The PROgnostic ModEl for chronic lung disease (PRO-MEL): development and temporal validation.

BACKGROUND: Patients with chronic lung diseases (CLDs), defined as progressive and life-limiting respiratory conditions, experience a heavy symptom burden as the conditions become more advanced, but palliative referral rates are low and late. Prognostic tools can help clinicians identify CLD patients at high risk of deterioration for needs assessments and referral to palliative care. As current prognostic tools may not generalize well across all CLD conditions, we aim to develop and validate a general model to predict one-year mortality in patients presenting with any CLD. METHODS: A retrospective cohort study of patients with a CLD diagnosis at a public hospital from July 2016 to October 2017 was conducted. The outcome of interest was all-cause mortality within one-year of diagnosis. Potential prognostic factors were identified from reviews of prognostic studies in CLD, and data was extracted from electronic medical records. Missing data was imputed using multiple imputation by chained equations. Logistic regression models were developed using variable selection methods and validated in patients seen from January 2018 to December 2019. Discriminative ability, calibration and clinical usefulness of the model was assessed. Model coefficients and performance were pooled across all imputed datasets and reported. RESULTS: Of the 1000 patients, 122 (12.2%) died within one year. Patients had chronic obstructive pulmonary disease or emphysema (55%), bronchiectasis (38%), interstitial lung diseases (12%), or multiple diagnoses (6%). The model selected through forward stepwise variable selection had the highest AUC (0.77 (0.72-0.82)) and consisted of ten prognostic factors. The model AUC for the validation cohort was 0.75 (0.70, 0.81), and the calibration intercept and slope were - 0.14 (-0.54, 0.26) and 0.74 (0.53, 0.95) respectively. Classifying patients with a predicted risk of death exceeding 0.30 as high risk, the model would correctly identify 3 out 10 decedents and 9 of 10 survivors. CONCLUSIONS: We developed and validated a prognostic model for one-year mortality in patients with CLD using routinely available administrative data. The model will support clinicians in identifying patients across various CLD etiologies who are at risk of deterioration for a basic palliative care assessment to identify unmet needs and trigger an early referral to palliative medicine. TRIAL REGISTRATION: Not applicable (retrospective study).

Risk Factors for All-Cause Mortality in Patients Diagnosed with Advanced Heart Failure: A Scoping Review.

Introduction: Identifying the evolving needs of patients with advanced heart failure (AdHF) and triaging those at high risk of death can facilitate timely referrals to palliative care and advance patient-centered individualized care. There are limited models specific for patients with end-stage HF. We aim to identify risk factors associated with up to three-year all-cause mortality (ACM) and describe prognostic models developed or validated in AdHF populations. Methods: Frameworks proposed by Arksey, O'Malley, and Levac were adopted for this scoping review. We searched the Medline, EMBASE, PubMed, CINAHL, Cochrane library, Web of Science and gray literature databases for articles published between January 2010 and September 2020. Primary studies that included adults aged ≥ 18 years, diagnosed with AdHF defined as New York Heart Association class III/IV, American Heart Association/American College of Cardiology Stage D, end-stage HF, and assessed for risk factors associated with up to three-year ACM using multivariate analysis were included. Studies were appraised using the Quality of Prognostic Studies tool. Data were analyzed using a narrative synthesis approach. Results: We reviewed 167 risk factors that were associated with up to three-year ACM and prognostic models specific to AdHF patients across 65 articles with low-to-moderate bias. Studies were mostly based in Western and/or European cohorts (n = 60), in the acute care setting (n = 56), and derived from clinical trials (n = 40). Risk factors were grouped into six domains. Variables related to cardiovascular and overall health were frequently assessed. Ten prognostic models developed/validated on AdHF patients displayed acceptable model performance [area under the curve (AUC) range: 0.71-0.81]. Among the ten models, the model for end-stage-liver disease (MELD-XI) and acute decompensated HF with N-terminal pro b-type natriuretic peptide (ADHF/proBNP) model attained the highest discriminatory performance against short-term ACM (AUC: 0.81). Conclusions: To enable timely referrals to palliative care interventions, further research is required to develop or validate prognostic models that consider the evolving landscape of AdHF management.

Evaluating the OpenAI's GPT-3.5 Turbo's performance in extracting information from scientific articles on diabetic retinopathy.

We aimed to compare the concordance of information extracted and the time taken between a large language model (OpenAI's GPT-3.5 Turbo via API) against conventional human extraction methods in retrieving information from scientific articles on diabetic retinopathy (DR). The extraction was done using GPT3.5 Turbo as of October 2023. OpenAI's GPT-3.5 Turbo significantly reduced the time taken for extraction. Concordance was highest at 100% for the extraction of the country of study, 64.7% for significant risk factors of DR, 47.1% for exclusion and inclusion criteria, and lastly 41.2% for odds ratio (OR) and 95% confidence interval (CI). The concordance levels seemed to indicate the complexity associated with each prompt. This suggests that OpenAI's GPT-3.5 Turbo may be adopted to extract simple information that is easily located in the text, leaving more complex information to be extracted by the researcher. It is crucial to note that the foundation model is constantly improving significantly with new versions being released quickly. Subsequent work can focus on retrieval-augmented generation (RAG), embedding, chunking PDF into useful sections, and prompting to improve the accuracy of extraction.

