Search

Background: The Interstitial Lung Disease (ILD) India registry, which included more than 1000 patients across 27 centers of the country, reported Hypersensitivity Pneumonitis (HP) to be the most common ILD in India, followed by Connective Tissue Disease-related ILD (CTD-ILD) and Idiopathic Pulmonary Fibrosis (IPF). This study was carried out to evaluate whether the spectrum of ILDs at our center conforms to the national data. Aims: To evaluate the clinical and epidemiological profile, distribution of various ILDs, and any association of the type of ILD with clinical parameters. Materials and methods: A prospective, observational study was carried out at a tertiary care center in North India, where patients having symptoms and radiological features suggestive of ILD were evaluated for clinical, radiological features and spirometric indices. Results: A total of 83 patients with ILD were evaluated. The mean age was 53.76 ± 13.07 years. The male-to-female ratio was 0.97. The mean FEV1 was 1.41 ± 0.38 L, mean FVC was 1.57 ± 0.43 L and the mean FEV1/FVC was 90.26 ± 8.99%. The mean 6 MWD was 270.85 ± 110.52 m. Reticulation and honeycombing were the most common radiological features. IPF was the most common ILD (28.9%). Conclusion: IPF was the most common ILD at our center. A statistically significant association was found between type of ILD and age, gender, past ATT intake, HTN, clubbing, and FEV1/FVC%.

Aim: The aim of this study was to monitor prescription patterns, clinical outcomes, and adverse drug reactions (ADR) among patients of various interstitial lung diseases (ILDs). Materials and Methods: This prospective study was conducted in the Department of Pharmacology and Therapeutics in collaboration with the Department of Respiratory Medicine, King George’s Medical University, Lucknow, for a period of 12 months (October 2020–September 2021). A total of 77 patients were enrolled after satisfying the inclusion and exclusion criteria. The prescriptions were collected, and necessary details were noted on the case report form. After completion of the study, the data were analyzed for prescription patterns, clinical outcomes, and quality of life with the help of a validated questionnaire-King’s Brief ILD (KBILD) questionnaire. At the same time, ADRs, if any, were assessed using Hartwig’s Severity Assessment Scale and Naranjo Causality Assessment Scale. Results: The most common ILD was acute/chronic hypersensitivity pneumonitis (HP). Average number of drugs per encounter was 4.45. Crepitations were the most common clinical signs. Clubbing and rhonchi were reported maximum in idiopathic pulmonary fibrosis. It was found that psychological, breathlessness and activities, chest symptoms, and total KBILD reduced significantly after 3 months as compared to baseline with a statistically significant difference as P < 0.01. ADRs were found in 23.38% (18) of the subjects. Maximum ADR reported was gastritis (9.09%), followed by hepatitis (3.90%). Conclusion: The high proportion of patients clinically diagnosed with HP in our study highlights the importance of a detailed environmental exposure history in the diagnostic evaluation of patients with ILD to avoid inaccurate diagnoses. ADR-related hospital admissions are a significant problem in the health-care system.

Patients with metastatic breast cancer often have respiratory symptoms due to various causes. Trastuzumab is a drug used in the treatment of HER2/neu over-expressing breast cancer patients. Organising pneumonia is a type of idiopathic interstitial pneumonia that mimics infection or progressive disease and can be difficult to diagnose in the setting of malignancy. Making a correct diagnosis is of extreme importance since any delay in the treatment can result in significant adverse patient outcome. Here, we have described a case of organising pneumonia associated with the use of trastuzumab in metastatic breast cancer patients. On the basis of clinical data, including findings such as a decreased PaO2 level and findings on chest CT scan, these patients were diagnosed with drug-induced organising pneumonia. Although it is a rare adverse event associated with trastuzumab, it may cause rapid deterioration without preceding symptoms; hence, even though it is very rare, with an incidence of less than 2%, it is still crucial to intervene so as to prevent the occurrence of such an unfavourable outcome by means of close observation and early diagnosis along with an early withdrawal of the drug and an immediate commencement of corticosteroid therapy.

