Hospital Patient Research Articles

Assessment of the value and findings of CT in diagnosing acute appendicitis

Appendicitis is one of the most common abdominal emergencies. Patients are usually presented with lower right abdominal pain, nausea, vomiting and fever. Acute appendicitis is a challenging clinical diagnosis, and patients with suspected appendicitis can be diagnosed by Ultrasound (US) or computed tomography (CT) according to the hospital protocol and patient clinical condition. The aim of this study is to investigate the value of CT in diagnosing suspected cases of acute appendicitis. Retrospective research to evaluate the role of CT scan in the diagnosis of acute appendicitis, based on data received from King Abdulaziz university hospital in Jeddah, from January 2017 to January 2022. A total of 204 patients (121 Males and 83 Females) ranging in age from 2 to 91 years presented with acute appendicitis were included. The collected data included age, gender, patients' complaints, medical history, laboratory tests, radiology reports, operations, and pathological results. The most prevalent age group was 10-30 years old. Most patients (77%) presented with typical appendicular pain, while (56%) presented with vomiting. CT was requested for 142 patients while 35 patients were referred to Ultrasound. Both modalities were done to 27 patients. The Commonest finding in CT scan was dilated appendix with sensitivity of 84% with 100% overall diagnostic sensitivity. CT is a sensitive tool used to diagnose acute appendicitis and its complications. It is recommended to be used as the primary imaging modality in cases of acute appendicitis.

Developing a Green Nursing Practice in a Profession That Contributes to Climate Change: One Nurse's Journey.

The health care industry accounts for 5% of global greenhouse gas emissions, with hospitals being the largest contributor. Critical care units create 3 times the greenhouse emissions of other hospital patient care units. Health care contributions to environmental harm include medical waste disposal, toxicant exposure, and pollutants. Integrating green practices into hospitals, especially in intensive care units, can seem overwhelming, with barriers including time constraints, lack of leadership and organizational support, and ignorance of green practices. Nursing is a socially responsible discipline committed to improving the health of individuals and communities; values of environmental stewardship and the desire to minimize poor health outcomes caused by climate change do not always align with hospital policies or clinician practices. This article addresses how nurses can confront the complex environmental problems in the workplace, apply sustainability principles to develop a green nursing practice, and collectively influence the future of national and global health.

A stochastic optimisation model to support cybersecurity within the UK national health service

Over the past decade, the adoption of new digital technologies in healthcare has surged, significantly enhancing care delivery and accessibility. However, this digital transformation has been accompanied by a sharp increase in cyber-attacks, posing severe risks to hospital functionality and patient safety. To address the challenge of planning for uncertain future cyber incidents, we propose a two-stage stochastic model designed to bolster the cyber resilience of healthcare providers by selecting optimal countermeasures in preparation for upcoming cyber incidents. Numerical tests demonstrate the model’s effectiveness, with the Value of the Stochastic Solution showing a 21% improvement over a deterministic approach. To be optimally equipped even for low-probability high-impact attacks we incorporate the risk measure Conditional Value-at-Risk. The corresponding countermeasure solution led to 44% fewer rejected patients in a worst-case scenario. The robustness of the proposed solution is underscored by its consistent performance across various scenarios, budget levels, and risk preferences, making it a reliable tool for enhancing cybersecurity in healthcare. These results highlight the importance of tailored, robust cybersecurity strategies in healthcare, ensuring preparedness for a wide range of potential threats.

