Background: Depression and anxiety are common in patients with chronic respiratory diseases (CRDs), but their prevalence in intensive care settings, particularly in low-resource regions, remains underexplored. Objective: To assess the prevalence and severity of depression and anxiety in patients with CRDs admitted to an intensive care unit (ICU) and identify associated factors. Methods: A cross-sectional study was conducted at Gulab Devi Teaching Hospital, Lahore, Pakistan. Adult patients with CRDs admitted to the ICU were assessed using the Hamilton Depression Rating Scale. Statistical analyses included Fisher’s exact test, Mann–Whitney/Kruskal–Wallis tests, and logistic regression. Results: Depression was highly prevalent across all CRD categories: 83%, 89%, 84%, and 93% in obstructive, restrictive, infectious, and other respiratory disease categories, and severe depression in 16%, 18%, 14%, and 37%, respectively. Anxiety symptoms were also widespread (77–100%), with no significant differences across disease groups. Depression was significantly associated with older age (p < 0.001, OR 1.08) and anxiety symptoms (p < 0.001, OR 47.07). Female gender was linked to anxiety (p = 0.034, OR 4.17). Conclusion: The high burden of depression and anxiety in ICU patients with CRDs underscores the need for routine psychiatric screening and integrated mental health care in critical-care settings.

Background: Mechanically ventilated patients constitute a high-risk population in intensive care units (ICUs), where a combination of clinical, physiological, and demographic variables frequently determines mortality. Early identification of these predictors is critical to inform therapeutic strategies and improve survival outcomes. Objective: To determine the association of clinical, physiological, and demographic parameters with mortality among patients receiving invasive mechanical ventilation in a tertiary care ICU in Pakistan. Study Design: Descriptive cross-sectional study. Settings: Chest Intensive Care Unit, Gulab Devi Teaching Hospital, Lahore, Pakistan. Duration of Study: August 2023 to January 2024. Methods: A total of 60 adult patients (aged <70 years) who underwent invasive mechanical ventilation were enrolled through non-probability convenience sampling. Demographic characteristics, comorbidities, clinical diagnosis, and indications for intubation were recorded. Post-intubation parameters—including arterial pH, PaO₂/FiO₂ ratio, and Richmond Agitation-Sedation Scale (RASS) scores—were analyzed. The primary endpoint was in-hospital mortality. Statistical analysis was performed using SPSS version 26, with a significance threshold of p<0.05. Results: The in-hospital mortality rate was 75% (n=45), while 25% (n=15) of patients were successfully extubated. No significant correlation was found between mortality and demographic factors such as age (p=0.257), gender (p=0.620), or weight (p=0.389). However, significant predictors of mortality included the underlying reason for intubation (p=0.019), particularly low Glasgow Coma Scale scores and cardiac arrest. Comorbid conditions such as diabetes mellitus (p=0.015) and cardiac disease (p=0.030) were also significantly associated with mortality. Moreover, post-intubation arterial pH (p=0.021), PaO₂/FiO₂ ratio (p=0.021), and RASS scores (p=0.000) demonstrated strong associations with adverse outcomes. Conclusion: The etiology of intubation, pre-existing comorbidities, and early post-intubation physiological parameters significantly influence mortality among mechanically ventilated patients. Proactive recognition and targeted management of these predictors may enhance survival outcomes in critically ill ventilated patients.

Background: This study aimed to identify factors influencing non-invasive ventilation (NIV) outcomes in patients with hypercapnic respiratory failure due to various respiratory conditions in a resource-limited intensive care unit (ICU) setting. These predictors can guide us in the prompt decision of ventilation, resulting in better outcomes. Methods: Patients requiring NIV for hypercapnic respiratory failure of any cause were included. Arterial blood gases were measured at 1 and 24 h, and an improvement in pH ≥ 7.35 was taken as a cut-off for early and late physiological responses, respectively. Binary regression analysis was used to identify predictors of physiological response, need for mechanical ventilation, and mortality. Results: Among 226 patients (139 males), the underlying causes were obstructive (71%), restrictive (25%), and infective disorders (4%). Older age, higher one-hour PCO₂, FiO_2, and respiratory rate were associated with increased mortality. Late physiological response correlated with higher IPAP and WBC counts, while higher WBC counts also predicted need for mechanical ventilation on binary logistic regression. Conclusions: Higher one-hour PCO₂, older age, higher FiO₂, respiratory rate, WBC count, and IPAP predicted an unfavorable outcome of NIV in acute hypercapnoic respiratory failure. Locally generated data can support timely escalation to mechanical ventilation and inform patient selection for initial NIV therapy in resource-limited settings.