MétaCan
Menu
Retour à la cohorte
Enregistrement W3032990589 · doi:10.1111/cpf.12650

Lung function monitoring in the era of respiratory pandemics

2020· letter· en· W3032990589 sur OpenAlex

Pourquoi ce travail est dans la base

Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.

affAu moins un auteur déclare une institution canadienne dans l'instantané OpenAlex épinglé.
aboutLe titre ou le résumé porte un signal canadien du lexique géographique.

Notice bibliographique

RevueClinical Physiology and Functional Imaging · 2020
Typeletter
Langueen
DomaineMedicine
ThématiqueRespiratory Support and Mechanisms
Établissements canadiensUniversity of TorontoUniversity Health NetworkMcGill University
Organismes subventionnairesnon disponible
Mots-clésMedicineLung functionLungRespiratory systemPandemicIntensive care medicineCoronavirus disease 2019 (COVID-19)Internal medicineDisease

Résumé

récupéré en direct d'OpenAlex

Oscillometry has been used in adjunct with spirometry in many studies and in clinical practice. Recent events with the spread of a viral respiratory pandemic has caused many clinics to stop using standard spirometry for the fear of aerosol transmission of virus. With recent experiences of our and other groups using oscillometry demonstrating its sensitivity, precision, and ease of use without any forced maneuvers, we suggest that it could be an alternative to spirometry while minimizing exhalation aerosol generation. Coming on the heels of the SARS, MeRS and H1N1, the respiratory infections caused by the novel SARS-Cov-2 virus causing COVID-19 is remarkable for its scope, speed of infectivity, mortality and geographic spread. It has already overwhelmed the health care capacity of developing and developed countries alike due to the unprecedented need for intensive medical care. Countries have responded with virtual shut down of all but essential services as a means to limit spread of infection. These measures also include postponement of routine follow-up diagnostic assessments and medical visits for the overall population. Indeed, to free up capacity to care for of the anticipated onslaught of severe COVID-19, the Toronto Lung Transplant Program made an unprecedented decision on March 16, 2020 to suspend new lung transplants and elected to conduct virtual clinics for all postlung transplant patients with the exception of the few who require in-person visit and/or essential diagnostic investigations. The measures were taken to minimize risk of infection due to travel to health care facilities as these patients are immunocompromised however, these precautions also mean that routine diagnostic evaluations such as chest imaging, surveillance bronchoscopies and pulmonary function studies are also deferred. Indeed, since March 19, 2020, the pulmonary function laboratories at the Toronto teaching hospitals have been closed until further noticed, which is in accordance with recommendations from expert panels associated with the European Respiratory and the American Thoracic Societies (McCormack & Kaminsky, 2020; McGowan, Sylvester, & Burgos, 2020); While lung transplant patients can self-monitor pulmonary function with home spirometry (as it is part of the standard postlung transplant care), it is well recognized that home monitoring lacks the quality control of those performed in accredited pulmonary function laboratories. Moreover, in the face of respiratory epidemics and pandemics, how do we care for patients with common chronic lung diseases such as asthma and chronic obstructive lung disease where evaluation by pulmonary function tests is a cornerstone of management? Oscillometry has emerged as a useful diagnostic tool that has been shown to be highly sensitive to small airway and peripheral lung function (Eddy, Westcott, Maksym, Parraga, & Dandurand, 2019; Foy et al., 2019; Young, Guo, Eddy, Maksym, & Parraga, 2018). Our recent study in lung transplant patients showed that oscillometry outperformed spirometry in detecting physiologic changes associated with biopsy-proven rejection and improvement following treatment of rejection. In contrast, spirometry was stable or improving in 15 of the 16 episodes of acute rejection (Cho et al., 2020; Usmani, 2020). Oscillometry is very sensitive to alterations in the lung periphery in diseases such as asthma and COPD (Foy et al., 2019; Kuo, Jabbal, & Lipworth, 2019; Lundblad, Miletic, Piitulainen, & Wollmer, 2019; Lundblad, Siddiqui, Bossé, & Dandurand, 2019), a feature that likely could be extrapolated to infections as oscillometry is agnostic to the underlying disease but is specific to the physiologic changes in airway dimensions and lung stiffness, both of which are altered during pulmonary infections. Have respiratory infections been shown to be detectable by assessing lung mechanics? Indeed, yes! Over 40 years ago a report from Hall et al., 1976 (Hall et al., 1976) showed