Optimal Timing for Postanesthesia Care Unit Discharge Using Physiological-Based Criteria in In-Patients Undergoing Low-Risk Surgery with General Anesthesia: A Prospective Observational Study

Objective: All postanesthesia patients must be monitored in the postanesthesia care unit (PACU) until they meet PACU discharge protocols. These included both physiological-based discharge (PBD) criteria and time-based discharge (TBD) criteria. The efficacy of using only PBD criteria to determine PACU discharge remains unclear. Therefore, this study aimed to determine the optimal timing for PACU discharge using PBD criteria alone for in-hospital patients undergoing low-risk surgeries. Material and Methods: This was a prospective observational study, involving 532 patients who had undergone elective low-risk surgery under general anesthesia (GA). At the PACU, the following data points were recorded: patient demographics, anesthesia and surgical data, the time required to meet PBD criteria, the actual PACU discharge time, complications during PACU admission, and causes of delayed PACU discharge. This study analyzed the comparison between the average time to meet PBD criteria and the ‘actual’ PACU discharge time. Results: A total of 532 patients admitted to the PACU were enrolled in this study. The mean PBD time was 12.6± 8.4 minutes, and the mean actual PACU time was 65.1±15.5 minutes: a difference that was statically significant [mean difference 52.5 (51.1, 54.0) minutes, p-value<0.001]. No severe complications were observed. Severe pain was the most recorded complication during PACU admission. The highest cause of delayed PACU discharge was the unavailability of hospital patient transporters. Conclusion: The PACU discharge time for in-hospital patients undergoing low-risk surgery under GA, based on PBD criteria, was significantly shorter than that based on TBD criteria; additionally, no severe complications were reported.

Impact of pay-for-performance on hospital readmissions in Lebanon: an ARIMA-based intervention analysis using routine data

BackgroundThe objective of this paper was to estimate the impact of country-wide hospital pay-for-performance on readmissions for a set of common conditions in Lebanon.MethodsThis retrospective cohort study included all hospitalizations under the coverage of the Ministry of Public Health in Lebanon between 2011 and 2019. We calculated 30-day all-cause readmissions following general, pneumonia, cholecystectomy and stroke cases. We used an interrupted time series design, including the use of AutoRegressive Integrated Moving Average models. This nationwide study including 1,333,691 hospitalizations was undertaken in Lebanon, using hospitalizations at about 140 private and public hospitals contracted by the Ministry. The participants included citizens across all ages under the Ministry’s coverage (52% of citizens). The intervention was the engagement of hospital leaders by the Ministry, informing them of the addition of a readmissions component to the ongoing pay-for-performance initiative. Engagement participants included hospital directors and managers, and the leadership of the Syndicate of Private Hospitals. The main outcome measure was age-adjusted monthly all-cause readmission rates for each of general, pneumonia, cholecystectomy and stroke cases. We also assessed for change in readmissions for three conditions not included in the intervention (myocardial infarction, cataract surgery and appendectomy).ResultsAcross 2011–2019, the overall readmission rates were 6.00% (SD 0.24%) for general readmissions, 5.06% (SD 0.22%) for pneumonia, 2.54% (SD 0.16%) for cholecystectomy, and 6.55% (SD 0.25%) for stroke. Using ARIMA models we found a relative percentage decrease in mean monthly readmissions in the post-intervention period for cholecystectomy (5.9%; CI 0.1%-11.8%) and stroke (13.6%; CI 3.1%-24.2%). There was no evidence of intervention impact on pneumonia and general readmissions, both overall and among small, medium and large hospitals. There was also no evidence of change in non-P4P readmissions of myocardial infarction, cataract surgery and appendectomy.ConclusionsIncluding readmissions within pay-for-performance has the potential to improve hospital performance and patient outcomes, even in countries with more limited resources. Effects may vary across conditions, indicating the need for careful design and understanding of the particular context, both with respect to implementation and to evaluation of impact.

Imaging-Guided Subthalamic Nucleus Deep Brain Stimulation Programming for Parkinson Disease: A Real-Life Pilot Study.

