Lung carcinoma: its profile and changing trends

BACKGROUND: Lung Carcinoma is the leading causes of morbidity and mortality worldwide with an incidence of 1.3 million cases per year. This study was undertaken to determine prevalence of various histological types of lung carcinoma and to analyse their changing trends with time. METHODS: This is a retrospective analytical study. A total of 330 cases of lung carcinoma were analysed from 2003 to 2008. Cases from Khyber Pakhtunkhwa and Federally Administered Tribal Area (FATA) were included in this study. Furthermore, only cases of lung carcinoma were considered while other malignancies were excluded. RESULTS: Squamous Cell carcinoma was found in 42.7% of cases. Overall male to female ratio was 2.67:1. Prevalence of Squamous Cell carcinoma increased from 32% to 57.9% while that of Small Cell carcinoma increased from 12% to 17.1%. Unspecified type showed decrease from 36% to 5.3%. Increase in the prevalence of Squamous Cell carcinoma was found in both males and females while change in the prevalence of Small Cell carcinoma was found on!y in males. CONCLUSION: Squamous Cell carcinoma was the most prevalent variant of lung carcinoma in our region, followed by Adenocarcinoma. Male to female ratio across different histological patterns did not show significant variation. Increase in the prevalence of Squamous Cell carcinoma was statistically significant in both males and females while in case of Small Cell carcinoma change in its prevalence was also significant in males

General practitioner\u27s knowledge regarding the diagnosis and drug therapy for acute myocardial infarction

OBJECTIVE: To assess the general practitioners (GP) knowledge regarding the diagnosis and initial drug therapy for acute myocardial infarction (AMI). METHODS: A questionnaire-based survey was conducted in randomly selected GPs of Karachi. Doctors working in community as GPs who were registered medical practitioners having a Bachelor of Medicine & Bachelor of Surgery degree were included in the study. Doctors working at tertiary care facilities or having a post graduate degree or post graduate training in a specialty other than family medicine were excluded from the study. RESULTS: A total of 186 GPs participated in our study. GPs who studied research journals were 2.33 times more likely to investigate serum cardiac troponins levels for the diagnosis of AMI compared to those who did not study research journals (P = 0.02). Twenty six percent of the GPs said that they would refer a patient with suspected AMI without treatment, while 76% said that they would consider some treatment prior to referral. Fifty eight percent of the GPs identified ST segment elevation myocardial infarction (STEMI) of \u3c 12 hours duration as an indication of thrombolysis while 28% identified posterior wall AMI as a thrombolytic indication. CONCLUSION: GPs, although adequately aware of the presenting features of AMI, were lacking in knowledge regarding the means for confirmation of diagnosis, initial drug therapy and were less likely to carry management steps in their practice

The use of folic acid in dengue: Has it any value?

Folic acid is used in dengue patients. Our study aims to compare the duration of recovery of thrombocytopenia in patients with dengue infection who received folic acid and those who did not. We retrospectively reviewed the medical records of adult patients admitted over six years with a diagnosis of dengue. Of 2216 patients, 1464 fulfilled the inclusion criteria. Group A were those patients who received folic acid and group B were those who did not. A total of 1322 (90.3%) patients received folic acid. The mean time period required for platelets to double the nadir was 1.7 (±2.2) days in both groups A and B ( P = 0.89). In conclusion, there is no significant difference in the recovery of thrombocytopenia in patients with dengue fever who received folic and those who did not receive folic acid

Frequency of Complications Following Cataract Surgery in Diabetic Patients at Tertiary Care Hospital

OBJECTIVES: To determine the frequency of complications following cataract surgery in diabetic patients admitted in the ophthalmology unit. METHODOLOGY: A prospective descriptive interventional case series study was conducted after approval of the ethical committee, from June 2017-June 2020 at the Ophthalmology department MTI-MMC. A total of 129 patients from either gender were enrolled in study. All the study patients went through detailed history and complete ocular examination. After necessary investigations, surgical procedure was carried out. Results were analyzed through the SPSS-24 version. RESULTS: Out of the total 129 eyes of the diabetic patients, fifty-nine (45.7%) were males and seventy (54.3%) were females with a ratio of 1:1.2. Uveitis leads the chart in complications found in twenty (15.50%) eyes while PODR being the least common found in only ten (7.75%) eyes. Worse visual acuity was observed in fourteen (10.85%) eyes. Striate keratopathy and posterior capsule opacification were found in sixteen (12.40%) and fifteen (11.62%) eyes respectively. Among the patients, 15.7% were having more than one complication during follow-up visits and eighty-eight (68.2%) eyes were found to have none complication. The age group 51-60 years observed frequent complications as compared to other groups. Similarly female gender (38.57%) has frequent complications as compared to males (2.7%). CONCLUSION: The study concludes Uveitis as the most common complication observed in 15.50% 0f the eyes while worse visual acuity (10.85%) and progression of diabetic retinopathy (7.75%) being the least common. Striate keratopathy was found in 12.40% while posterior capsule opacification in 11.62% of the eyes