Prognostic Factors of Mortality in Nonchronic Obstructive Pulmonary Disease Chronic Lung Disease: A Scoping Review.

Introduction: Patients with chronic lung disease (CLD) experience a heavy symptom burden at the end of life, but their uptake of palliative care is notably low. Having an understanding of a patient's prognosis would facilitate shared decision making on treatment options and care planning between patients, families, and their clinicians, and complement clinicians' assessments of patients' unmet palliative needs. While literature on prognostication in patients with chronic obstructive pulmonary disease (COPD) has been established and summarized, information for other CLDs remains less consolidated. Summarizing the mortality risk factors for non-COPD CLDs would be a novel contribution to literature. Hence, we aimed to identify and summarize the prognostic factors associated with non-COPD CLDs from the literature. Methods: We conducted a scoping review following published guidelines. We searched MEDLINE, Embase, PubMed, CINAHL, Cochrane Library, and Web of Science for studies published between 2000 and 2020 that described non-COPD CLD populations with an all-cause mortality risk period of up to three years. Only primary studies which reported associations with mortality adjusted through multivariable analysis were included. Results: Fifty-five studies were reviewed, with 53 based on interstitial lung disease (ILD) or connective tissue disease-associated ILD populations and two in bronchiectasis populations. Prognostic factors were classified into 10 domains, with pulmonary function and disease being the largest. Older age, lower forced vital capacity, and lower carbon monoxide diffusing capacity were most commonly investigated and associated with statistically significant increases in mortality risks. Conclusions: This comprehensive overview of prognostic factors for patients with non-COPD CLDs would facilitate the identification and prioritization of candidate factors to predict short-term mortality, supporting tool development for decision making and to identify high-risk patients for palliative needs assessments. Literature focused on patients with ILDs, and more studies should be conducted on other CLDs to bridge the knowledge gap.

Perceived Roles and Barriers in Delivering Community-Based Care: A Qualitative Study of Health and Social Care Professionals.

Introduction: As healthcare systems increasingly embrace population health management, the integration of health and social care to improve the health and well-being of individuals is crucial. Thus, we conducted a qualitative study in Singapore to understand health and social care professionals' (HCPs and SCPs) perception of the roles they played in delivering community-based care. Methods: A descriptive phenomenological research design was adopted. HCPs and SCPs (n = 53) providing services in community settings were recruited purposefully and interviewed through eleven focus group discussions. Each session was recorded and transcribed. Thematic analysis was applied. Results: Our results revealed eight themes in three main categories describing the roles played by HCPs and SCPs, including: (1) delivering needs-based care in community settings; (2) activating and empowering clients in health care, and (3) fostering community-based sustainable support networks. Six barriers encountered while performing these roles were also identified. Discussion and Conclusion: Our results highlight that the roles of HCPs and SCPs go beyond the provision of direct medical and social care. They were involved in activating and empowering clients to take care of their health, and importantly, fostering community-based sustainable support networks to better empower individuals in coping with health challenges. The identified barriers shed light on areas for potential improvements for integrated community care.

Risk factors for incident falls in Singaporean community-dwelling adult men and women: a prospective cohort study.

OBJECTIVES: Our study aimed to identify the risk factors of incident falls between men and women. DESIGN: Prospective cohort study. SETTING: The study recruited participants from the Central region of Singapore. Baseline and follow-up data were collected via a face-to-face survey. PARTICIPANTS: Community-dwelling adults aged 40 years and above from the Population Health Index Survey. OUTCOME MEASURE: Incident falls were defined as the experience of a fall between the baseline and 1-year follow-up but having no falls 1 year prior to baseline. Multiple logistic regressions were performed to determine the association of sociodemographic factors, medical history and lifestyle with incident falls. Sex subgroup analyses were conducted to examine sex-specific risk factors for incident falls. RESULTS: 1056 participants were included in the analysis. At 1-year follow-up, 9.6% of the participants experienced an incident fall. Incidence of falls in women was 9.8% compared with 7.4% in men. In the multivariable analysis for the overall sample, older age (OR: 1.88, 95% CI: 1.10 to 2.86), being pre-frail (OR: 2.13, 95% CI: 1.12 to 4.00) and having depression or feeling depressed/anxious (OR: 2.35, 95% CI: 1.10 to 4.99) were associated with higher odds for incident falls. In subgroup analyses, older age was a risk factor for incident falls in men (OR: 2.68, 95% CI: 1.21 to 5.90) and pre-frail was a risk factor for incident falls in women (OR: 2.82, 95% CI: 1.28 to 6.20). There was no significant interaction effect between sex and age group (p value=0.341) and sex and frailty status (p value=0.181). CONCLUSION: Older age, presence of pre-frailty and having depression or feeling depressed/anxious were associated with higher odds of incident falls. In our subgroup analyses, older age was a risk factor for incident falls in men and being pre-frail was a risk factor for incident falls in women. These findings provide useful information for community health services in designing falls prevention programmes for community-dwelling adults in a multi-ethnic Asian population.