Deep brain stimulation (DBS) is a well-established treatment for Parkinson disease (PD), with programming methods continually evolving. This study aimed to compare the efficacy and patient burden between conventional ring-mode programming (CP-RM) and image-guided volume of tissue activated (IG-VTA) programming for subthalamic nucleus (STN) DBS in PD. In this retrospective study, patients with PD who underwent STN-DBS between 2011 and 2014 (CP-RM group) and 2019 and 2021 (IG-VTA group) were evaluated. The primary outcome was the improvement in the UPDRS III score from preoperative OFF to postoperative ON state without medication at one-year follow-up. Secondary outcomes included hospital stay duration and programming sessions. A total of 26 patients were analyzed (IG-VTA: n = 12, CP-RM: n = 14). Both groups showed similar improvements in UPDRS III scores (IG-VTA: 43.62, CP-RM: 41.29). However, the IG-VTA group experienced shorter immediate postoperative hospital stays and fewer hospitalizations after discharge. IG-VTA programming preserved the clinical efficacy of STN-DBS over 1 year and reduced the patient and clinician burden of hospital stay and programming sessions. However, conclusions drawn must consider the limitations of retrospective design, differing time epochs, and evolving clinical practices. Further multicentric and prospective studies are warranted to validate these findings in the evolving field of neurostimulation. The trial is registered on clinicaltrials.gov (NCT05103072).

Implementation of fuzzy logic approach for thalassemia screening in children

Thalassemia is one of the most dangerous blood disorders that can lead to severe complications. It is an inherited disease, usually detected after a child is two to four years old. Identification of thalassemia is a complex task, involving many variables. Doctors generally diagnose thalassemia by using a complete blood count (CBC) and high-performance liquid chromatography (HPLC) test results. However, HPLC tests are expensive and time consuming, hence the need for other methods to identify thalassemia. There are many studies on the application of artificial intelligence for medical applications. In this study, we developed a new fuzzy-based approach to identify thalassemia based on a patient’s blood laboratory results. First, we analyzed the CBC data for blood disorder prediction. Secondly, we adopt the test results of peripheral blood smear (PBS) to identify whether the person has thalassemia. We conducted several experiments using 30 (thirty) hospital patient data and the results were compared with the results provided by experts. The experimental results show that the system can determine blood disorders with 93% accuracy and 100% precision in thalassemia prediction. This system is very effective to help doctors in diagnosing thalassemia patients.

What is the relationship between hospital management practices and quality of care? A systematic review of the global evidence.

There is a widely held view that good management improves organisational performance. However, hospitals are complex organisations and the relationship between management practices and health service delivery is not straightforward. We conducted a global, systematic literature review of the quantitative evidence on the link between the adoption of management practices and quality of care in hospitals. We searched in PubMed, EMBASE, EconLit, Global Health and Web of Science on 16th October 2024, without language or country restrictions. We included empirical studies from January 1, 2000, onward, examining the quantitative association between hospital management practices and quality of care. Outcomes included structural quality (availability of resources such as drugs and equipment), clinical quality (adherence to guidelines), health outcomes and patient satisfaction or experience with care. In every study, each tested association was categorised as significantly positive (at the 5 percent level), null or significantly negative. The study was registered with PROSPERO (CRD42022301462). Of 11,731 articles, 25 studies met the inclusion criteria and had acceptable risk of bias. Studies were equally distributed between high-income and low- and middle-income countries, with 22 cross-sectional and three intervention studies. Of 111 associations, 55 (49.5%) were significantly positive, 1 (1%) was significantly negative, and 55 (49.5%) were null. Among associations tested, the majority were significantly positive for structural quality (79%), clinical quality (60%) and health outcomes (57%), while most associations between hospital management and patient satisfaction (80%) were null. The findings are mixed, with a similar proportion of positive and null associations between management practices and quality of care across studies. The evidence is limited by risk of bias introduced by non-randomised study designs. Evidence of positive associations in some settings warrants further investigation of the association through intervention studies or natural experiments. This could leverage methodological developments in quantitatively measuring management, highlighted by this review.

