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Enregistrement W4409562829 · doi:10.4103/pulmon.pulmon_3_25

Interstitial Lung Diseases - Registries are the Need of the Hour

2025· article· en· W4409562829 sur OpenAlexaboutno aff
M. Sajitha

Notice bibliographique

RevuePULMON · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésLungMedicineIntensive care medicineInternal medicine

Résumé

récupéré en direct d'OpenAlex

The entity of interstitial lung diseases (ILD) encompass over 200 heterogeneous lung disorders involving lung parenchyma characterized by interstitial inflammation and fibrosis affecting the very basic function of the lung namely gas exchange. The ILDs comprise different radiologic patterns such as usual interstitial pneumonia (UIP), nonspecific interstitial pneumonia, organizing pneumonia, hypersensitivity pneumonitis (HP), respiratory bronchiolitis ILD, cystic ILD, and unclassifiable ILD.[1] The differing etiologies such as connective tissue diseases, granulomatous diseases, smoking-related, pneumoconiosis, and unknown causes (idiopathic) channel lung into a common pathway of fibrosis and loss of lung function over time. This leads to significant symptoms such as dyspnea and hypoxemia in patients, lowering their quality of life and early mortality. The prototype of ILD is idiopathic pulmonary fibrosis (IPF) with a UIP radiologic pattern which has a worse prognosis than most cancers and is next to only lung and pancreatic cancers with median survival of 2–5 years.[2] But 18%-32% of other non-IPF ILDs[3] may also undergo progressive fibrosis with a median survival of 2.5-4 years.[4] The diverse etiology of lung fibrosis makes it challenging to subtype the ILD not to mention the many radiological patterns that maybe seen in a single etiology itself which in turn makes compartmentalization difficult and hence having a uniform protocol of treatment almost nonpractical even for a single etiology. The rate of progression of disease is also variable for different persons. Hence, an accurate etiologic diagnosis with type of radiologic pattern with close follow-up is a requisite for proper management. The guidelines on ILD starting from 2000 to 2022 have evolved continuously from characterizing the different ILDs, to specifying diagnostic criteria for (IPF) the prototype, to more recently clumping the non-IPF ILDs which show a progressive fibrotic nature into progressive pulmonary fibrosis.[1,5,6] Over the years, new disease categories such as pleuropulmonary fibroelastosis and combined pulmonary fibrosis and emphysema (CPFE) have been included. A separate guideline for HP[7] has also helped in characterizing the diagnostic criteria and treatment guidelines and has also addressed the inorganic antigens along with organic antigens which is a necessity nowadays with more industry and occupation-related exposures. Drugs and treatment-related lung injuries also merit attention in this new world of biologicals and immunotherapy. COVID-19, though only to a limited extent, also brought into foray the infections which may lead to lasting fibrotic changes. A multidisciplinary discussion for diagnosis remains the cornerstone for a specific diagnosis.[1] However, video-assisted thoracoscopic and transbronchial lung cryo biopsy (TBLC) also contribute in difficult cases. Hence, it is a continuously evolving arena. In the management of ILDs, identification and avoidance of inciting agents such as antigens, occupation-related exposures, drugs, and toxins are of paramount importance. An array of antinflammatory treatments and biologicals are available for connective tissue diseses, sarcoidosis, and HP. But regardless of etiology, fibrosing type of radiologic patterns shows functional decline with poor prognosis and the antifibrotic treatment available for these are still limited namely pirfenidone, nintedanib, and recently nerandomilast.[8] The timing of antinflammatory management and its modification in a deteriorating patient, timing of introduction of antifibrotics all need a close monitoring and precision medicine. The seasonal infections and exacerbations may complicate treatment and contribute to longitudinal decline in lung function. Supportive management with vaccines and pulmonary rehabilitation is essential for a good functional life. All this points to a longitudinal follow-up in a patient which requires a registry in every specialized center like the cancer registry in institutions. This will help in the administration of unified precision treatment, multidisciplinary approach both in diagnosis and management utilizing medical boards and smooth mobilization of rehabilitation and palliative care services. A registry can be defined as a systematic longitudinal, collection of “real-world” data describing the health status and medical interventions in a defined population of individuals.