Mortality Costs Research Articles

Assessing a decade of leukaemia-related premature mortality costs: impact on productivity loss in Spain.

Cancer mortality is one of the dominant causes of productivity loss; and within all cancer sites, blood cancer is the fourth most common cause of death in Spain. Thus, its impacts in work productivity are a major concern and represent a high social impact. The aim of this study was to evaluate the productivity losses resulting from of premature deaths due to leukaemia in Spain. The productivity costs stemming from premature mortality due to leukaemia were estimated using the human capital method. Information pertaining to mortality rates, typical incomes, and joblessness figures was gathered throughout a decade-long period spanning from 2012 to 2021. Leukaemia caused 40% of haematological malignancies losses. It represented a 3.39% of all cancer-related deaths. In addition, it was responsible for 7,851 years of potential productive life lost (YPLPLL) in 2021, and productivity losses of €4,206.52million over the 10-year period. All these numbers are relevant for Spain as will help on a more efficient distribution of resource. These productivity losses obtained, highlight the burden of leukaemia on the Spanish population, providing novel data on the number of deaths, trends and productivity losses for this type of cancer. This evaluation offers fresh insights that can aid policymakers in efficiently distributing resources, thereby lessening the economic burden it imposes on individuals of working age.

Use of Antibiotics in Animal Agriculture: Implications for Pediatrics: Technical Report.

Antimicrobial resistance is a global public health threat. Antimicrobial-resistant infections are on the rise and are associated with increased morbidity, mortality, and health care costs. Infants and children are affected by transmission of antimicrobial-resistant zoonotic pathogens through the food supply, direct contact with animals, environmental pathways, and contact with infected or colonized humans. Although the judicious use of antimicrobial agents is necessary for maintaining the health and welfare of humans and animals, it must be recognized that all use of antimicrobial agents exerts selective pressure that increases the risk of development of resistance. This report describes historical and recent use of antibiotics in animal agriculture, reviews the mechanisms of how such use contributes to development of resistance and can adversely affect child health, and discusses US initiatives to curb unnecessary use of antimicrobial agents in agriculture.

RiskPath: Explainable deep learning for multistep biomedical prediction in longitudinal data.

Predicting individual and population risk for disease outcomes and identifying persons at elevated risk is a key prerequisite for targeting interventions to improve health. However, current risk stratification tools for the common, chronic diseases that develop over the lifecourse and represent the majority of disease morbidity, mortality and healthcare costs are aging and achieve only moderate predictive performance. In some common, highly morbid conditions such as mental illness no risk stratification tools are yet available. There is an urgent need to improve predictive performance for chronic diseases and understand how cumulative, multifactorial risks aggregate over time so that intervention programs can be targeted earlier and more effectively in the disease course. Chronic diseases are the end outcomes of multifactorial risks that increment over years and represent cumulative, temporally-sensitive risk pathways. However, tools in current clinical use were constructed in older data and utilize inputs from a single data collection step. Here, we present RiskPath, a multistep deep learning method for temporally-sensitive biomedical risk prediction tailored for the constraints and demands of biomedical practice that achieves very strong performance and full translational explainability. RiskPath delineates and quantifies cumulative multifactorial risk pathways and allows the user to explore performance-complexity tradeoffs and constrain models as required by clinical use cases. Our results highlight the potential for developing a new generation of risk stratification tools and risk pathway mapping in time-dependent diseases and health outcomes by leveraging powerful timeseries deep learning methods in the wealth of biomedical data now appearing in large, longitudinal open science datasets.

Variation in bacterial pathotype is consistent with the sit-and-wait hypothesis.

The sit-and-wait hypothesis predicts that bacteria can become more virulent when they survive and transmit outside of their hosts due to circumventing the costs of host mortality. While this hypothesis is largely supported theoretically and through comparative analysis, experimental validation is limited. Here we test this hypothesis in Streptococcus suis, an opportunistic zoonotic pig pathogen, where a pathogenic ecotype proliferated during the change to intensive pig farming that amplifies opportunities for fomite transmission. We show in an in vitro environmental survival experiment that pathogenic ecotypes survive for longer than commensal ecotypes, despite similar rates of decline. The presence of a polysaccharide capsule has no consistent effect on survival. Our findings suggest that extended survival in the food chain may augment the zoonotic capability of S. suis. Moreover, eliminating the long-term environmental survival of bacteria could be a strategy that will both enhance infection control and curtail the evolution of virulence.