Strategies for Effective Health Services Management in Hospitals: A Systematic Review of Key Models and Practices

Background: Effective health services management is critical in hospitals, where the demands for improved patient outcomes, operational efficiency, and cost containment are paramount. Over the years, several management models and practices have been implemented in hospital settings, with varying degrees of success. Objective: This systematic review aims to examine and synthesize key models and practices in health services management that have proven effective in enhancing hospital performance, focusing on their impact on patient care, staff efficiency, and operational outcomes. Methods: A systematic literature search was conducted across major databases, including PubMed, Scopus, and Google Scholar, using keywords such as "hospital management," "health services management," and "patient care models." Studies were included if they focused on hospitals, were published in the past ten years, and evaluated the effectiveness of management practices. Results: The review identified several effective management models, including Lean Management, Six Sigma, Patient-Centered Care, Workflow Optimization, and Total Quality Management (TQM). Key practices contributing to successful management included leadership engagement, technology integration, performance measurement, and patient safety protocols. These strategies collectively improved patient satisfaction, reduced wait times, and enhanced hospital efficiency. Conclusion: This review highlights evidence-based management strategies that have a significant impact on hospital operations and patient care. Implementing these practices can help hospital administrators optimize resources, improve staff productivity, and enhance patient experiences.

Quantifying the potential contribution of drugs to the occurrence of acute kidney injury in patients with chronic kidney disease

Abstract Background We sought to comprehensively describe drug-related components associated with AKI in patients with CKD, describing the incidence of drug-related AKI, the proportion of preventable AKI, identified the various drugs potentially associated with it, explored the risk factors, and assessed the one-year incidences of the recurrence of drug-related AKI, kidney failure, and death. Methods CKD-REIN is a French national prospective cohort of 3,033 nephrology outpatients with a confirmed diagnosis of CKD (eGFR <60 mL/min/1.73 m²). AKIs and adverse drug reactions (ADRs) were prospectively identified from hospital reports, medical records, and patient interviews. Expert nephrologists used the KDIGO criteria to adjudicate all stages of AKI, and expert pharmacologists used validated tools to adjudicate ADRs (including drug-related AKIs). Results Over a median [interquartile range] period of 4.9 [3.4-5.1] years, 832 cases of AKI were reported in 639 (21%) of the 3,033 study participants. The drug-related component associated with AKI accounted for 236 cases, and 28% were judged to be preventable or potentially preventable. The three most frequently implicated drug classes were diuretics, renin-angiotensin system inhibitors, and contrast agents. A history of cardiovascular events, diabetes, lower levels of hemoglobin and eGFR, poor medication adherence, and ≥ 5 drug taken daily were associated with a greater risk of drug-related AKI. Full recovery was not attained in 64 (27%) of the 236 cases of drug-related AKI. The one-year cumulative incidences of recurrence of drug-related AKI, kidney replacement therapy, and death were 7%, 15%, and 11%, respectively, after the first drug-related AKI. Conclusions Drug-related AKI is prevalent among patients with CKD. Even though a substantial proportion of these events were classified as stage 1, our findings point to a poor prognosis.

Predicting individual patient and hospital-level discharge using machine learning

BackgroundAccurately predicting hospital discharge events could help improve patient flow and the efficiency of healthcare delivery. However, using machine learning and diverse electronic health record (EHR) data for this task remains incompletely explored.MethodsWe used EHR data from February-2017 to January-2020 from Oxfordshire, UK to predict hospital discharges in the next 24 h. We fitted separate extreme gradient boosting models for elective and emergency admissions, trained on the first two years of data and tested on the final year of data. We examined individual-level and hospital-level model performance and evaluated the impact of training data size and recency, prediction time, and performance in subgroups.ResultsOur models achieve AUROCs of 0.87 and 0.86, AUPRCs of 0.66 and 0.64, and F1 scores of 0.61 and 0.59 for elective and emergency admissions, respectively. These models outperform a logistic regression model using the same features and are substantially better than a baseline logistic regression model with more limited features. Notably, the relative performance increase from adding additional features is greater than the increase from using a sophisticated model. Aggregating individual probabilities, daily total discharge estimates are accurate with mean absolute errors of 8.9% (elective) and 4.9% (emergency). The most informative predictors include antibiotic prescriptions, medications, and hospital capacity factors. Performance remains robust across patient subgroups and different training strategies, but is lower in patients with longer admissions and those who died in hospital.ConclusionsOur findings highlight the potential of machine learning in optimising hospital patient flow and facilitating patient care and recovery.