[9] Patient registries enable the collection of data on the clinical course of diseases and their impact on patients and healthcare services. In addition, many registries collect a range of biological samples, with the aim of linking clinical features or outcomes to disease pathobiology. Multicentric registries with common protocol will help in delineating the patterns over different regions. The radiologic patterns and etiology may vary across different geographic regions. There are registries such as Australasian registry, Canadian registry, BTS registry, Danish registry, and EXCITING-ILD registry Portray registry of China. Some of them are for specific diseases such as IPF and sarcoidosis. Others enlist all ILD patients and follow them up longitudinally. This helps in identifying regional variations and also helps in avoidance of inciting antigen or occupational exposure or can initiate activity against some exposures. The ILD INDIA registry (1088 patients) identified hypersensitivity as the most common cause (47.3%) in India, but this included more centers from northern India.[10] The study identified air coolers as a possible reason for fungal sensitization. There is dearth of data regarding ILDs in southern India. In this edition of PULMON Dr Anusree et al. of Government Medical College Kottayam has an original article based on ILD database in the institution. Despite being a single-center study, the study gives valuable insights. CTD ILD was found to be the commonest followed by IPF and HP. This in contrast to the ILD India registry. They also could identify interstitial pneumonia with auto immune features (IPAF), CPFE, and a spate of docetaxel-induced ILDS (which in turn led to corrective measures). This may be because it was a referral center. A multicentric registry with a common protocol could eliminate any bias. The integration of institutional registries region-wise and nation-wise with common protocols for diagnosis will further help in providing insights into early detection of progression in different ILD subtypes with a high degree of diagnostic certainty, further characterization, and understanding of disease behavior in these diverse group of patients. The registries document disease course and outcomes among patients who fall outside the narrow inclusion criteria of clinical trials like those with severe lung function impairment, high comorbidity burden, unclassifiable ILDs or those with atypical features. It should be noted that they cannot by themselves determine treatment effects in these patient groups in the way that a randomized trial could. But like in cystic fibrosis research,[11] these registries can leverage the biobank data for pragmatic clinical trials and gain insights that would be difficult to achieve in a traditional standalone trial. The large numbers and heterogeneity of patients, different outcome events, and duration of follow-up help to incorporate the individual disease behavior gleaned from the registry into analyses of individual treatment effects and can validate individualized diagnostic and therapeutic approaches in randomized clinical trials. There is a growing body of evidence, mainly in the liver and kidneys, that human fibrogenesis may be reversible to some extent.[12] Although human lung seems to lack this regeneration property in chronic fibrosis, fibrosis induced by acute forms of injury like COVID-19 showed partial or even complete resolution, though the specific mechanisms of fibrosis stabilization or regression are uncertain.[13,14] Data from patient registries have already helped in improving understanding of the clinical characteristics of patients with IPF, the impact that the disease has on their quality of life and survival, and current practices in diagnosis and management. The same is now happening for the non-IPF fibrosing ILDs. As genotyping and gene sequencing reveal new targets fruits are to be reaped though slow to bear. In the future, analyses of biospecimens linked to detailed patient profiles may provide the opportunity to identify biomarkers linked to disease progression, facilitating the development of precision medicine approaches for prognosis and therapy in patients with chronic fibrosing ILDs. Maintaining the quality and completeness of registry databases presents logistic and resourcing challenges, but it is important to ensure the robustness of the analyses. Let us hope that maintaining databases and registries for all subtypes of this diverse group of patients will help in our understanding and management of these patients who need an accurate diagnosis, tailored treatment, close monitoring, and lifestyle modifications to maintain their lung function. A large, inclusive, and efficiently managed ILD registry surely provides an invaluable opportunity to efficiently facilitate prospective interventional studies in this challenging patient population. Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.

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.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,012
score de la tête « metaresearch » (Gemma)0,067
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,117
Score d'incertitude au seuil0,391

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0120,067
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0040,005
Études des sciences et des technologies0,0020,002
Communication savante0,0090,019
Science ouverte0,0030,008
Intégrité de la recherche0,0070,009
Charge utile insuffisante (le modèle a refusé de juger)0,1170,055

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 Opus0,006
Tête enseignante GPT0,247
Écart entre enseignants0,242 · 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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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