Journal of Medicine, Surgery, and Public Health最新文献

{"title":"Temporal variations in and predictive values of ABG results prior to in-hospital cardiac arrest","authors":"Mina Attin , Jie Ren , Chad Cross , Sidath Kapukotuwa , Ryan Shao , Peter G. Kaufmann , C.D. (Joey) Lin , Kim Arcoleo","doi":"10.1016/j.glmedi.2024.100143","DOIUrl":"10.1016/j.glmedi.2024.100143","url":null,"abstract":"<div><div>In-hospital cardiac arrest (IHCA) has been understudied relative to out-of-hospital cardiac arrest. Further, studies of IHCA have mainly focused on a limited number of pre-arrest patient characteristics (e.g., demographics, number and types of comorbidities). Arterial blood gas (ABG) analysis, one of the most common diagnostic tests for assessing and managing critically or acutely ill hospitalized patients, reflects pathophysiological changes associated with adverse events or complications, including IHCA. Yet the predictive and prognostic values of patterns of pre-arrest ABG parameters for IHCA have not been fully studied. The purpose of this retrospective pilot cohort study was to investigate temporal variations in and predictive values of pre-IHCA ABG values among patients with a history of cardiopulmonary diseases. Eligible patients had a history of structural heart disease, heart failure, or pulmonary diseases. Patients were excluded if their IHCA was due to trauma, drug overdose, hypothermia, drowning, chronic terminal illness such as cancer or human immunodeficiency virus, or bleeding not caused by hemorrhage in the brain or heart. Also collected were dates, times, and causes of mechanical intubation prior to IHCA and causes of mortality. Co-primary outcomes were initial rhythms of IHCA and return of spontaneous circulation (ROSC). We conducted a pilot study and the ABG results (pH, partial pressure of carbon dioxide [PaCO<sub>2</sub>], partial pressure of oxygen [PaO<sub>2</sub>], bicarbonate [HCO<sub>3</sub><sup>-</sup>] , and lactate) from each of the 3 days prior to IHCA were extracted from the electronic health records (EHRs) of patients (N = 44) who had experienced IHCA at a single medical center. To characterize differences in ABG parameters among study days, coefficients of variation (CVs) were compared using the modified likelihood ratio test (MLRT) using the worst ABG values. Linear regression models were run for the continuous ABG parameters and logistic regression models for the dichotomous ABG variables. Overall model effect and least squares means, SDs, mean differences within and between days (with 95 % confidence intervals), <em>p</em>-values and effect sizes were reported for continuous variables. For categorical variables, estimates and standard errors, 95 % confidence intervals, Wald X2 variables and <em>p</em>-values were presented. The CVs for pH, PaCO<sub>2</sub>, and HCO<sub>3</sub><sup>-</sup> differed significant between study days (<em>p</em> <.05). The least squares means with 95 % confidence intervals for pH and lactate differed significantly in days (<em>p</em> <.01). Moderate to large effect sizes were obtained for all ABG parameters. Arterial lactate predicted initial rhythm (shockable versus non-shockable) and ROSC, while pH and HCO<sub>3</sub><sup>-</sup> predicted ROSC. Results demonstrate, for the first time, the presence of significant variability in ABG parameters across 72 h prior to IH","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"4 ","pages":"Article 100143"},"PeriodicalIF":0.0,"publicationDate":"2024-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142554959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Epiploic appendagitis: A case report and review of diagnostic challenges","authors":"Usamah Al-Anbagi ,&nbsp;Abdulrahman Saad ,&nbsp;Tarek Ibrahim ,&nbsp;Abdulqadir J. Nashwan","doi":"10.1016/j.glmedi.2024.100148","DOIUrl":"10.1016/j.glmedi.2024.100148","url":null,"abstract":"<div><div>Epiploic appendagitis is a rare, self-limiting inflammatory condition affecting the epiploic appendages, which often mimics other acute abdominal conditions such as appendicitis or diverticulitis, creating a diagnostic challenge for healthcare providers. In this case, a 37-year-old male presented with sharp, non-radiating right lower quadrant abdominal pain lasting two days, accompanied by nausea. Upon physical examination, localized tenderness was noted without signs of rebound or guarding. A contrast-enhanced CT scan revealed a 2.5 cm ovoid lesion with fatty stranding on the cecum wall, along with adjacent reactive lymph nodes, confirming the diagnosis of epiploic appendagitis. Given its rarity, this condition should be included in the differential diagnosis for acute abdominal pain, as accurate diagnosis through appropriate imaging can prevent unnecessary surgical interventions and ensure effective management.