Predicting successful liberation of patients from mechanical ventilation has been a focus of interest to clinicians practicing in intensive care. Various weaning indices have been investigated to identify an optimal weaning window. Among them, the rapid shallow breathing index (RSBI) has gained wide use due to its simple technique and avoidance of calculation of complex pulmonary mechanics. Since its first description, several modifications have been suggested, such as the serial measurements and the rate of change of RSBI, to further improve its predictive value. The objective of this paper is to review the utility of RSBI in predicting weaning success. In addition, the use of RSBI in specific patient populations and the reported modifications of RSBI technique that attempt to improve the utility of RSBI are also reviewed.

Lung ultrasound is a point-of-care imaging tool that is routinely used in acute care medicine. Traditionally, radiology physicians were the primary practitioners of diagnostic ultrasound, but with the recognition of its importance in intensive care medicine, critical care physicians have also adopted this practice. Within the intensive care unit inter-professional team is the respiratory therapist, who participates actively in the care of ventilated patients. Their scope of responsibility is expanding with newer technologies being brought into clinical use on a regular basis. This review focuses on the scope and benefits of ultrasound training within respiratory care–related areas.

The evolution of artificial intelligence (AI) has revolutionised numerous aspects of our daily lives, with profound implications across various sectors, including healthcare. Although the concept of AI in healthcare was introduced in the early 1970s, the integration of this technology in healthcare is still in the evolution phase. Despite barriers, the current decade is witnessing an increased utility of AI into diverse specialities of the medical field to enhance precision medicine, predict diagnosis, therapeutic results, and prognosis; this includes respiratory medicine, critical care, and in their allied specialties. AI algorithms are widely studied in areas like mechanical ventilation, sleep medicine, lung ultrasound, and pulmonary function diagnostics and the results are found to be promising. The quality of patient care and safety can be greatly enhanced if respiratory care professionals fully understand the concept and importance of AI, as they are already incorporating various aspects of this technology into their clinical practice. Awareness of AI in the clinical field is essential during this phase; hence, it is desirable to establish widely accepted standards presented in a clear and accessible language. This article aims to describe the existing and prospective role of AI in the field of respiratory care and allied areas.

The word “quality” refers to the features of a product or service to which a certain value is ascribed. When it comes to hospital-based practices, quality has often been considered to be specific to the care provided. However, this specific perspective is transitioning toward a broader concept after the evolution of quality-improvement projects and quality frameworks at the organizational level. Respiratory therapy departments have been identified as an essential part of any hospital because the key nature of discipline for respiratory therapists is widely understood. Due to their professional accountability and professional values, respiratory therapists often have administrative roles in infection control practices and quality-improvement projects. Therefore, it would be ideal to have a core team of respiratory therapists trained in quality management and to initiate quality-improvement processes at the departmental level. Every respiratory therapy department should have its own quality-improvement team to assist with the process of training, implementation, and analysis. Thus, this article aimed to discuss the role of respiratory therapists and respiratory therapy departments in quality-improvement processes and projects to set benchmarks and enhance outcomes.

Over the past ten years, significant transformations have occurred in the healthcare landscape, presenting respiratory therapists (RTs) with a mix of challenges and opportunities. Hence, their perceptions about career progression and job satisfaction will be critical factor in determining the recruitment and retention of RTs. However, there are no studies in the literature that comprehensively assessed these aspects using a reliable and valid measure specific to RTs. Our objective was to develop and psychometrically test a Standardized Questionnaire (SQ) for evaluating RT's overall job satisfaction. Following consultations with experts and interviews conducted with RTs, a preliminary questionnaire was devised for the purpose of exploratory factor analysis (EFA). The 49 items of the Structured Questionnaire (SQ) were used for verification of the theorized factor structure and content validity using a confirmatory factor analysis (CFA). Principal Component Analysis (PCA), Structural Equation Modeling (SEM), and Confirmatory Factor Analysis (CFA) for the global fit were done. Cronbach's alpha was performed to estimate the internal consistency. The samples of RTs were collected from India between August 2021 and January 2022. A convenience sample comprising 409 respiratory therapists (RTs) employed in India participated in the survey conducted from June 2021 to January 2022. The exploratory factor analysis revealed three factors that explained 61.2 % of the total variance. The confirmatory factor analysis yielded a 3-factor structure (X2/df = 4.4, p < 0.02, standardized root-mean-square residual = 0.05, goodness of fit index = 0.94, comparative fit index = 0.98). The Cronbach's alpha was 0.94 for the total scale. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) are becoming more prevalent, especially in the development and psychometric evaluation of instruments. This Structured Questionnaire is a reliable and valid tool that has utility for assessing perceptions, satisfaction, and attitude among Respiratory Therapists and for making comparisons of similar psychometric measures.

Arterial and Venous Estimation of Hemoglobin: A Correlational Study