Introduction Pneumococcal diseases pose a significant public health concern in India, with substantial morbidity and mortality, with the elderly and those with coexisting medical conditions being most at risk. Pneumococcus was also seen to be one of the main reasons for co-infection, pneumonia and complications in COVID. Current guidelines recommend vaccination for specific adult populations, but there is a lack of uniformity and guidance on risk stratification, prioritisation and optimal timing. Methods Nation Against Pneumococcal Infections – Expert Panel Opinion (NAP-EXPO) is a panel convened to review and update recommendations for adult pneumococcal vaccination in India. The panel of 23 experts from various medical specialties engaged in discussions and evidence-based reviews, discussed appropriate age for vaccination, risk stratification for COPD and asthma patients, vaccination strategies for post-COVID patients, smokers and diabetics, as well as methods to improve vaccine awareness and uptake. Outcome The NAP-EXPO recommends the following for adults: All healthy individuals 60 years of age and above should receive the pneumococcal vaccine; all COPD patients, regardless of severity, high-risk asthma patients, post-COVID cases with lung fibrosis or significant lung damage, should be vaccinated with the pneumococcal vaccine; all current smokers and passive smokers should be educated and offered the pneumococcal vaccine, regardless of their age or health condition; all diabetic individuals should receive the pneumococcal vaccine, irrespective of their diabetes control. Strategies to improve vaccine awareness and uptake should involve general practitioners (GPs), primary health physicians (PHPs) and physicians treating patients at high risk of pneumococcal disease. Advocacy campaigns should involve media, including social media platforms. Conclusion These recommendations aim to enhance pneumococcal vaccination coverage among high-risk populations in India in order to ensure a reduction in the burden of pneumococcal diseases, in the post-COVID era. There is a need to create more evidence and data to support the recommendations that the vaccine will be useful to a wider range of populations, as suggested in our consensus.

Background and Objective Tobacco smoking is an established risk factor for chronic obstructive pulmonary disease (COPD). Current evidence suggests that non-tobacco-related risk factors vary geographically and are less understood than smoking. This study aims to compare the risk factors, symptoms, and clinical features of smoking (S-COPD) and non-smoking (NS-COPD) in a COPD population. Materials and Methods In this retrospective cross-sectional study, 489 COPD patients were screened. Data on socio-demographics, smoking and medical history, other risk factors, symptoms, and clinical characteristics including COPD Assessment Test (CAT) score, and Modified Medical Research Council (mMRC) Dyspnea Scale were examined. Results Of the total selected 416 COPD patients, 35.34% were NS-COPD while 64.66% were S-COPD. S-COPD was predominant in males, whereas NS-COPD was predominant in females (P < 0.0001). In NS-COPD, biomass fuel exposure was a major risk factor (P < 0.0001), and 61% of subjects had a biomass fuel exposure index of >60. In bivariate and multivariate analyses, no risk factors were correlated with forced expiratory volume in 1 second (FEV1)% predicted, while among clinical features, duration of illness (P = 0.001) was correlated with lower values of FEV1 in the multivariate table of S-COPD. In the multivariate analysis, biomass fuel exposure (P = 0.039) and CAT score (P < 0.0001) were correlated with FEV1(%) in NS-COPD. Conclusion Biomass fuel exposure is a substantial risk factor for NS-COPD and was correlated with FEV1(%) predicted. In addition, the CAT score correlated with disease severity in patients with NS-COPD. The development of COPD in non-smokers is being recognized as a separate phenotype and it should be managed according to risk factors.

Cystic fibrosis (CF) is a life-threatening genetic disorder caused by mutations in the CFTR gene. This leads to a defective protein that impairs chloride transport, resulting in thick mucus buildup and chronic inflammation in the airways. The review discusses current and future therapeutic approaches for CFTR dysfunction and airway dysbiosis in the era of personalized medicine. Personalized medicine has revolutionized CF treatment with the advent of CFTR modulator therapies that target specific genetic mutations. These therapies have significantly improved patient outcomes, slowing disease progression, and enhancing quality of life. It also highlights the growing recognition of the airway microbiome’s role in CF pathogenesis and discusses strategies to modulate the microbiome to further improve patient outcomes. This review discusses various therapeutic approaches for cystic fibrosis (CFTR) mutations, including adenovirus gene treatments, nonviral vectors, CRISPR/cas9 methods, RNA replacement, antisense-oligonucleotide-mediated DNA-based therapies, and cell-based therapies. It also introduces airway dysbiosis with CF and how microbes influence the lungs. The review highlights the importance of understanding the cellular and molecular causes of CF and the development of personalized medicine to improve quality of life and health outcomes.

Abstract Background As the pulmonary system and cardiovascular system are intimately linked, patients with chronic obstructive pulmonary disease (COPD) and asthma have high risk for developing cardiovascular diseases (CVDs) and altered central hemodynamic. Objective We aim to assess the central aortic blood pressure (CABP) indices, pulse wave velocity (PWV) and other indicators of arterial stiffness in Indian patients with COPD and bronchial asthma. Methods This is a single‐center, cross‐sectional study conducted in outpatients diagnosed with either chronic stable phase of COPD or bronchial asthma. CABP indices, vascular age, arterial stiffness and central hemodynamics were measured in patients. Results Of 193 patients with obstructive airway disease who were enrolled, (n = 81 had COPD and n = 112 had partially‐controlled bronchial asthma) the proportion of male patients was higher in both groups. The PWV, augmentation index (AI) and vascular age (VA) were significantly higher in patients with COPD compared to those with bronchial asthma (all, p

Birt–Hogg–Dubé syndrome (BHDS) is a rare hereditary autosomal dominant condition characterized by benign cutaneous lesions, lung cysts, and increased risk of spontaneous pneumothorax and renal cancer. We report a case of a young Indian boy with bilateral pneumothorax as the first symptom of BHDS. Detailed history examination and investigation showed multiple facial lesions; his computerized tomography was suggestive of renal angiomyolipoma, hepatic angiomyolipoma, pulmonary cyst with pneumothorax, and small bilateral subependymal soft tissue density lesion with calcification in the brain, all of which were collectively suggestive of BHDS. Identification of the above commonly presented clinical features as a syndrome is important for even a primary care physician so as to ensure the timely management and if required referral to a higher center.

Pleural effusion is a common problem in our country, and most of these patients need invasive tests as they can’t be evaluated by blood tests alone. The simplest of them is diagnostic pleural aspiration, and diagnostic techniques such as medical thoracoscopy are being performed more frequently than ever before. However, most physicians in India treat pleural effusion empirically, leading to delays in diagnosis, misdiagnosis and complications from wrong treatments. This situation must change, and the adoption of evidence-based protocols is urgently needed. Furthermore, the spectrum of pleural disease in India is different from that in the West, and yet Western guidelines and algorithms are used by Indian physicians. Therefore, India-specific consensus guidelines are needed. To fulfil this need, the Indian Chest Society and the National College of Chest Physicians; the premier societies for pulmonary physicians came together to create this National guideline. This document aims to provide evidence based recommendations on basic principles, initial assessment, diagnostic modalities and management of pleural effusions.

Small cell lung carcinoma (SCLC) is characterized by rapid growth and an aggressive clinical course. Standard therapy regimes have limited effects on disease course; therefore the prognosis of SCLC is poor. In the current study, the frequency of programmed death ligand 1 (PD-L1) expression in SCLC and its correlation with clinico-pathological features were evaluated. The study included 100 cases of SCLC wherein testing for PD-L1 was done with the SP263 clone on the Ventana benchmark XT system. Cases with > 1% PD-L1 expression in tumour cells or immune cells were categorized as positive. PD-L1 expression was identified in 14% of cases using the cut-off of ≥ 1%. The tumour proportion score was 10% and the immune proportion score was 9.78% using a cut-off of ≥ 1%. PD-L1 positive expression was more frequent in the male population with age > 40 years. All the patients with positive PD-L1 expression were smokers. In the PD-L1 positive group, presence of necrosis was identified in 71.4% of cases and when compared with the PD-L1 negative subgroup this finding was statistically significant (p = 0.010). Personalized targeted therapy for cases of SCLC is still under evaluation. The use of immunotherapeutic targets, such as PD-L1, may help to define a new treatment strategy for SCLC. Development of new treatment strategies may improve prognosis and survival.

Abstract Background Professionalism among nurses plays a critical role in ensuring patient safety and quality care and involves delivering competent, safe, and ethical care while also working with clients, families, communities, and healthcare teams. Aims and objectives To assess the level of nursing professionalism and the factors affecting professionalism among nurses working at a tertiary care center in India. Methods A descriptive cross-sectional study was conducted from October 2022 to March 2023 using a total enumeration sampling technique. Following institutional ethics committee approval, standardized tools were administered consisting of Nursing Professionalism Scale and socio-demographic, personal, and organizational characteristics. Results A total of 270 nurses participated, with a response rate of 93.7%. The mean age of the participants was 27.33 ± 2.75 years, with the majority being female (82.6%) and belonged to the age group of 23–27 years (59.6%). More than half of the nurses exhibited high professionalism (53%), with the highest and lowest median scores for professional responsibility (29.0) and valuing human beings (13.0) respectively. Multivariate regression analysis demonstrated that, compared with their counterparts, nurses with a graduate nursing qualification (AOR = 4.77, 95% CI = 1.16–19.68), up-to-date training (AOR = 4.13, 95% CI = 1.88–9.06), and adequate career opportunity (AOR = 33.91, 95% CI = 14.48–79.39) had significant associations with high nursing professionalism. Conclusion/Implications for practice The majority of the nurses had high professionalism, particularly in the domains of professional responsibility and management. Hospitals and healthcare institutions can use these findings to develop policies and prioritize opportunities for nurses to attend conferences and workshops to enhance their professional values, ultimately leading to improved patient care outcomes. Patient and public contribution No patient or public contribution.

Heat stress is a critical environmental factor that adversely affects crop productivity. With the increasing frequency and intensity of heat waves and extreme weather events, heat stress has become a challenge for wheat production, which is one of the most important cereal crops. To sustain wheat production under heat stress conditions, there is an urgent need to develop high-yielding, heat-tolerant wheat varieties. This requires characterizing the genetic and physiological mechanisms underlying heat tolerance, as well as developing efficient phenotyping methods to evaluate a large number of wheat genotypes under heat stress field conditions. In this study, we used 184 wheat genotypes that were sown at two times of sowing (TOS), i.e., optimal sowing as TOS1 and late sowing as TOS2, with higher temperatures faced by plants during heading and grain filling in TOS2. We used a combination of physiological traits, multispectral vegetative indices (VIs) derived from aerial imagery and machine learning approaches to effectively differentiate wheat genotypes for heat tolerance and susceptibility. The response of wheat genotypes to heat stress was delineated as being susceptible, moderate, and tolerant using the stress susceptibility index, percentage loss, and tolerance index. Different VIs varied significantly between the two TOS. The decline in VIs during anthesis and post-anthesis was minimal in heat tolerant genotypes compared to susceptible genotypes under TOS2. We classified the stress severity and yield using VIs with a machine learning approach. A model was created with a random forest classifier (RFC) trained to categorize genotypes based on the stress susceptibility index using Python libraries. The PCA was utilized to reduce dimensionality, and five principal components explaining 99 % of the variability were employed as input for developing the model. The RFC model achieved an accuracy of 64 % and excelled in recognizing crops under extreme stress, with a recall rate of 0.87 and an F1 score of 0.77 for the susceptible class. The model had high precision metrics, with values of 0.69, 0.42, and 0.80 for the susceptible, moderate, and tolerant classes, respectively. Our results suggest that multispectral-driven phenotypic traits can be used by breeders to select and develop wheat varieties tolerant to heat stress.

Water stress is a significant challenge for global food production. Rainfall pattern is becoming unpredictable due to climate change that causes unprecedent water stress conditions in cereals production including wheat which is one of the important staple food crops. To sustain wheat production under water limiting conditions, there is an urgent need to develop drought-tolerant wheat varieties. For this, screening large numbers of wheat genotype for traits related to growth and yield under water stressed conditions is crucial. In this study, we deployed high-throughput phenotyping approaches, including uncrewed aerial vehicle (UAV)-based multispectral imaging, advanced machine and deep learning regression models. Two separate field experiments, irrigated and rainfed, were conducted comprising 553 wheat genotypes, and collected dataset for traits such as plant height, phenology, grain yield, and timeseries multispectral imaging. UAV-multispectral imagery derived plant height measurements showed a high correlation (R2=0.75) with manual measurements. Vegetation indices derived from multispectral data differentiated growth pattern of genotypes under rainfed and irrigated conditions and were used in yield prediction modeling. Wheat genotypes were effectively ranked, and their response differentiated for water stress tolerance based on yield index, stress susceptibility index, and yield loss%. Importantly, yield prediction in genotypes was computed using four machine learning regression algorithms i.e., linear regression, support vector machine, random forest, and deep learning H2O-3, where H2O-3 was the most accurate model with R2=0.80. Results show that multispectral-driven traits combined with machine learning models effectively phenotyped large wheat population and such approaches can be integrated in crop breeding program to develop varieties tolerant to water stress.

To enhance their company operations, organizations within the industry leverage the ecosystem of big data to manage vast volumes of information effectively. To achieve this objective, it is imperative to analyze textual data while prioritizing the safeguarding of data integrity and implementing robust measures for organizing and validating data through the utilization of spam filters. Various methodologies can be employed, including Word2Vec, bag-of-words, BERT, as well as term frequency & reciprocal document frequency (TF-IDF). Nevertheless, none of these solutions effectively address the problem of data scarcity, which might lead to the existence of missing information in the collected documents. To properly address this problem, it is necessary to employ a strategy that categorizes each document based on the topic matter and uses statistical approaches for approximation. This research paper presents a novel approach for spam detection using natural language processing. The proposed strategy utilizes a least-squares model to modify themes and incorporates gradient descent and altering least-squares (i.e., AMALS) models for estimating missing data. TF-IDF and uniform-distribution methods perform the estimation. The performance evaluation reveals that the suggested technique exhibits a superior performance of 98% compared to the existing industry TF-IDF model in accurately predicting spam within big data ecosystems. By this model, the environment of an organization or a company can be saved from spamming or other attacks, which can lead to extracting their data for unauthorized users to protect the details.

Background: Nurses frequently experience compassion fatigue and burnout, which impact their personal lives and patient care. The COVID-19 pandemic additionally caused stress, uncertainty, and fear of death among healthcare professionals. Aim: To assess professional quality of life (ProQoL) among nurses after the second wave of the COVID-19 pandemic. Material and Methods: A web-based cross-sectional study was conducted among 203 nurses using a purposive sampling technique in the month of September to December 2021. Data were collected using a self-administered ProQoL scale version 5. Statistical Analysis: Descriptive and inferential statistics were used. Kolmogorov–Smirnov test, Mann–Whitney U, and Kruskal–Wallis H test were used. Bivariate correlations were used to correlate the main variables. Multiple linear regression analysis was also performed. Results: The majority of the nurses reported a moderate level of compassion satisfaction (CS) (62.6%), burnout (BO) (66.0%), and secondary traumatic stress (STS) (63.1%). Residence and education emerged as a factor whether the nurses experienced BO or STS, respectively. Additionally, CS negatively correlated with BO (r = -0.732: P < 0.001) and STS (r = -0.141: p-0.04). Conclusions: The majority of the nurses experienced moderate levels of CS, BO, and STS after the second wave of the COVID-19 crisis and nurse patient–ratio emerged as a significant factor to predict CS, BO, or STS. Hence, effective measures need to be implemented by hospital administration to enhance the nurses' satisfaction and reduce fatigue and burnout.

The persistent morbidity and mortality associated with tuberculosis (TB), despite our continued efforts, has been long recognized, and the rise in the incidence of drug-resistant TB adds to the preexisting concern. The bulk of the TB burden is confined to low-income countries, and rigorous efforts are made to detect, notify, and systematically treat TB. Efforts have been infused with renewed vigor and determination by the World Health Organization (WHO) to eliminate tuberculosis in the near future. Different health agencies worldwide are harvesting all possible strategies apart from consolidating ongoing practices, including prevention of the development of active disease by treating latent TB infection (LTBI). The guidelines for the same were already provided by the WHO and were then adapted in the Indian guidelines for the treatment of LTBI in 2021. While the long-term impact of TBI treatment is awaited, in this article, we aim to discuss the implications in the Indian context.

The growth and yield of crops have been significantly affected by abiotic stresses. Although respiratory metabolism is integral to plants, its understanding within the context of stress adaptation remains limited . While the rice genome contains three Aconitase genes, their specific roles in abiotic stress tolerance and plant development remain largely unexplored. This study aimed to characterize the Aconitase gene family in rice, shedding light on the evolution of Aconitase and its involvement in diverse developmental processes, as well as its response under various abiotic stress conditions. Phylogenetic analysis indicated the evolutionary relationship between rice Aconitase genes and those of other plant species. The prediction of promoter cis-elements revealed the presence of diverse cis-acting elements associated with the response to abiotic stress within the Aconitase gene family. In addition, an analysis of public RNA-seq data indicated the potential involvement of Aconitase genes in various developmental processes and mechanisms related to stress tolerance. Further, qRT-PCR confirmed the expression patterns of Aconitase genes. Expression analysis revealed differential expression of Aconitase genes under cold, drought, ABA, and salt stresses. Elevated levels of the OsAco1 transcript resulted in a phenotype that exhibited increased tolerance to salt stress. Biochemical analysis revealed higher Aconitase activity in the overexpressed line compared to the control plant. Furthermore, the overexpressed line exhibited improved growth and lower H2O2 levels than the control plant following a 2-hour exposure to 200 mM salt stress. These findings suggest a potential role of Aconitase in enhancing salt stress tolerance. Moreover, they lay the foundation for further exploration into the precise involvement of Aconitase in plant developmental processes under various stress conditions, with the ultimate aim of developing salt-tolerant rice cultivars.

Background: With the emergence of the COVID-19 pandemic, the role of nurses came into the limelight. Despite efforts, concerns have grown about the nurse's support, interest in carrying out their job responsibilities, and fear of getting COVID-19 infection. Therefore, we aim to assess the prevalence and predictors of job turnover intention, social support, and fear of COVID-19 (FCV-19) among frontline nurses. Methods: A descriptive cross-sectional survey was conducted in May–June 2022, involving 229 nurses using total enumeration sampling technique. Standardized tools consisting of turnover intention scale, multidimensional scale of perceived social support, and FCV-19 scale were administered. The data was analyzed using IBM SPSS version 20.0. Descriptive and inferential statistics included the Kolmogorov–Smirnov test, Mann–Whitney U, and Kruskal–Wallis H test. Multiple linear regression analysis was performed to predict factors affecting the main variables. Results: The mean age of the study participants was 27.10 ± 2.72 years, with the majority being females (86.0 %). The results indicated that a significant proportion of nurses had the intention to leave the nursing profession (43.7 %). Majority of the nurses reported high social support (55.9 %) and low fear of COVID-19 (61.6 %). Regression analysis identified marital status and fear of COVID-19 as significant factors influencing job turnover intention. Conclusion: Our study suggested that approximately half of the nurses might leave nursing profession in the near future, even though they report high social support and low FCV-19, potentially have adverse effects on patient care within the hospital setting, necessitating urgent interventions from both nurse managers and hospital administrators.

Abstract Background Desmoid fibromatosis (DF) is an atypical, non-malignant tumor known for its distinctive feature of exhibiting an intermediate biological behavior that falls between benign fibrous lesions and fibrosarcoma. The article aimed to outline the imaging characteristics of desmoid fibromatosis and distinguish it from its similar counterpart, nerve sheath tumors. Results Here, we present two cases of desmoid fibromatosis whose imaging findings mimic nerve sheath tumors. The patients presented with neck swelling and radiating pain. Both cases were biopsy-proven. Imaging features characteristic of these lesions include elongated shape, split-fat sign, and fascial tail sign with mixed signal intensity on T1WIs and T2WIs depending upon the collagen content of the lesion. Conclusions MRI is the best diagnostic modality for differentiating fibromatosis from nerve sheath tumors. Surgery continues to be the primary approach for treating these growths, but in some cases, chemoradiation is employed to achieve improved control rates. The presence of intralesional low-intensity bands in T2WIs is a characteristic feature of fibromatosis. Given its local aggressiveness and propensity for recurrence, the use of multiple imaging modalities is essential for providing informed guidance on outcomes and treatment strategies.