between these two years. Between the years 2008 and 2017, the changes in the proportion of apheresis, platelet-rich plasma and buffy coat PLT distributions were −29·9%, −70·7% and 80·0%, respectively. Conclusion: The number of PLT distributions increased during the 10-year study period despite prophylactic PLT transfusion thresholds having remained fairly consistent over the last decade. Perhaps this increase is in part driven by increased administration of platelets to patients with massive haemorrhage or an increase in stem cell transplantation. The use of buffy coat PLTs is increasing at these collectors