Predictive modelling of transport decisions and resources optimisation in pre-hospital setting using machine learning techniques.

BACKGROUND: The global evolution of pre-hospital care systems faces dynamic challenges, particularly in multinational settings. Machine learning (ML) techniques enable the exploration of deeply embedded data patterns for improved patient care and resource optimisation. This study's objective was to accurately predict cases that necessitated transportation versus those that did not, using ML techniques, thereby facilitating efficient resource allocation. METHODS: ML algorithms were utilised to predict patient transport decisions in a Middle Eastern national pre-hospital emergency medical care provider. A comprehensive dataset comprising 93,712 emergency calls from the 999-call centre was analysed using R programming language. Demographic and clinical variables were incorporated to enhance predictive accuracy. Random Forest (RF), Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), and Adaptive Boosting (AdaBoost) algorithms were trained and validated. RESULTS: All the trained algorithm models, particularly XGBoost (Accuracy = 83.1%), correctly predicted patients' transportation decisions. Further, they indicated statistically significant patterns that could be leveraged for targeted resource deployment. Moreover, the specificity rates were high; 97.96% in RF and 95.39% in XGBoost, minimising the incidence of incorrectly identified "Transported" cases (False Positive). CONCLUSION: The study identified the transformative potential of ML algorithms in enhancing the quality of pre-hospital care in Qatar. The high predictive accuracy of the employed models suggested actionable avenues for day and time-specific resource planning and patient triaging, thereby having potential to contribute to pre-hospital quality, safety, and value improvement. These findings pave the way for more nuanced, data-driven quality improvement interventions with significant implications for future operational strategies.

Epidemiology of prehospital emergency calls according to patient transport decision in a middle eastern emergency care environment: Retrospective cohort-based.

Background and Aim: Though emergency medical services (EMS) respond to all types of emergency calls, they do not always result in the patient being transported to the hospital. This study aimed to explore the determinants influencing emergency call-response-based conveyance decisions in a Middle Eastern ambulance service. Methods: This retrospective quantitative analysis of 93,712 emergency calls to the Hamad Medical Corporation Ambulance Service (HMCAS) between January 1 and May 31, 2023, obtained from the HMCAS electronic system, was analyzed to determine pertinent variables. Sociodemographic, emergency dispatch-related, clinical, and miscellaneous predictors were analyzed. Descriptive, bivariate, ridge logistic regression, and combination analyses were evaluated. Results: 23.95% (N = 21,194) and 76.05% (N = 67,285) resulted in patient nontransport and transportation, respectively. Sociodemographic analysis revealed that males predominantly activated EMS resources, and 60% of males (n = 12,687) were not transported, whilst 65% of females (n = 44,053) were transported. South Asians represented a significant proportion of the transported patients (36%, n = 24,007). "Home" emerged as the primary emergency location (56%, n = 37,725). Bivariate analysis revealed significant associations across several variables, though multicollinearity was identified as a challenge. Ridge regression analysis underscored the role of certain predictors, such as missing provisional diagnoses, in transportation decisions. The upset plot shows that hypertension and diabetes mellitus were the most common combinations in both groups. Conclusions: This study highlights the nuanced complexities governing conveyance decisions. By unveiling patterns such as male predominance, which reflects Qatar's expatriate population, and specific temporal EMS activity peaks, this study accentuates the importance of holistic patient assessment that transcends medical histories.

Exploring factors influencing time from dispatch to unit availability according to the transport decision in the pre-hospital setting: an exploratory study.

BACKGROUND: Efficient resource distribution is important. Despite extensive research on response timings within ambulance services, nuances of time from unit dispatch to becoming available still need to be explored. This study aimed to identify the determinants of the duration between ambulance dispatch and readiness to respond to the next case according to the patients' transport decisions. METHODS: Time from ambulance dispatch to availability (TDA) analysis according to the patients' transport decision (Transport versus Non-Transport) was conducted using R-Studio™ for a data set of 93,712 emergency calls managed by a Middle Eastern ambulance service from January to May 2023. Log-transformed Hazard Ratios (HR) were examined across diverse parameters. A Cox regression model was utilised to determine the influence of variables on TDA. Kaplan-Meier curves discerned potential variances in the time elapsed for both cohorts based on demographics and clinical indicators. A competing risk analysis assessed the probabilities of distinct outcomes occurring. RESULTS: The median duration of elapsed TDA was 173 min for the transported patients and 73 min for those not transported. The HR unveiled Significant associations in various demographic variables. The Kaplan-Meier curves revealed variances in TDA across different nationalities and age categories. In the competing risk analysis, the 'Not Transported' group demonstrated a higher incidence of prolonged TDA than the 'Transported' group at specified time points. CONCLUSIONS: Exploring TDA offers a novel perspective on ambulance services' efficiency. Though promising, the findings necessitate further exploration across diverse settings, ensuring broader applicability. Future research should consider a comprehensive range of variables to fully harness the utility of this period as a metric for healthcare excellence.