Unveiling the Landscape of Acute Kidney Injury in Surgical Patients: A Systematic Review of Risk Factors and Clinical Biomarkers

Acute Kidney Injury (AKI) is a critical complication with significant implications for surgical patients, leading to increased morbidity, mortality, and healthcare costs. Identifying the risk factors and clinical biomarkers associated with AKI in the surgical context is essential for timely intervention and personalized management. To address this knowledge gap, we conducted a systematic review to comprehensively analyze existing literature on AKI in surgical patients. In this paper, we provided a systemically review analysis based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) technique for AKI risk factors and clinical biomarkers. The advanced searching into two powerful databases which is Scopus, Pubmed and Mendeley. Based on searching, find finally main data n=30 and will be analyzed using the synthesis approach. Through a meticulous search and appraisal of studies in reputable scientific databases, we identified a diverse range of research articles, clinical trials, and cohort studies that met our rigorous inclusion criteria. Synthesizing the findings from these studies, we explored the multifactorial nature of AKI, encompassing patient-related factors, surgical variables, and exposure to potential nephrotoxic agents. Our review revealed that AKI in surgical patients is influenced by a complex interplay of risk factors, including patient demographics, comorbidities, surgical procedures, anaesthetic management, and exposure to nephrotoxic drugs. The systematic analysis identified the most common drug classes associated with drug-induced AKI, such as diuretics, ACE inhibitors/angiotensin receptor blockers (ACEIs/ARBs), and antibiotics

Determinants of Healthcare-Associated Infections in King Abdulaziz Specialized Hospital in Taif, Saudi Arabia.

Healthcare-associated infections (HAIs) represent a significant challenge in hospital settings, contributing to increased morbidity, mortality, and healthcare costs. This study aimed to estimate the prevalence and socio-demographic and clinical determinants of HAIs at the King Abdulaziz Specialized Hospital (KAASH) in Taif, Saudi Arabia. A hospital-based cross-sectional study was conducted from March 2023 to January 2024targeting inpatients aged 18 and above in all units and wards. Data were collected using the National Healthcare Safety Network (NHSN) criteria for definitions of surveillance. A structured questionnaire gathered socio-demographic and clinical data from patients or next of kin if the patient was not fully oriented.Descriptive statistics were performed, and analytical methods used included Pearson chi-square test, Pearsoncorrelation, independent t-test, and one-way analysis of variance. Among 318 participants included in this study, the mean age of participants was 56.44 years, with a slight female predominance (n=164, 51.6%). Hypertension (n=162, 50.9%) and diabetes (n=126, 39.6%) were the most prevalent comorbidities. Pneumonia (n=60, 26.8%) and trauma (n=55, 17.4%) were the leading causes of admission. The two most common HAIs included catheter-associated urinary tract infections (CAUTI) (n=124, 39%) and central line-associated bloodstream infections (CLABSI) (n=74, 23.3%). The primary causative organisms were Klebsiella pneumoniae (n=96, 30.2%) and Acinetobacter baumannii (n=32, 10.1%). The most significant predictors of HAIs were as follows: For CLABSI, risk factors include having three or more comorbidities, fever above 37.8°C, chills or rigors, hypotension, and positive blood culture. For CAUTI, key predictors were urinary tract infection (UTI), positive urine culture, acute pain or swelling of the testes, suprapubic tenderness, visible hematuria, and leukocytosis. Significant predictors of bloodstream infections (BSI) include having a BSI, positive blood culture, chills or rigors, and hypotension. Fever and hypotension increased CLABSI and BSI risk but reduced the CAUTI risk. The study highlights a significant burden of HAIs at the KAASH, with multiple predictors. The findings underscore the need for robust infection control measures and targeted interventions to reduce HAI incidence and improve patient outcomes.