</div></div>","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"4 ","pages":"Article 100148"},"PeriodicalIF":0.0,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142529261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A case report of brainstem encephalitis associated with systemic lupus erythematosus in a young female","authors":"Muhammad Nawaz Khan ,&nbsp;Muniba Fatima ,&nbsp;Muhammad Mubashir ,&nbsp;Syed Muhammad Sinaan Ali","doi":"10.1016/j.glmedi.2024.100145","DOIUrl":"10.1016/j.glmedi.2024.100145","url":null,"abstract":"<div><div>We present a rare case of autoimmune brainstem encephalitis, a serious inflammatory condition affecting the brainstem, in a 20-year-old female simultaneously with systemic lupus erythematosus (SLE). Brainstem encephalitis can be caused by various infectious diseases, autoimmune disorders, and paraneoplastic syndromes. When associated with autoimmune disorders, its diagnosis and management can be challenging.Symptoms typically include those of the underlying autoimmune disorder, along with features of encephalitis such as headache, altered consciousness, fever, seizures, and cranial nerve involvement. Our patient presented with fever, seizures, and signs indicative of SLE, which were later confirmed through various antibody profiles. The patient was treated with steroids and immunosuppressants, showing a positive response, and was eventually discharged. This case highlights the diagnostic challenges and treatment approaches employed to manage symptoms and address the disease. Autoimmune brainstem encephalitis caused by SLE is a rare but potentially morbid condition, often diagnosed late. Looking out for specific signs and symptoms leads to prompt diagnosis and timely management. SLE encephalitis is rarely reported and poorly understood.Therefore, further research is required.</div></div>","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"4 ","pages":"Article 100145"},"PeriodicalIF":0.0,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142529263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Giant fecaloma: Can early surgical intervention prevent stercoral peritonitis?","authors":"Najib Bahrou ,&nbsp;El Khalil Cherif ,&nbsp;Safa Elmouhib ,&nbsp;Jihane EL Hamzaoui ,&nbsp;Yahia ZaineAl Abidine Khedid ,&nbsp;Mohamed El Absi ,&nbsp;El Mahjoub Echarrab ,&nbsp;Mohamed El Ounani ,&nbsp;EL Alami El Faricha El Hassan","doi":"10.1016/j.glmedi.2024.100146","DOIUrl":"10.1016/j.glmedi.2024.100146","url":null,"abstract":"<div><div>Fecaloma, an accumulation of hardened fecal matter, is a clinical challenge that most often occurs in the rectum and sigmoid colon, rarely in the rest of the colon. Often overlooked, fecalomas can potentially lead to serious complications such as obstruction and perforation. Conservative management of fecaloma typically involves the use of laxatives, enemas, or digital disimpaction. However, when conservative methods are ineffective surgical intervention is required. This article presents a rare case of a 54-year-old patient with a history of tuberculous meningoradiculitis and chronic constipation, leading to a giant fecaloma presenting with severe abdominal distension. Despite conservative measures, including enemas and dietary care, the patient developed stercoral peritonitis and sigmoid colonic perforation necessitating late surgical intervention leading to death. This case allows us to engage in discussions over the correct management of this entity which is often underestimated by healthcare practitioners particularly by surgeons.