Enhancing Patient Safety in Prehospital Environment: Analyzing Patient Perspectives on Non-Transport Decisions With Natural Language Processing and Machine Learning.

OBJECTIVE: This research explored the experiences and perspectives of patients declining hospital transportation after receiving prehospital emergency care using advanced computational techniques. METHOD: Between 15th June and 1st August 2023, 210 patients in Qatar, treated by Hamad Medical Corporation Ambulance Service (HMCAS) but refusing transportation to hospital, were interviewed. Key outcome variables stratified by demographics included "reasons for refusing transport," "satisfaction with HMCAS service," and "postrefusal actions." Responses underwent sentiment analysis and topic modeling using latent Dirichlet allocation. Machine learning models, such as Naïve Bayes, K-nearest neighboring, random forest, and support vector machine, were used to predict patients' subsequent actions. RESULTS: Participants had an average age of 38.61 ± 19.91 years. The chief complaints were primarily chest and abdominal pains (18.49%; n = 39). Sentiment Analysis revealed a generally favorable perception of HMCAS-provided service. Latent Dirichlet allocation identified two main topics pertaining to refusal reasons and service satisfaction. Naïve Bayes and support vector machine algorithms were most effective in predicting postrefusal actions with an accuracy rate of 81.58%. CONCLUSIONS: This study highlighted the utility of Natural Language Processing and ML in enhancing our understanding of patient behaviors and sentiments in prehospital settings. These advanced computational methodologies allowed for a nuanced exploration of patient demographics and sentiments, providing insights for Quality Improvement initiatives. The study also advocates for continuously integrating automated feedback mechanisms to improve patient-centered care in the prehospital context. Continuous integration of automated feedback systems is recommended to improve prehospital patient-centered care.

Foot involvement in psoriatic arthritis: Prevalence, clinical and radiological features.

BACKGROUND: The purpose of this study was to evaluate the prevalence of foot involvement in psoriatic arthritis and to describe its different clinical and radiological features. PATIENTS AND METHODS: We conducted a cross sectional study including 40 patients with psoriatic arthritis over a period of 12 months. Anamnesis, clinical examination of feet, podoscopic examination, X-rays of feet and heels, and ultrasound in B mode and power Doppler mode were done for each patient. RESULTS: Foot involvement was found in 95% of cases. It was symptomatic in 70% and inaugural of the disease in 20% of cases. The hindfoot and the forefoot were the sites most affected (77.5% and 47.5% respectively). The involvement of the midfoot was rarer (25%). Dactylitis was found in 17.5% and deformities of forefoot were found in 22.5% of cases. Antalgic gait was noted in 17.5% and static disorders of foot at podoscopic examination were identified in 35% of cases. Feet dermatological manifestations were found in 45% of cases. Diagnosis of different rheumatological manifestations was based on clinical findings and caracteristic radiological images on X-rays. We demonstrate he sensitivity of ultrasound in the detection and the diagnosis of different foot lesions including enthesitis, synovitis and tenosynovitis, dactylitis, bone erosions and psoriatic nail dystrophy.

Central retinal vein occlusion : an uncommon complication in sarcoidosis.

Sarcoidosis is a multi-system granulomatosis of unknown etiology, defined by the presence of epithelioid and gigantocellular granulomas, without caseous necrosis. Ocular sarcoidosis manifests mainly as bilateral granulomatous anterior uveitis. Occlusion of the central retinal vein in sarcoidosis is a rare manifestation, which is the particularity of our observation. We report the case of a patient presenting with unilateral central retinal vein occlusion associated with granulomatous anterior uveitis on the same side. Systemic manifestations and further investigations led to the diagnosis of sarcoidosis.

Epidemiological Determinants of Patient Non-Conveyance to the Hospital in an Emergency Medical Service Environment.