The Impact of Infection Prevention Bundles on Neurosurgical Outcomes and Healthcare Costs: A Systematic Review

Background: Post-operative infections represent a significant challenge in neurosurgery, leading to increased morbidity, mortality, and healthcare costs. The implementation of infection prevention bundles, which encompass a set of evidence-based practices, has emerged as a potential solution to mitigate these adverse outcomes. This systematic review aims to evaluate the effectiveness of infection prevention bundles in improving neurosurgical outcomes and reducing healthcare costs. Methods: A comprehensive search of electronic databases (PubMed, Scopus, Web of Science) was conducted to identify studies published between 2010 and 2023 that evaluated the impact of infection prevention bundles on neurosurgical outcomes and healthcare costs. The search strategy included keywords such as "neurosurgery," "infection prevention," "surgical site infection," "bundle," "outcomes," and "healthcare costs." Studies were included if they reported on at least one clinical outcome (e.g., surgical site infection rates, mortality, length of stay) and/or healthcare costs. Data extraction and quality assessment were performed independently by two reviewers. Results: The search yielded 45 studies that met the inclusion criteria. The studies encompassed a variety of neurosurgical procedures, including craniotomies, spinal surgeries, and deep brain stimulation. The infection prevention bundles implemented varied across studies but commonly included preoperative antibiotic prophylaxis, skin antisepsis, and intraoperative measures. The pooled analysis demonstrated a significant reduction in surgical site infection rates and length of stay associated with the use of infection prevention bundles. Moreover, several studies reported cost savings, primarily attributed to reduced complications and shorter hospital stays. Conclusion: The evidence suggests that infection prevention bundles are effective in improving neurosurgical outcomes and reducing healthcare costs. The implementation of these bundles should be considered a standard of care in neurosurgery to enhance patient safety and optimize resource utilization. Keywords: Neurosurgery, infection prevention, surgical site infection, healthcare costs, systematic review.

Comparative evaluation of early treatment with ceftolozane/tazobactam versus ceftazidime/avibactam for non-COVID-19 patients with pneumonia due to multidrug-resistant Pseudomonas aeruginosa.

Ceftolozane/tazobactam and ceftazidime/avibactam are commonly used in patients with MDR-Pseudomonas aeruginosa (PSA) pneumonia (PNA). This study compared outcomes between non-COVID-19 hospitalized patients with MDR-PSA PNA who received ceftolozane/tazobactam or ceftazidime/avibactam. The study included non-COVID-19 adult hospitalized patients with MDR-PSA PNA in the PINC AI Healthcare Database (2016-22) who received ceftolozane/tazobactam or ceftazidime/avibactam within 3 days of index culture for ≥2 days. Outcomes were mortality, recurrent MDR-PSA PNA, discharge destination, post-index culture day length of stay (LOS) and costs (in US dollars, USD), and hospital readmission. The final sample included 197 patients (117 ceftolozane/tazobactam, 80 ceftazidime/avibactam). No significant differences were observed in mortality and post-index culture LOS and costs between groups. In the multivariable analyses, patients who received ceftolozane/tazobactam versus ceftazidime/avibactam had lower recurrent MDR-PSA PNA (7.9% versus 18.0%, P = 0.03) and 60 day PNA-related readmissions (11.1% versus 28.5%, P = 0.03) and were more likely to be discharged home (25.8% versus 9.8%, P = 0.03). Compared with ceftazidime/avibactam patients, ceftolozane/tazobactam patients had lower adjusted median total antibiotic costs (5052 USD versus 8099 USD, P = 0.003) and lower adjusted median comparator (ceftolozane/tazobactam or ceftazidime/avibactam) antibiotic costs (3938 USD versus 6441 USD, P = 0.005). In the desirability of outcome ranking (DOOR) analysis, a ceftolozane/tazobactam-treated patient was more likely to have a more favourable outcome than a ceftazidime/avibactam-treated patient [DOOR probability: 59.6% (95% CI: 52.5%-66.8%)]. Early treatment with ceftolozane/tazobactam may offer some clinical and cost benefits over ceftazidime/avibactam in patients with MDR-PSA PNA. Further large-scale studies are necessary to comprehensively understand the outcomes associated with these treatments for MDR-PSA PNA.