Enhancing Resurrection Practices for Unusable General Inventory Items in Hospital Settings

Background: Effective patient care in hospitals relies on the proper functioning of medical equipment. Malfunctioning general inventory items, such as patient beds, wheelchairs, and saline stands, pose significant challenges to hospital operations and patient care. D.G.H. Negombo needs help maintaining these items due to limited financial resources and inadequate technical expertise.Objective: To improve the resurrection practices of selected unusable general inventory items at D.G.H. Negombo.Methodology: This cross-sectional descriptive study was conducted from August 1, 2022, to November 15, 2023, and involved three phases: pre-intervention (assessment), intervention (implementation), and post-intervention (evaluation). Data collection methods included key informant interviews (K.I.I.), self-administered questionnaires (S.A.Q.), and desk reviews. The study targeted general inventory items marked for condemnation and included unit heads and maintenance technicians in its scope.Results: Pre-intervention assessments identified key issues such as inadequate technical skills, poor coordination, and insufficient infrastructure. Interventions implemented included skill development workshops, improved documentation practices, and enhanced communication strategies. Post-intervention evaluations demonstrated significant improvements in repair times, resource availability, and satisfaction among unit heads. Notably, 78% of wheelchairs, 79% of patient trolleys, and 76% of patient beds were successfully resurrected.Conclusions: The interventions enhanced the resurrection of unusable general inventory items, extended equipment lifespans, and achieved substantial cost savings.

Effective Communication of System-Level Events for Hospital System Health and Nurse Well-Being: A Qualitative Study

Many injuries and deaths occur yearly in the United States due to preventable errors; however, documented harm is lower in hospitals with Magnet® designation from the American Nurses Credentialing Center (Silver Spring, MD, USA). This manuscript illustrates insights from Magnet® and non-Magnet® nurses and nursing leaders regarding what impacts hospital system health, how those factors are communicated, and how hospital system health impacts patient safety. A qualitative descriptive approach was used with semi-structured interview questions. Within-methods data triangulation was applied to transcribed interviews using thematic analysis, application of the Goodwin statistic, and natural language processing (NLP). Thematic analysis revealed the four main themes of Healthy Systems, Unhealthy Systems, Patient Safety, and Nurse Well-Being. NLP revealed non-Magnet® leaders and nurses scored highest for anxiety, anger, and sadness, in contrast to Magnet® participants who had the highest levels of positive emotion. Key findings from the Magnet® participants revealed that poaching employees and placing people in the wrong positions harm hospital system health and patient safety. The use of within-methods data triangulation illuminated the contextual depth of the participants’ speech, revealing the alarming emotional state that non-Magnet® nurses and leaders are facing. Healthcare staff’s wellness must be prioritized to cultivate environments that provide safe care.

Improving the hospital or immunizing its organization? Patient and public involvement at the service of quality.