BACKGROUND: The increasing prevalence of comorbidities worldwide has spurred the need for time-effective pre-hospital emergency medical services (EMS). Some pre-hospital emergency calls requesting EMS result in patient non-conveyance. Decisions for non-conveyance are sometimes driven by the patient or the clinician, which may jeopardize the patients' healthcare outcomes. This study aimed to explore the distribution and determinants of patient non-conveyance to hospitals in a Middle Eastern national Ambulance Service that promotes the transportation of all emergency call patients and does not adopt clinician-based non-conveyance decision. METHODS: Using R Language, descriptive, bivariate, and binary logistic regression analyses were conducted for 334,392 multi-national patient non-conveyance emergency calls from June 2018 to July 2022, from a total of 1,030,228 calls to which a response unit was dispatched. RESULTS: After data pre-processing, 237,862 cases of patient non-conveyance to hospital were retained, with a monthly average of 41.96% (n = 8799) of the emergency service demands and a standard deviation of 5.49% (n = 2040.63). They predominantly involved South Asians (29.36%, n = 69,849); 64.50% (n = 153,427) were of the age category from 14 to 44 years; 61.22% (n = 145,610) were male; 74.59% (n = 177,424) from the urban setting; and 71.28% (n = 169,552) had received on-scene treatment. Binary logistic regression with full variables and backward methods identified the final models of the determinants of patient non-conveyance decisions with an Akaike information criterion prediction estimator, respectively, of (250,200) and (250,169), indicating no significant difference between both models (Chi-square test; p-value = 0.63). CONCLUSIONS: Despite exercising a cautious protocol by encouraging patient transportation to hospital, patient non-conveyance seems to be a problem in the healthcare system that strains the pre-hospital medical response teams' resources. Policies and regulations should be adopted to encourage individuals to access other primary care centers when required rather than draining emergency services for non-emergency situations.

Multifocal hydatidosis with extensive involvement of the sacrum and the femoral head.

Key Clinical Message: Hydatidosis is a parasitic infection caused by the larval form of "Echinococcus granulosis." Bone localization is rare even in endemic areas. We report an unusual case of an extensive hydatidosis of the right sacrum and femur with muscle involvement. Abstract: We report the case of a man, with a history of visceral hydatidosis, who developed after 14 years an extensive hydatidosis of the sacrum and femur with muscle involvement. The treatment of visceral hydatidosis was chemotherapy with albendazole for a long term. Conservative surgical treatment is considered for bone locations.

Isolation of bacterial strains from compost teas and screening of their PGPR properties on potato plants.

The beneficial effect of compost and compost tea on plant growth and protection is mainly associated with the microbial diversity and the presence of bacteria with plant growth-promoting effect. PGPR are considered as eco-friendly bio-fertilizers that may reduce the use of chemical pesticides and fertilizers. Three composts (AT, A10, and A30) were previously prepared from industrial wastes (olive mill wastewater, olive pomace, coffee ground, and phosphogypsum). In the present study, we isolated three bacterial strains from the compost teas. The phylogenetic identification of these bacterial strains (B.AT, B.A10, and B.A30) showed that they correspond to Serratia liquefaciens (B.AT and B.A10) and Achromobacter spanius (B.A30) species. A further characterization of the PGPR traits of these bacteria showed that they produce siderophore, exopolysaccharides, and IAA. Their effect on potato plant growth, yields, and tuber quality was performed under field culture conditions. Results showed that these strains can be characterized as PGPR, the best effect on potato plant growth was observed with Serratia liquefaciens (B.AT), the best yield and tuber quality was observed with Serratia liquefaciens (B.A10) while bacterial treatment with Achromobacter spanius (B.A30) is a Cd-tolerant PGPR.

The effectiveness of platelet-rich plasma gel on full-thickness cartilage defect repair in a rabbit model.

AIMS: The present study investigates the effectiveness of platelet-rich plasma (PRP) gel without adjunct to induce cartilage regeneration in large osteochondral defects in a rabbit model. METHODS: A bilateral osteochondral defect was created in the femoral trochlear groove of 14 New Zealand white rabbits. The right knees were filled with PRP gel and the contralateral knees remained untreated and served as control sides. Some animals were killed at week 3 and others at week 12 postoperatively. The joints were harvested and assessed by Magnetic Resonance Observation of Cartilage Repair Tissue (MOCART) MRI scoring system, and examined using the International Cartilage Repair Society (ICRS) macroscopic and ICRS histological scoring systems. Additionally, the collagen type II content was evaluated by the immunohistochemical staining. RESULTS: After 12 weeks post-surgery, the defects of the PRP group were repaired by hyaline cartilage-like tissue. However, incomplete cartilage regeneration was observed in the PRP group for three weeks. The control groups showed fibrocartilaginous or fibrous tissue, respectively, at each timepoint. CONCLUSION: Our study proved that the use of PRP gel without any adjuncts could successfully produce a good healing response and resurface the osteochondral defect with a better quality of cartilage in a rabbit model. Cite this article: Bone Joint Res 2021;10(3):192-202.