Population health value of being in target: Results from the Canadian Multi-Morbidity Model for Type 2 Diabetes

ObjectiveTo develop a microsimulation model for type 2 diabetes using population-level real-world data. Such a model allows for the synthesis of multiple data sources for comparative effectiveness analysis related to a variety of correlated outcomes. ApproachThe model was built using health state features including sex, age, diabetes duration, laboratory test results, and a history of major acute events. Features update using a cycle length of one month. Events modelled include myocardial infarction, stroke, heart failure, amputation and death. Model outputs include counts of events, lifetime healthcare costs and quality-adjusted life-years (QALYs). We then used the model to calculate the number of events that could be averted if a population with type 2 diabetes achieved treatment targets for HbA1c, blood pressure and LDL-cholesterol for 10 years. ResultsBringing all 60-year-olds with type 2 diabetes into target for 10 years would result in annual event reductions of 87.0 per 100,000 person-years for myocardial infarction, 49.4 for stroke, and 166.8 for heart failure. QALYs would improve by 1,155 per 100,000 patients. For 75-year-olds, annual event reductions would be 178.2, 56.8 and 261.6 per 100,000 person-years, respectively, and QALYs would improve by 2,121 per 100,000 patients. ConclusionsPopulation-level real-world data can be used to develop microsimulation models for type 2 diabetes that estimate long-term event risks, mortality and healthcare costs. This model is capable of comparative effectiveness and cost-effectiveness analysis of novel therapies in diabetes.

Prevalence of undiagnosed stage B heart failure among emergency department patients

IntroductionHeart failure (HF) is associated with significant morbidity, mortality, and health care costs. Stage B HF is defined as structural heart disease prior to developing symptomatic HF. If identified early in the disease process, preventative measures may be implemented to slow disease progression to Stage C (symptomatic) or Stage D (refractory) HF. Previous research has focused on outpatient screening for HF in the primary care setting; however, there are limited data on Stage B HF screening in the Emergency Department (ED) setting. The objective of this study was to determine the prevalence of undiagnosed Stage B HF among those with cardiovascular risk factors in the ED setting and identify which risk factors were associated with a greater risk of having Stage B HF. MethodsA prospective, observational study was performed in a single, urban academic ED from 07/2023 to 05/2024. Inclusion criteria were age ≥ 45 years with hypertension, diabetes, obesity, coronary heart disease, previous cardiotoxic chemotherapy, or family history of HF. Exclusion criteria included signs or symptoms of HF, known history of HF, valvular disease, current atrial fibrillation, or primary language other than English. A focused cardiac ultrasound was performed and interpreted by ultrasound-fellowship trained emergency physicians. Sonographers assessed systolic function as ejection fraction <50 % using visual assessment in at least two different views. Sonographers assessed diastolic dysfunction as an E/A ratio < 0.8, or if ≥2 of the following were present: septal e' < 7 cm/s or lateral e' < 10 cm/s, E/e' ratio > 14, or left atrial volume > 34 mL/m2. Descriptive statistics were performed, followed by comparative analyses and regression modeling. Results209 participants were included in the study, with a mean age of 60 years and 51.7 % women. Of these, 125 (59.8 %) had undiagnosed Stage B HF, with 13 (10.4 %) having systolic dysfunction and 112 (89.6 %) having isolated diastolic dysfunction. Among those with isolated diastolic dysfunction, 44 (39.3 %) were grade I, 66 (58.9 %) were grade II, and 2 (1.8 %) were grade III. Predictors of undiagnosed Stage B HF included age (odds ratio 1.06; 95 % CI 1.02 to 1.10) and BMI (odds ratio 1.06; 95 % CI 1.01 to 1.10). ConclusionA large majority of ED patients with cardiovascular risk factors had undiagnosed Stage B HF. Age and obesity were associated with a higher risk of Stage B HF. This provides an opportunity for early identification and intervention for patients with undiagnosed Stage B HF to reduce progression to more severe HF.