There is a pressing need for the hospitals to improve their quality and become more patient-centered. Over the last decade, several approaches were implemented to meet this demand, such as hospital accreditation or patient surveys. Many studies have addressed the patient involvement systems from the viewpoint of the factors that drive them or the achieved performance. In this study, we examined the patient involvement from the viewpoint of its function and operation rather than its performance. Following Luhmann, we reconsidered quality to be related to the absorption of uncertainty rather than improvement or innovation. The adaptation of an organization to involve patient participation can be regarded as contributing to the immune function of the organizational system. Three case studies addressing patient and family advisory councils in general hospitals were conducted in Belgium. Qualitative empirical material is retrieved from observation, documentation, and interviews. Our findings suggest that the immune function of the hospital organization operates in four main phases. First, we assess how the communicative process indicates the relevant difference that needs to be addressed. Role differentiation occurs through the depoliticization and depersonalization of criticism. Second, given the impossible realization of first-order observation of the environment, our material shows how second-order observation is organized through a dual representation. Third, we unveil how the environmental representation requires a specific organizational socialization to overcome the representation paradox. Finally, we analyze how the whole described process must fulfil the preparation of a repertoire of responses to the irritations of its environment. The analysis revealed that patient and family advisory councils complete a crucial immune function for organizations, far beyond the simple discussion of the "nuts and bolts" of organizational structure. These findings permit to discuss implications of the notions of participation and quality regarding to identity work of stakeholders, open organization, and change management.

A Fuzzy Logic Approach to Enhance GPS Accuracy for Blood Cooler Box Tracking

An innovative technological development, the position tracking system uses latitude and longitude coordinates to determine the GPS's location. The covid-19 pandemic has caused the demand for cool box delivery for convalescent blood plasma to increase significantly. The obstacle in the field is the hospital's position and patient rooms far from the reach convalescent donors, so they require a cool box for delivery. The problem is tracking the cool box accurately and precisely so that it can be monitored by the hospital properly. For this reason, it is necessary to increase the accuracy of the GPS position in the cool box by using fuzzy logic algorithms The Ublox NEO-6M is one GPS module that can be utilized for navigation. This module uses UART connection using the NMEA 0183 protocol and has an accuracy level of around 2.5 meters to 10 meters. In this research, validation of the accuracy of the GPS coordinate position was carried out on a Blood Cool Box device which was designed using the fuzzy logic method. The Sugeno method fuzzy logic algorithm is used to validate the accuracy of GPS coordinate positions based on latitude and longitude obtained from the GPS sensor module. The test results show a Mean Absolute Percent Error (MAPE) value of 21.66% which can be concluded that the Sugeno fuzzy logic method algorithm has forecasting model capabilities that are suitable for use as a validation method for testing GPS position coordinates.

Clinical outcomes and profitability following rural hospital mergersand acquisitions.

As US hospital markets become increasingly consolidated, empirical evidence is needed on the clinical and financial impacts of mergers on care provided by rural hospitals. We identified characteristics of rural hospitals that underwent mergers or acquisitions and examined changes in profitability, clinical outcomes, and patient experience at acquired versus non-acquired rural hospitals. We identified 145 rural US hospitals that underwent merger or acquisition between 2009 and 2014 and 906 rural non-acquired control hospitals. For each acquisition year, we used a difference-in-differences design to compare that year's acquired hospitals to a randomly chosen set of non-acquired controls. Adjusted linear regression models were used to assess the relationship between acquisition and changes in profitability, patient experience, and clinical outcomes. Compared to non-acquired hospitals, acquired hospitals were more likely to be for-profit (18.6%vs. 4.6%, p<0.001) and tended to have lower total margins (-1.1%vs. 1.2%; p<0.05) despite higher average clinical volumes. Changes in acquired hospitals' total margins, patient satisfaction, and risk-adjusted 30-day mortality rates were not different than changes among control hospitals. However, acquisition was associated with lower improvement in30-day risk-adjusted readmission rates (-0.58 percentage point [p.p.] difference-in-differences, 95% confidence interval -0.88 to -0.28 p.p., p<0.001). Overall, mergers or acquisitions of rural hospitals were not associated with significant improvements in profitability, clinical outcomes, or patient experience. Policymakers may need to closely monitor rural hospital mergers in order to balance preserving access for rural patients with the consequences of health care consolidation.

Analysis of emergency centre recidivism for interpersonal violence in a district-level hospital in Cape Town, South Africa.

Interpersonal violence is a major cause of morbidity and mortality in low- and upper-middle-income countries. It is postulated that a significant portion of these patients have repeated presentations to an already overburdened healthcare system. Data describing the burden of interpersonal violence recidivism are poor. To determine and describe the burden of emergency centre recidivism for interpersonal violent injury presenting to Khayelitsha Hospital, Cape Town, over a 2-year period. An analysis of a prospectively collected observational database combined with a retrospective chart review was conducted of all trauma patients who presented to Khayelitsha Hospital from 1 October 2020 to 30 September 2022. All patients (aged ≥14 years) with ≥2 presentations for interpersonal violence-related injuries were included. Cases were limited to the inclusion of mechanisms of injury attributable to stab wounds, blunt assault, firearm injury and gender-based violence. Recidivist cases were identified by repeat hospital number on the electronic hospital patient system. Repeat cases were manually reviewed for inclusion. Summary statistics are used to describe all variables. In total, 10 218 interpersonal violence presentations were identified over the study period, and 1 125 (11.0%) were attributed to recidivists (522 patients). The mean (standard deviation) age was 30 (7.7) years, and most were male (n=463, 88.7%). Stab wounds (n=583, 51.8%) and blunt assault injuries (n=456, 40.5%) were the main mechanisms of injury. Repeat presentation occurred within a median of 198 (25th - 75th percentile, 81.5 - 373.9) days. A total of 337 (64.6%) patients presented with higher acuity at one of their subsequent visits. Recidivist presentations represent a significant proportion of interpersonally violently injured patients, and are likely to be under-documented. Recidivism poses a measurable burden, and further research is needed to facilitate the identification of at-risk individuals, and specific secondary prevention strategies should be developed to prevent or reduce escalating patterns of injury associated with interpersonal violence.

UNDERSTANDING THE LEVEL OF KNOWLEDGE AMONG NURSES ABOUT FIRE SAFETY IN TERTIARY CARE HOSPITAL LAHORE

Fire safety in healthcare facilities is an important but frequently disregarded part of hospital administration and patient care. Despite substantial study on different aspects of healthcare delivery, there is still a significant gap in understanding and measuring fire safety knowledge and practices among healthcare personnel, particularly in Pakistan's tertiary care facilities. Objective: The purpose of this study was to assess the degree of fire safety knowledge among medical personnel at a tertiary care hospital in Lahore, Pakistan, to identify any shortcomings that may affect their capacity to respond effectively in the event of a fire. Methods: A cross sectional quantitative descriptive study was conducted at Public Tertiary care hospital in Lahore involving 202 nurses. A customized questionnaire was administered to assess the participant’s fire safety knowledge, selected through successive sampling. Data analysis was performed using SPSS version 22.0, categorizing knowledge level as poor, average and good. Results: 85% of survey participants were aware of fire response procedures. However, only 15% knew the fire department contact numbers, and 25% were unaware that foam or water extinguishers are ineffective against grease fires. Additionally, a significant proportion of participants struggled to correctly identify different types of fire extinguishers (65%) and fire categories (50%). The finding underscore the importance of comprehensive fire safety training to address significant knowledge gaps. Conclusions: Healthcare institutions should develop comprehensive fire safety training programs that extend beyond basic emergency protocols. Regular fire drills and simulations should be held to check staff members' understanding and reinforce fire safety procedures. Administrators should examine and update fire safety protocols on a regular basis to reflect new technology, legislation, and lessons learnt from previous events.

