Publications by authors named "M A Bains"

Objective: Evaluate an electronic platform for remote symptom monitoring to enhance postdischarge care in thoracic surgery using patient reporting of symptoms.

Summary Background Data: Owing to the increased use of enhanced recovery after surgery protocols, patients are spending a larger portion of their postoperative course at home. For patients undergoing complex operations, this represents an opportunity for early identification of abnormal symptoms at home before deterioration.

View Article and Find Full Text PDF

Rationale: Asthma attacks (AA) are potentially life-threatening complications of asthma associated with high levels of morbidity, mortality and rising healthcare costs. Patient experience, impact and understanding of AA is poorly described in the literature. Enhanced understanding will identify unmet needs in asthma care and support the development of improved personalised strategies for managing and preventing attacks.

View Article and Find Full Text PDF

Background: Modelling shows smokefree generation (SFG) policies could effectively reduce smoking rates by banning tobacco sales to those born after a specific year. Little is known about how young people perceive the legitimacy and impact of the planned SFG policy in England.

Methods: We conducted 7 semi-structured focus groups with 36 participants aged 12 - 21 (mean = 15) in England over video call and in person.

View Article and Find Full Text PDF

Introduction: People living at home with dementia are often cared for by family members, especially those from minority ethnic groups. Many people living with dementia from minority ethnic communities face barriers to accessing formal care. However, there is a paucity of dementia research, which foregrounds diversity within minority ethnic populations.

View Article and Find Full Text PDF
Article Synopsis
  • The study aimed to create a prediction model to help decide between stereotactic body radiotherapy (SBRT) and minimally invasive surgery (MIS) for treating early-stage non-small cell lung cancer (NSCLC).
  • Researchers analyzed data from 1,291 patients to develop the model using logistic regression, which produced three risk categories for patient treatment based on several health factors.
  • The model showed strong predictive power and suggested that the decision on treatment modality does not significantly impact overall survival, highlighting the importance of assessing intermediate-risk patients through a multidisciplinary approach.
View Article and Find Full Text PDF