Determinants of polydoctoring among multimorbid older adults; a cross‐sectional study in an urban area of Japan

AbstractBackgroundMultimorbidity increases with age, leading to various adverse outcomes, including higher mortality, care dependency, hospitalizations, and healthcare costs. Polydoctoring, managing a patient with multimorbidity by multiple healthcare providers, can be a risk of fragmented care and increased healthcare expenditures. This study aims to identify patient‐related factors contributing to polydoctoring in older adults with multimorbidity.MethodsThis study is a cross‐sectional study using baseline data from the Kawasaki Aging and Wellbeing Project. Participants were residents of Kawasaki City aged 85–89 years, without disability in basic activities of daily living, and being able to visit study site. The regularly visited facilities (RVF) index was employed to quantify polydoctoring. Polydoctoring was defined as having two or more RVFs. Poisson regression analysis was conducted to assess the association between polydoctoring and patient demographics, including types of chronic conditions and socioeconomic factors.ResultsA total of, 968 participants with multimorbidity were analyzed. Increased RVF was significantly associated with eye diseases (rate ratio [RR] 1.27, 95% confidence interval [CI] 1.12–1.44), osteoporosis (RR 1.22, 95% CI 1.08–1.38), prostate diseases (RR 1.22, 95% CI 1.07–1.40), and osteoarthritis (RR 1.16, 95% CI 1.05–1.27). No significant correlation was found with educational status or financial hardship.ConclusionThe study indicated that certain chronic conditions are linked to increased polydoctoring among multimorbid older adults in Japan. However, most of those conditions are considered to be within a scope of family medicine/general practice. Training general practitioners to manage these conditions could reduce healthcare costs and the treatment burden, indicating a direction for future healthcare policy and medical education.

Integration of an electronic hand hygiene auditing system with electronic health records using machine learning to predict hospital-acquired infection in a health care setting

Hospital-acquired infections (HAIs) increase morbidity, mortality, and healthcare costs. Effective hand hygiene (HH) is crucial for prevention, but achieving high compliance remains challenge. This study explores using machine learning to integrate an electronic HH auditing system with electronic health records to predict HAIs. A retrospective cohort study was conducted at a Brazilian hospital during 2017-2020. HH compliance was recorded electronically, and patient data were collected from electronic health records. The primary outcomes were HAIs per CDC/NHSN surveillance definitions. Machine learning algorithms, balanced with Random Over Sampling Examples (ROSE), were utilized for predictive modeling, including generalized linear models (GLM); generalized additive models for location, scale, and shape (GAMLSS); random forest; support vector machine; and extreme gradient boosting (XGboost). 125 of 6,253 patients (2%) developed HAIs and 920,489 HH opportunities (49.3% compliance) were analyzed. A direct correlation between HH compliance and HAIs was observed. The GLM algorithm with ROSE demonstrated superior performance, with 84.2% sensitivity, 82.9% specificity, and a 93% AUC. Integrating electronic HH auditing systems with electronic health records and using machine learning models can enhance infection control surveillance and predict patient outcomes. Further research is needed to validate these findings and integrate them into clinical practice.

Association Between Surgeon Sex and Days Alive at Home Following Surgery: A Population-Based Cohort Study.

