High red blood cell distribution width attenuates the effectiveness of Immune checkpoint inhibitor therapy: An exploratory study using a clinical data warehouse.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have improved outcomes in cancer treatment but are also associated with adverse events and financial burdens. Identifying accurate biomarkers is crucial for determining which patients are likely to benefit from ICIs. Current markers, such as PD-L1 expression and tumor mutation burden, exhibit limited predictive accuracy. This study utilizes a Clinical Data Warehouse (CDW) to explore the prognostic significance of novel blood-based factors, such as the neutrophil-to-lymphocyte ratio and red cell distribution width (RDW), to enhance the prediction of ICI therapy benefit. METHODS: This retrospective study utilized an exploratory cohort from the CDW that included a variety of cancers to explore factors associated with pembrolizumab treatment duration, validated in a non-small cell lung cancer (NSCLC) patient cohort from electronic medical records (EMR) and CDW. The CDW contained anonymized data on demographics, diagnoses, medications, and tests for cancer patients treated with ICIs between 2017-2022. Logistic regression identified factors predicting ≤2 or ≥5 pembrolizumab doses as proxies for progression-free survival (PFS), and Receiver Operating Characteristic analysis was used to examine their predictive ability. These factors were validated by correlating doses with PFS in the EMR cohort and re-testing their significance in the CDW cohort with other ICIs. This dual approach utilized the CDW for discovery and EMR/CDW cohorts for validating prognostic biomarkers before ICI treatment. RESULTS: A total of 609 cases (428 in the exploratory cohort and 181 in the validation cohort) from CDW and 44 cases from EMR were selected for study. CDW analysis revealed that elevated red cell distribution width (RDW) correlated with receiving ≤2 pembrolizumab doses (p = 0.0008), with an AUC of 0.60 for predicting treatment duration. RDW's correlation with PFS (r = 0.80, p<0.0001) and its weak association with RDW (r = -0.30, p = 0.049) were confirmed in the EMR cohort. RDW also remained significant in predicting short treatment duration across various ICIs (p = 0.0081). This dual methodology verified pretreatment RDW elevation as a prognostic biomarker for shortened ICI therapy. CONCLUSION: This study suggests the utility of CDWs in identifying prognostic biomarkers for ICI therapy in cancer treatment. Elevated RDW before treatment initiation emerged as a potential biomarker of shorter therapy duration.

Infection control for COVID-19 in hospital examination room.

Healthcare providers are vulnerable to infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) because of their close proximity to patients with coronavirus disease 2019. SARS-CoV-2 is mainly transmitted via direct and indirect contact with respiratory droplets, and its airborne transmission has also been identified. However, evidence for environmental factors is scarce, and evidence-based measures to minimize the risk of infection in clinical settings are insufficient. Using computational fluid dynamics, we simulated exhalation of large and small aerosol particles by patients in an otolaryngology examination room, where medical procedures require the removal of a face mask. The effects of coughing were analyzed, as well as those of humidity as a controllable environmental factor and of a suction device as an effective control method. Our results show that a suction device can minimize aerosol exposure of healthcare workers by efficiently removing both large (11.6-98.2%) and small (39.3-99.9%) aerosol particles. However, for coughing patients, the removal efficiency varies inversely with the particle size, and the humidity notably affects the aerosol behavior, indicating the need for countermeasures against smaller aerosols. Overall, these results highlight the potential and limitation of using a suction device to protect against SARS-CoV-2 and future respiratory infections.

Practical approach to prevent COVID-19 infection at breast cancer screening.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) undermines the benefits of cancer screening. To date, no study has identified specific infection control methods. We aimed to provide practical methods for COVID-19 risk reduction during breast cancer screening mammography (MMG) by examining an overview of potential contamination routes of aerosols and possible risks for patients and health care providers. METHODS: Computational fluid dynamics (CFD) simulations were conducted for airflow and aerosol dispersion in a 3D virtual model of a mobile MMG laboratory room. This model was constructed based on the actual mobile screening MMG bus 'Cosmos' in the Chiba Foundation for Health Promotion & Disease Prevention. Examiner and patient geometries were obtained by scanning an actual human using a 3D Scanner. Contamination of the room was evaluated by counting the numbers of suspended and deposited aerosols. RESULTS: We applied the CFD simulation model to the exhalation of small or large aerosols from a patient and examiner in the MMG laboratory. Only 14.5% and 54.5% of large and small aerosols, respectively, were discharged out of the room with two doors open. In contrast, the proportion of large and small aerosols discharged out of the room increased to 96.6% and 97.9%, respectively, with the addition of forced gentle wind by the blower fan. This simulation was verified by a mist aerosol experiment conducted in the mobile MMG laboratory. CONCLUSION: Adding forced ventilation to a MMG laboratory with two doors open may enable risk reduction dramatically. This could be applied to other clinical situations.

Visualizing the Flow Patterns in an Expanding and Contracting Pulmonary Alveolated Duct Based on Microcomputed Tomography Images.

We visualized the flow patterns in an alveolated duct model with breathing-like expanding and contracting wall motions using particle image velocimetry, and then, we investigated the effect of acinar deformation on the flow patterns. We reconstructed a compliant, scaled-up model of an alveolated duct from synchrotron microcomputed tomography images of a mammalian lung. The alveolated duct did not include any bifurcation, and its entire surface was covered with alveoli. We embedded the alveolated duct in a sealed container that was filled with fluid. We oscillated the fluid in the duct and container simultaneously and independently to control the flow and duct volume. We examined the flow patterns in alveoli, with the Reynolds number (Re) at 0.03 or 0.22 and the acinar volume change at 0%, 20%, or 80%. At the same Re, the heterogeneous deformation induced different inspiration and expiration flow patterns, and the recirculating regions in alveoli changed during respiratory cycle. During a larger acinar deformation at Re = 0.03, the flow patterns tended to change from recirculating flow to radial flow during inspiration and vice versa during expiration. Additionally, the alveolar geometric characteristics, particularly the angle between the alveolar duct and mouth, affected these differences in flow patterns. At Re = 0.22, recirculating flow patterns tended to form during inspiration and expiration, regardless of the magnitude of the acinar deformation. Our in vitro experiments suggest that the alveolated flows with nonself-similar and heterogeneous wall motions may promote particle mixing and deposition.