Reduction in Packaging Wastes Through Identification of Lean Wastes to Deliver Efficient Waste Controlling Techniques for a Pharmaceutical Industry

The purpose of this paper is to propose a method of reducing material and time waste during packaging in the pharmaceutical industry. This is done by means of identifying the four major lean wastes i.e., motion, inadequate processing, waiting, and defects. These wastes are identified and reduced by means of using lean tools and proposing other cost-effective solutions that would increase process efficiency. Material waste is dealt with through selecting optimal requirements under the constraint limits of ergonomics, engineering, and machine space availability. Along with reduction in change over time, a strategy ensuring improvement in the primary packaging area was developed. The validity of this research has been brought about by means of a case study of a multinational pharmaceutical company. The proposed system proves to be highly beneficial in ensuring wastage and time reduction in changeovers. This strategy provides improved results without any new costs introduced and the production targets were met faster. There is also a special consideration given to the ergonomic aspect of the production processes

Designing an IT-Based System for Optimizing Lung Cancer Management

Digital health offers lung cancer patients to improve their health status while allowing patients, providers, and administrators to coordinate data and care at individual and community levels. While technology improvements provide lung cancer patients and healthcare providers with a valuable new tool for disease management, these are yet to be widely accepted. In particular, we aim to: (1) develop a Machine Learning (ML)-based framework for data collection from active online lung cancer forums and other parameters for patients, providers and their organizations, (2) build an AI-based model to develop a cancer ontology for exploring different factors and patients’ emotions associated to lung cancer management, (3) Design a mHealth app to set up a support system in terms of providing patients with information and social support, and ML models-based treatment recommendation system. The IT-based support system will provide the best and most specific treatment plan and recommendation system for lung cancer management

PsyRA – A Retrieval-Augmented Dialogue System for Mental Health Support

Mental health support continues to face numerous challenges, including limited access to care, persistent social stigma, and a shortage of trained mental health professionals. In response to these issues, this paper introduces PsyRA, an innovative AI-powered system designed to enhance psychological assessments through a specialized retrieval-augmented generation (RAG) approach. Unlike conventional chatbots that often fail to capture the nuanced context of patient interactions, PsyRA leverages domain-specific psychological knowledge to deliver more accurate and in-depth assessments. It draws from a carefully curated knowledge base that includes psychological research, diagnostic guidelines, therapy exercises, and intervention strategies to inform its responses and suggestions. PsyRA is equipped to understand patient narratives more clearly, provide evidence-based assessments by retrieving relevant psychological information, and offer personalized intervention recommendations tailored to individual needs. Early evaluations indicate that PsyRA is capable of detecting subtle emotional cues within patient conversations and responding in alignment with established psychological practices. The system demonstrates promising potential to broaden access to mental health support, assist professionals in the assessment process, and reduce the barriers that often prevent individuals from seeking treatment. This work contributes to the expanding field of AI-assisted mental health care by illustrating how retrieval-based models can enhance both the depth and quality of psychological assessments, offering improved emotional sensitivity and reliable, evidence-driven guidance

PsyRA – A Retrieval-Augmented Dialogue System for Mental Health Support

Mental health support continues to face numerous challenges, including limited access to care, persistent social stigma, and a shortage of trained mental health professionals. In response to these issues, this paper introduces PsyRA, an innovative AI-powered system designed to enhance psychological assessments through a specialized retrieval-augmented generation (RAG) approach. Unlike conventional chatbots that often fail to capture the nuanced context of patient interactions, PsyRA leverages domain-specific psychological knowledge to deliver more accurate and in-depth assessments. It draws from a carefully curated knowledge base that includes psychological research, diagnostic guidelines, therapy exercises, and intervention strategies to inform its responses and suggestions. PsyRA is equipped to understand patient narratives more clearly, provide evidence-based assessments by retrieving relevant psychological information, and offer personalized intervention recommendations tailored to individual needs. Early evaluations indicate that PsyRA is capable of detecting subtle emotional cues within patient conversations and responding in alignment with established psychological practices. The system demonstrates promising potential to broaden access to mental health support, assist professionals in the assessment process, and reduce the barriers that often prevent individuals from seeking treatment. This work contributes to the expanding field of AI-assisted mental health care by illustrating how retrieval-based models can enhance both the depth and quality of psychological assessments, offering improved emotional sensitivity and reliable, evidence-driven guidance