The objective of this study was to measure potential associations between surgeon sex and number of days alive and at home (DAH). Patients treated by female surgeons appear to have lower rates of mortality, complications, readmissions, and healthcare costs when compared with male surgeons. DAH is a validated measure, shown to better capture the patient experience of postoperative recovery. We conducted a retrospective study of adults (≥18 years of age) undergoing common surgeries between January 01, 2007 and December 31, 2019 in Ontario, Canada. The outcome measures were the number of DAH within 30-, 90-, and 365-days. The data was summarized using descriptive statistics and adjusted using multivariable generalized estimating equations. During the study period, 1,165,711 individuals were included, of which 61.9% (N = 721,575) were female. Those managed by a female surgeon experienced a higher mean number of DAH when compared with male surgeons at 365 days (351.7 vs. 342.1 days; P < 0.001) and at each earlier time point. This remained consistent following adjustment for covariates, with patients of female surgeons experiencing a higher number of DAH at all time points, including at 365 days (343.2 [339.5-347.1] vs. 339.4 [335.9-343.0] days). Multivariable regression modeling revealed that patients of male surgeons had a significantly lower number of DAH versus female surgeons. Patients of female surgeons experienced a higher number of DAH when compared with those treated by male surgeons at all time points. More time spent at home after surgery may in turn lower costs of care, resource utilization, and potentially improve quality of life. Further studies are needed to examine these findings across other care contexts.

Comprehensive Analysis of the Significance of Breast Cancer Gene 1 (BRCA-1) in Bladder Cancer.

Bladder carcinoma (BLCA) is characterized by high morbidity, mortality, and treatment costs. Breast cancer gene 1 (BRCA1), a tumor suppressor gene, inhibits the development of malignant tumors. However, research on the significance of BRCA1 in BLCA is limited. This study aims to explore the importance of BRCA1 in BLCA using bioinformatic methods and immunohistochemistry. Gene expression, clinical, and survival data were collected from the TCGA databases through the UCSC Xena platform (http://xena.ucsc.edu/). The TPM data from the TCGA and GETEx databases were integrated using the GEPIA database (http://GEPIA.cancer-pku.cn). The study then explored the differential expression, survival prognosis, functional enrichment, and immune cell infiltration analyses of BRCA1 in BLCA. A PPI network of BRCA1 was constructed using the STRING database, and a BRCA1-associated gene-gene interaction network was generated using the GeneMANIA database. Immunohistochemistry (IHC) assays were performed to verify the expression levels of BRCA1 in bladder tumour tissues and adjacent normal tissues. BRCA1 is associated with BLCA. Differential analysis indicated that BRCA1 acts as a risk factor for BLCA but does not show significant expression differences across genders, stages, tumor stages, lymph node stages, or metastasis stages. Additionally, staging was based on the eighth edition of the American Joint Committee on Cancer (AJCC) for BLCA. Co-expression network and Gene Set Enrichment Analysis (GESA) confirmed that BRCA1 is involved in various BLCA pathways. Furthermore, BRCA1 expression was also linked to immune cell infiltration. However, survival prognosis analysis revealed no significant correlation between the prognosis of BLCA and BRCA1. We demonstrated that BRCA1 is a prospective predicted and immunological biomarker in BLCA, offering new avenues for potential therapies.

Postoperative Atrial Fibrillation: A Review.

Atrial fibrillation (AF) in the postoperative phase is a manifestation of numerous factors, including surgical stress, anesthetic effects, and underlying cardiovascular conditions. The resultant cardiac hyperactivity can induce new onset or exacerbate existing AF. A common phenomenon, postoperative atrial fibrillation (POAF) affects nearly 40% of patients and is associated with longer hospitalization stays, and increased mortality, heart failure, stroke, and healthcare costs. Areas of controversy in POAF include whether to anticoagulate patients who have short-lived POAF, especially given their higher bleeding risk in the postoperative period, and the identification of patients who would benefit the most from preventive drug therapy for POAF. This review discusses the pathophysiology and management of POAF, and strategies to reduce its occurrence.