that pulmonary mechanics measured with oscillometry identified early signs of small airway disease (SAD) in patients infected with H3N2 influenza and that it tracked worsening and improvement of SAD as patients were followed for 5 weeks until resolution when oscillometry normalized in most patients. During the entire period, spirometry did not change significantly (Hall et al., 1976), similar to our transplant study. All patients had an uncomplicated influenza that did not require hospitalization and recovered fully, yet oscillometry was sensitive enough to detect SAD. In a study of pigs infected with porcine reproductive and respiratory syndrome virus, oscillometry revealed peripheral airway obstruction and reduced lung compliance. The physiology changes correlated with histopathological interstitial pneumonia providing a link between structure and function (Wagner et al., 2011). This link was also illustrated in recent work using magnetic resonance imaging in patients with COPD and asthma where a significant correlation between ventilation defects, oscillometry parameters and quality of life scores were found, providing clinical functional correlations to the structure-physiologic function link (Eddy et al., 2019; Foy et al., 2019; Young et al., 2018). The human studies from 1976 were methodologically challenging due to technological limitations necessitating manual recordings on oscilloscopes and analysis with limited computer assistance. Advancements in computerization, signal processing and general scientific progress over the past decades have led to improved technologies with several oscillometers that are now commercially available (Dandurand, Lavoie, Lands, & Hantos, 2019). While normal references values are not as abundantly available as spirometry due to the relative infancy of oscillometry as a diagnostic tool, the growing body of literature suggests that oscillometry offers a highly sensitive assessment of the pathological events such as SAD during lung allograft rejection, asthma, COPD and respiratory infections (Cho et al., 2020; Eddy et al., 2019; Guan et al., 2015; Ochman et al., 2018; Young et al., 2018). Oscillometry is easy for patients to perform because no effort manoeuvres are required and can thus be repeated more frequently than spirometry. It is generally less time consuming which further reduces exposure time to potential contagions. While quality control is important, operator training is also relatively quick (Wu et al., 2020). A major advantage of oscillometry over spirometry, particularly during respiratory pandemics and epidemics, is that oscillometry is conducted during normal tidal breathing, thus likely significantly reducing generation of aerosols and potential spread of pathogens compared with forced exhalation manoeuvres where the manoeuvre itself and the induced cough contributes to spreading of the contagion (Lindsley et al., 2012, 2016; Yan et al., 2018). The small airways and peripheral lung are sites of early injury in many respiratory diseases, including viral infections, asthma, COPD, interstitial lung diseases and graft dysfunction. Early detection of SAD will greatly enhance the possibility to treat in a timely manner. The addition of oscillometry to routine pulmonary function monitoring will add further insights to allow us to correlate disease severity with specific measurements in the different oscillometry parameters. In time, we believe that oscillometry will prove to be useful in management of patients with acute and chronic lung diseases while minimizing the public health potential of spreading respiratory infections. Finally, with respect to the current situation, epidemiologists expect the COVID-19 pandemic to continue in several waves over the next 18–24 months and could affect almost everyone (Giesecke, 2020). We do not believe it is sustainable to maintain optimal patient care without access to pulmonary function testing as objective data is critical for management of patients with chronic lung diseases, for preoperative risk assessment of patients and oncology patients needing life-saving therapies. Hence, we suggest that use of oscillometry as an alternative to conventional pulmonary function tests could provide high quality information about lung health and lung function while minimize public health risks. Dr. Lundblad is the clinical Science Director of Thorasys Thoracic Medical Systems, a manufacturer of lung function equipment. Dr. Chow declares no conflicting interests.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesIntégrité de la recherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,211
Score d'incertitude au seuil0,998

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,004
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,080
Tête enseignante GPT0,351
Écart entre enseignants0,272 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle