Terence Chi Chun Tam

Chronic obstructive pulmonary disease (COPD) is often exacerbated by various viruses and bacteria, leading to acute episodes of worsening respiratory symptoms, which contribute significantly to the morbidity and mortality associated with COPD. Consequently, vaccination against these pathogens is recommended by numerous guidelines to safeguard COPD patients from adverse health outcomes. The Global Initiative for Chronic Obstructive Lung Disease (GOLD) recommendation advocates for vaccination against influenza, Streptococcus pneumoniae, respiratory syncytial virus (RSV), severe acute respiratory syndrome coronavirus (SARS-CoV2), pertussis, and varicella zoster. This review article will examine the current vaccination strategies recommended for adult COPD patients and will discuss the clinical benefits associated with these vaccines.

Bronchiectasis is a disease with predominantly neutrophilic inflammation. As a readily available biomarker, there is little evidence to support the use of blood neutrophil-to-lymphocyte ratio (NLR) to predict bronchiectasis exacerbation severe enough to warrant hospitalization. A registry-based retrospective cohort study was conducted at a in Hong Kong. Chinese patients with non-cystic fibrosis (CF) bronchiectasis were retrospectively reviewed and subsequently followed up to investigate the association of NLR and the need for hospitalization for bronchiectasis exacerbation. Data on the NLR for patients in a clinically stable state in 2018 were collected and patients followed up from 1 January 2019 to 31 December 2022. The primary outcome was the need for hospitalization due to bronchiectasis exacerbation over the next 4 years. We reviewed 473 Chinese patients with non-CF bronchiectasis, of whom 94 required hospitalization for bronchiectasis exacerbation during the 4-year follow-up period. Multi-variable logistic regression adjusted for E-FACED score (Exacerbation, Forced expiratory volume in 1 s (FEV₁), Age, Chronic colonization, Extension, and Dyspnea score), gender, age, smoking status, and presence of co-existing chronic obstructive pulmonary disease (COPD) was conducted to compare patients with highest and lowest quartile NLR. Results revealed that those with NLR at the highest quartile were at increased risk of hospitalization for bronchiectasis exacerbation with an adjusted odds ratio (aOR) of 2.02 (95% confidence interval = 1.00–4.12, p = 0.05). Blood NLR may serve as a marker to predict the need for hospitalization due to bronchiectasis exacerbation.

Influenza is an important respiratory viral pathogen in adults, with secondary bacterial pneumonia being a common complication. While pneumococcal vaccines can prevent pneumococcal pneumonia and invasive pneumococcal disease, whether they can also prevent the severe in-hospital outcomes among patients hospitalized for influenza has not been examined. A territory-wide retrospective study was conducted in Hong Kong, which included all adult patients having chronic airway diseases (asthma, bronchiectasis, and chronic obstructive pulmonary disease) hospitalized for influenza and who had received seasonal influenza vaccine. The occurrence of secondary bacterial pneumonia, mortality, and other severe in-hospital outcomes were compared among subjects with or without pneumococcal vaccination. There was a total of 3066 eligible patients who were hospitalized for influenza in public hospitals in Hong Kong from 1 January 2016 to 30 June 2023. Completed pneumococcal vaccination with PSV23/PCV13 conferred protection against secondary bacterial pneumonia, all-cause mortality, and respiratory cause of mortality with adjusted odds ratios of 0.74 (95% CI = 0.57–0.95, p = 0.019), 0.12 (95% CI = 0.03–0.53, p = 0.005), and 0.04 (95% CI = 0.00–0.527, p = 0.0038), respectively.

Airway segmentation is essential for chest CT image analysis. Different from natural image segmentation, which pursues high pixel-wise accuracy, airway segmentation focuses on topology. The task is challenging not only because of its complex tree-like structure but also the severe pixel imbalance among airway branches of different generations. To tackle the problems, we present a NaviAirway method which consists of a bronchiole-sensitive loss function for airway topology preservation and an iterative training strategy for accurate model learning across different airway generations. To supplement the features of airway branches learned by the model, we distill the knowledge from numerous unlabeled chest CT images in a teacher-student manner. Experimental results show that NaviAirway outperforms existing methods, particularly in the identification of higher-generation bronchioles and robustness to new CT scans. Moreover, NaviAirway is general enough to be combined with different backbone models to significantly improve their performance. NaviAirway can generate an airway roadmap for Navigation Bronchoscopy and can also be applied to other scenarios when segmenting fine and long tubular structures in biomedical images. The code is publicly available on https://github.com/AntonotnaWang/NaviAirway.

Background and Objective: Electronic medical record (EMR) databases can facilitate epidemiology research in various diseases including bronchiectasis. Given the diagnostic challenges of bronchiectasis, the validity of the coding in EMR requires clarification. We aimed to assess the validity of International Classification of Diseases, 9th Revision (ICD‐9) code algorithms for identifying bronchiectasis in the territory‐wide electronic medical health record system of Clinical Data Analysis and Reporting System (CDARS) in Hong Kong.Materials and Methods: Adult patients who had the diagnosis of bronchiectasis input from Queen Mary Hospital in 2011–2020 were identified using the ICD‐9 code of 494 by CDARS. All patients who had high resolution computed tomography (HRCT) were reviewed by respiratory specialists to confirm the presence of bronchiectasis on HRCT.Results: A total of 19 617 patients who had the diagnostic code of bronchiectasis among all public hospitals in Hong Kong and 1866 in Queen Mary Hospital in the same period. Six hundred and forty‐eight cases were randomly selected and validated using medical record and HRCT review by a respiratory specialist. The overall positive predictive value (PPV) was 92.7% (95% CI 90.7–94.7).Conclusions: This was the first ICD‐9 coding validation for bronchiectasis in Hong Kong CDARS. Our study demonstrated that using ICD‐9 code of 494 was reliable to support utility of CDARS database for further clinical research on bronchiectasis.

Background and ObjectiveAlthough stage I non-small cell lung carcinoma (NSCLC) typically carries a good prognosis following complete resection, early disease recurrence can occur. An accurate survival prediction model would help refine a follow-up strategy and personalize future adjuvant therapy. We developed a post-operative prediction model based on readily available clinical information for patients with stage I adenocarcinoma. MethodsWe retrospectively studied the disease-free survival (DFS) of 408 patients with pathologically confirmed low-risk stage I adenocarcinoma of lung who underwent curative resection from 2013 to 2017. A tree-based method was employed to partition the cohort into subgroups with distinct DFS outcome and stepwise risk ratio. These covariates were included in multivariate analysis to build a scoring system to predict disease recurrence. The model was subsequently validated using a 2011-2012 cohort. ResultsNon-smoker status, stage IA disease, epidermal-growth factor receptor mutants and female gender were associated with better DFS. Multivariate analysis identified smoking status, disease stage and gender as factors necessary for the scoring system and yielded 3 distinct risk groups for DFS [99.4 (95% CI 78.3-125.3), 62.9 (95% CI 48.2-82.0), 33.7 (95% CI 24.6-46.1) months, p < 0.005]. External validation yielded an area under the curve by receiver operating characteristic analysis of 0.863 (95% CI 0.755-0.972). ConclusionThe model could categorize post-operative patients using readily available clinical information, and may help personalize a follow-up strategy and future adjuvant therapy.

Background: Electronic health record (EHR) databases can facilitate epidemiology research into various diseases including asthma. Given the diagnostic challenges of asthma, the validity of the coding in EHR requires clarification. We aimed to assess the validity of International Classification of Diseases, 9th Revision (ICD-9) code algorithms for identifying asthma in the territory-wide electronic medical health record system of the Clinical Data Analysis and Reporting System (CDARS) in Hong Kong. Methods: Adult patients who had the diagnosis of asthma input from all public hospitals in Hong Kong and those from Queen Mary Hospital in 2011– 2020 were identified using the ICD-9 code of 493 (493.0, 493.1, 493.2, and 493.9) by CDARS. Patients’ clinical record and spirometry were reviewed by two respiratory specialists to confirm the presence of asthma in the randomly selected cases. Results: There were 43,454 patients who had the diagnostic code of asthma among all public hospitals in Hong Kong and 1852 in Queen Mary Hospital in the same period. A total of 200 cases were randomly selected and validated using medical record and spirometry review by a respiratory specialist. The overall positive predictive value (PPV) was 85.0% (95% CI 80.1− 89.9%). Conclusion: This was the first ICD-9 code validation for CDARS (EHR) in Hong Kong on asthma. Our study demonstrated that using ICD-9 code (493.0, 493.1, 493.2 and 493.9) to identify asthma can result in a PPV that was reliable to support the utility of the CDARS database for further research on asthma among the Hong Kong population.

While molnupiravir (MOV) and nirmatrelvir–ritonavir (NMV-r) were developed for treatment of mild to moderate COVID-19 infection, there has been a lack of data on the efficacy among unvaccinated adult patients with chronic respiratory diseases, including asthma, chronic obstructive pulmonary disease (COPD) and bronchiectasis. A territory-wide retrospective cohort study was conducted in Hong Kong to investigate the efficacy of MOV and NMV-r against severe outcomes of COVID-19 in unvaccinated adult patients with chronic respiratory diseases. A total of 3267 patients were included. NMV-r was effective in preventing respiratory failure (66.6%; 95% CI, 25.6–85.0%, p = 0.007), severe respiratory failure (77.0%; 95% CI, 6.9–94.3%, p = 0.039) with statistical significance, and COVID-19 related hospitalization (43.9%; 95% CI, −1.7–69.0%, p = 0.057) and in-hospital mortality (62.7%; 95% CI, −0.6–86.2, p = 0.051) with borderline statistical significance. MOV was effective in preventing COVID-19 related severe respiratory failure (48.2%; 95% CI 0.5–73.0, p = 0.048) and in-hospital mortality (58.3%; 95% CI 22.9–77.4, p = 0.005) but not hospitalization (p = 0.16) and respiratory failure (p = 0.10). In summary, both NMV-r and MOV are effective for reducing severe outcomes in unvaccinated COVID-19 patients with chronic respiratory diseases.

Accessibility of diagnostic screening and treatment monitoring devices for respiratory diseases is critical in promoting healthcare and reducing sudden complications and mortality. Spirometry is the standard for diagnosing and monitoring several lung diseases. However, it lacks regional assessment capabilities necessary for detecting subtle regional changes in certain diseases. It also requires challenging breathing maneuvers difficult for elderlies, children, and diseased patients. Here, we actualized an affordable, portable, and self-administrable electrical impedance tomography (EIT) system for home-based lung function assessment and telemedicine. Through simultaneous EIT-spirometry trials on healthy subjects, we demonstrated that our device can predict spirometry indicators over a wide range and can provide regional mapping of these indicators. We further developed a close-to-effortless breathing paradigm and tested it by longitudinally monitoring a COVID-19 discharged subject and two healthy controls with results suggesting the paradigm can detect initial deterioration followed by recovery. Overall, the EIT system can be widely applicable for lung function screening and monitoring both at homes and clinics.