Analyzing the Prevalence and Patterns of Antibiotic-Resistant Pathogens Causing Surgical Site Infections

Surgical Site Infections (SSIs) remain a critical healthcare challenge, contributing to increased morbidity, mortality, and healthcare costs. SSIs represent the third most common nosocomial infection globally with an incidence of 19-20%, while their prevalence in Pakistan was significantly higher, ranging up to 33.6%. The emergence of Multidrug-Resistant (MDR) organisms has worsened this issue. Objective: To determine the prevalence of antibiotic-resistant pathogens responsible for SSIs and analyze their antibiotic susceptibility patterns over the past decade. Methods: A systematic review was conducted adhering to PRISMA guidelines. Studies published between 2006 and 2023 were included. Data on the prevalence of antibiotic-resistant organisms associated with SSIs were extracted and analyzed through several databases (PubMed, Google Scholar, Sci-hub and Science Direct) using Boolean logic “AND” and “OR”, and Medical Subject Headings (MeSH Terms) and keywords. A total of 70 articles were retrieved from which 16 articles were considered eligible after applying detailed inclusion/exclusion criteria and removing the duplicates and irrelevant articles. Results: The study identified Staphylococcus aureus, coagulase-negative staphylococci, Pseudomonas aeruginosa, Klebsiella pneumoniae, Escherichia coli, and Acinetobacter spp. as predominant MDR pathogens. A significant increase in the prevalence of antibiotic-resistant strains was observed over the study period. Gram-negative bacteria exhibited a higher resistance rate (66.8%) compared to Gram-positive organisms (51.1%). Conclusions: The increasing prevalence of antibiotic-resistant pathogens underscores the urgent need for comprehensive infection prevention and control measures to address the burden of SSIs. Targeted interventions, antimicrobial stewardship, and continued surveillance were essential to combat this growing challenge.

Unveiling the Disease Patterns and Infection Categories in MDRO-Infected Patients: Insights from a Comprehensive Study at Dr. Kariadi Hospital, Semarang

Background: Multi-drug resistant organisms (MDRO) pose a significant challenge to healthcare systems worldwide, leading to increased morbidity, mortality, and healthcare costs. Understanding the disease patterns and infection categories associated with MDRO infections is crucial for effective management and prevention strategies. This study aims to unveil the prevalent diseases and infection categories among MDRO-infected patients at Dr. Kariadi Hospital, Semarang in Indonesia.Methods: A comprehensive retrospective analysis was conducted on medical records of patients diagnosed with MDRO infections. Clinical characteristics were collected and analyzed. The diseases were classified into broader categories based on their organ system or common medical classification.Result: The study included 100 MDRO-infected patients and they presented with 81 various medical conditions/diseases. The most common diseases associated with MDRO infections were Covid-19, and Bronchopneumonia. Among the infection categories, gastrointestinal disorders, and Neoplastic Diseases were the predominant categories. The study revealed a high prevalence of MDRO infections in patients with these conditions while as the category of Autoimmune and Rheumatic Diseases accounted for the smallest proportion of cases with only one case.Conclusion : This comprehensive study provides valuable insights into the disease patterns and infection categories in MDRO-infected patients at Dr. Kariadi Hospital, Semarang. The findings highlight the need for targeted surveillance, infection control measures, and antimicrobial stewardship programs to effectively manage MDRO infections. Understanding the most prevalent diseases and infection categories associated with MDROs can aid in early detection, appropriate treatment, and the development of preventive strategies.

Per- and polyfluoroalkyl substances (PFAS) and hypertensive disorders of Pregnancy- integration of epidemiological and mechanistic evidence

BackgroundHypertensive disorders of pregnancy (HDP) remain a significant global health burden despite medical advancements. HDP prevalence appears to be rising, leading to increased maternal and fetal complications, mortality, and substantial healthcare costs. The etiology of HDP are complex and multifaceted, influenced by factors like nutrition, obesity, stress, metabolic disorders, and genetics. Emerging evidence suggests environmental pollutants, particularly Per- and polyfluoroalkyl substances (PFAS), may contribute to HDP development. ObjectiveThis review integrates epidemiological and mechanistic data to explore the intricate relationship between PFAS exposure and HDP. Epidemiological evidenceStudies show varying degrees of association between PFAS exposure and HDP, with some demonstrating positive correlations, particularly with preeclampsia. Meta-analyses suggest potential fetal sex-specific differences in these associations. Mechanistic insightsMechanistically, PFAS exposure appears to disrupt vascular hemodynamics, placental development, and critical processes like angiogenesis and sex steroid regulation. Experimental studies reveal alterations in the renin-angiotensin system, trophoblast invasion, oxidative stress, inflammation, and hormonal dysregulation – all of which contribute to HDP pathogenesis. Elucidating these mechanisms is crucial for developing preventive strategies. Therapeutic potentialTargeted interventions such as AT2R agonists, caspase inhibitors, and modulation of specific microRNAs show promise in mitigating adverse outcomes associated with PFAS exposure during pregnancy. Knowledge gaps and future directionsFurther research is needed to comprehensively understand the full spectrum of PFAS-induced placental alterations and their long-term implications for maternal and fetal health. This knowledge will be instrumental in developing effective preventive and therapeutic strategies for HDP in a changing environmental landscape.