Causes of Coronary Angioplasty Denial in Patients Diagnosed with Significant Coronary Artery Disease in East Afghanistan

Coronary Artery Disease (CAD) is a leading cause of mortality worldwide, with coronary angioplasty being a crucial intervention for patients with significant disease. This study aimed to identify and analyze the causes of coronary angioplasty denial in patients with significant coronary artery disease in Afghanistan, focusing on demographic, socioeconomic, and clinical factors. A case-control study was conducted with a sample size of 213 patients diagnosed with significant CAD at tertiary care center in Afghanistan. The case group consisted of 106 patients who were denied angioplasty, and the control group included 107 patients who underwent the procedure. Data were collected on demographic characteristics, comorbidities, education, residence, functional status, income, and the reasons for angioplasty denial. Descriptive statistics and comparative analyses were performed to assess the factors associated with denial. The primary reasons for angioplasty denial were financial constraints (45.3%, p &lt; 0.001), limited hospital facilities (15.1%, p = 0.045), patient refusal (23.6%, p &lt; 0.001), and physician preference for conservative management (12.3%, p = 0.091). Denial rates were higher among patients who were older, had multiple comorbidities, were from rural areas, and had lower education and income levels. Illiteracy and cultural beliefs contributed significantly to patient refusal, while inadequate healthcare infrastructure disproportionately affected rural populations. Financial and infrastructural barriers are the leading causes of coronary angioplasty denial in Afghanistan, exacerbating disparities in healthcare access, particularly among low-income and rural patients. Addressing these issues through policy reforms, improved healthcare infrastructure, and targeted public health education is essential to reducing CAD-related morbidity and mortality in the country.

Association of P2Y12 inhibitor pretreatment strategy with short and long term ischemic and bleeding outcomes in NSTE-ACS patients

Abstract Background and Aims Oral P2Y12 inhibitors form the basis of both short and long term antiplatelet therapy in NSTE-ACS patients. While reducing thrombogenic activity and ischemic risk is the basis of routine P2Y12 inhibitor pretreatment in NSTE-ACS patients, timing of treatment became controversial as a result of studies showing routine P2Y12 inhibitor pretreatment is associated with an increased risk of bleeding. Even though routine pretreatment is no longer recommended in the ESC guidelines, the inadequacies in RCTs combining all treatment modalities have been noted. Our study aims to determine the relationship between P2Y12 inhibitor pretreatment strategy and short and long-term ischemic and bleeding events. Methods The study was designed as a single-center, prospective and observational study. 2602 patients, aged between 18 and 85, diagnosed with NSTE-ACS in accordance with ESC guidelines were included in the study. 2189 patients were administered with P2Y12 inhibitor pretreatment while 413 patients weren't. Demographic data, CVD risk factors, ECG, echocardiography and laboratory findings at the time of admission, interventional procedural details, type of antiplatelet and anticoagulant treatment and application time were recorded. Patients were divided into two groups as pretreatment and no-pretreatment according to the time of administration of P2Y12 inhibitor loading dose. In the no-pretreatment group choice of P2Y12 inhibitor was left to operator in the cath lab before proceeding to PCI. Post-procedural in-hospital and long term follow up (1 year) were obtained through hospital and national registry systems and patient survey. Results In the no-pretreatment group 91.3% of patients underwent coronary angiography and PCI was performed in 51.8%. In patients proceeding to PCI, 58.5% were given clopidogrel and 41.5% were given a potent P2Y12 inhibitor. In the pretreatment group, clopidogrel was the drug of choice in 93.8% of patients. In the pretreatment group, the primary composite endpoint (MACE and bleeding events) were more common during in-hospital follow-up and this difference was due to a significant increase in both BARC class I &amp; II and class III, IV &amp; V bleedings (Table 1). In the long-term follow up, statistically significant difference was only seen in BARC class I &amp; II bleedings in the pretreatment group. There were no difference in MACE rates in neither in-hospital or long-term follow up (Table 2). Also in multivariate regression analysis, pretreatment with a P2Y12 inhibitor was found to be an independent predictor of short term primary composite endpoints and long-term all-cause mortality. Conclusion The results of our study investigating the effects of the P2Y12 inhibitor pretreatment strategy on ischemic and bleeding endpoints in NSTE-ACS patients showed that the pretreatment strategy did not lead to an improvement in MACE rates in in-hospital and long-term follow-up but caused on overall increase in bleeding events.Kaplan-Meier Survival Analysis