Health economic evaluation of an artificial intelligence (AI)-based rapid nutritional diagnostic system for hospitalised patients: A multicentre, randomised controlled trial

Background & aimsMalnutrition is prevalent among hospitalised patients, and increases the morbidity, mortality, and medical costs; yet nutritional assessments on admission are not routine. This study assessed the clinical and economic benefits of using an artificial intelligence (AI)-based rapid nutritional diagnostic system for routine nutritional screening of hospitalised patients. MethodsA nationwide multicentre randomised controlled trial was conducted at 11 centres in 10 provinces. Hospitalised patients were randomised to either receive an assessment using an AI-based rapid nutritional diagnostic system as part of routine care (experimental group), or not (control group). The overall medical resource costs were calculated for each participant and a decision-tree was generated based on an intention-to-treat analysis to analyse the cost-effectiveness of various treatment modalities. Subgroup analyses were performed according to clinical characteristics and a probabilistic sensitivity analysis was performed to evaluate the influence of parameter variations on the incremental cost-effectiveness ratio (ICER). ResultsIn total, 5763 patients participated in the study, 2830 in the experimental arm and 2933 in the control arm. The experimental arm had a significantly higher cure rate than the control arm (23.24% versus 20.18%; p = 0.005). The experimental arm incurred an incremental cost of 276.52 CNY, leading to an additional 3.06 cures, yielding an ICER of 90.37 CNY. Sensitivity analysis revealed that the decision-tree model was relatively stable. ConclusionThe integration of the AI-based rapid nutritional diagnostic system into routine inpatient care substantially enhanced the cure rate among hospitalised patients and was cost-effective. RegistrationNCT04776070 (https://clinicaltrials.gov/study/NCT04776070)

Identification of phase angle and Triglyceride-Glucose index as biomarkers for prediction and management of diabetic foot disease

IntroductionApproximately 25 % of diabetic patients develop diabetic foot ulcers (DFUs), significantly increasing morbidity, mortality, and healthcare costs. Effective control and prevention are crucial. ObjectiveThis study aims to identify easily measurable parameters for predicting DFU risk by assessing the correlation between Phase Angle (PA) and the Triglyceride-Glucose (TyG) index with DFU risk. Materials and methodsA comparative case-control study was conducted at the General Hospital of Elche from March to June 2023 with 70 participants (33 with diabetes, 37 without). Cases had diabetes for over five years and a diabetic foot risk grade of 0, 1, or 2 (IWGDF 2019). Exclusion criteria included inability to walk, prior use of orthoses, and severe complications like edema or wounds. Predictive variables were PA, TyG index, body composition, and biochemical markers. Statistical analyses included Pearson/Spearman tests for correlations, Student's t-test/Mann-Whitney test for group comparisons, and ANOVA/Kruskal-Wallis tests for normally and non-normally distributed variables. ResultsPAand TyG index were strongly linked to diabetic foot risk, supporting their potential as biomarkers. Significant relationships with other relevant biomarkers were also confirmed. ConclusionPA and TyG index are valuable, easily measurable biomarkers for assessing diabetic foot risk, and can be monitored in primary care settings. Implementing these biomarkers in routine practice could enhance the management of diabetic complications, particularly in resource-limited settings, by enabling early detection and intervention, thus improving patient outcomes and reducing the burden of advanced complications.