</div></div>","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"4 ","pages":"Article 100146"},"PeriodicalIF":0.0,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142529262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A case report of combined hemoperfusion and hemodiafiltration utilization in pediatric severe Quetiapine poisoning","authors":"Ufuk Yükselmiş ,&nbsp;Merve Akçay ,&nbsp;Omar Alomari ,&nbsp;Müge Kömürcüoğlu Yılmaz","doi":"10.1016/j.glmedi.2024.100147","DOIUrl":"10.1016/j.glmedi.2024.100147","url":null,"abstract":"<div><div>Quetiapine is an atypical antipsychotic commonly used to manage psychotic and bipolar disorders. While quetiapine overdose is often associated with sedation, tachycardia, and QT interval prolongation on the ECG, severe hypotension and corrected QT interval (QTc) prolongation are relatively rare. There is limited information available regarding the safety of quetiapine overdose, particularly in the pediatric population. Here, we present the case of a 15-year-old girl who ingested quetiapine in a suicide attempt. A 15-year-old girl who ingested 1200 mg of quetiapine (22.6 mg/kg) in a suicide attempt. The overdose led to multiple severe symptoms, including tachycardia, agitation, hypotension, loss of consciousness, and QTc prolongation. To effectively eliminate quetiapine, we utilized a combination of hemoperfusion (HP) and continuous venovenous hemodiafiltration (CVVHDF) therapy. According to recent literature, this is the first reported pediatric case of severe quetiapine poisoning successfully treated with the combined use of HP and CVVHDF. In this report, we compare the clinical presentation with previous cases of quetiapine overdose in both pediatric and adult populations, review current treatment recommendations, and introduce a novel therapeutic approach for managing quetiapine poisoning.</div></div>","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"4 ","pages":"Article 100147"},"PeriodicalIF":0.0,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142529264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The role of social media influencers on health behaviors in Saudi Arabia","authors":"Najim Z. Alshahrani","doi":"10.1016/j.glmedi.2024.100149","DOIUrl":"10.1016/j.glmedi.2024.100149","url":null,"abstract":"<div><div>In the digital age, social media influencers (SMIs) have emerged as a significant force in altering public attitudes and behaviors, notably in the health sector. While SMIs can provide useful insights on crucial health issues such as diet and mental health, they also raise concerns about their varying levels of health competence and potential commercial biases. This dichotomy poses a challenge: can SMIs effectively contribute to better health outcomes, or do they risk encouraging harmful behavior? This letter investigates this dynamic by synthesizing findings from three cross-sectional studies undertaken in Saudi Arabia, with the goal of providing policymakers with actionable insights on how to improve public health while navigating the inherent risks.</div></div>","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"4 ","pages":"Article 100149"},"PeriodicalIF":0.0,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142529265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Emergence of a more virulent clade of Mpox in Africa: Learning from history and charting a path forward","authors":"Isaac Iyinoluwa Olufadewa,&nbsp;Ruth Ifeoluwa Oladele ,&nbsp;Oluwatayo Ayobami Olajide,&nbsp;Harrison Toluwanimi Adetunji,&nbsp;Godwin Edoseawe Okoduwa,&nbsp;Toluwase Ayobola Olufadewa,&nbsp;Miracle Ayomikun Adesina","doi":"10.1016/j.glmedi.2024.100134","DOIUrl":"10.1016/j.glmedi.2024.100134","url":null,"abstract":"<div><p>The resurgence of Mpox (formerly known as Monkeypox) in Africa, marked by a 160 % increase in cases and a 19 % rise in deaths in 2024 compared to the previous year, is driven by the emergence of a more virulent clade 1b variant. This resurgence, declared a Public Health Emergency of International Concern by the World Health Organization, highlights the persistent challenges in global health equity, particularly in vaccine distribution, public health infrastructure, and surveillance. Drawing from historical lessons, including vaccine inequity during the COVID-19 pandemic and delayed responses in past outbreaks, this paper outlines critical strategies for addressing the current crisis. These strategies include strengthening vaccine equity and access, enhancing community-level surveillance, promoting research and development, implementing comprehensive public health campaigns, and addressing environmental factors that facilitate outbreaks. The paper emphasizes the need for international solidarity and support, proposing the establishment of a global accord to ensure equitable sharing of resources during health emergencies and to prevent low- and middle-income countries from being left behind.</p></div>","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"3 ","pages":"Article 100134"},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949916X24000872/pdfft?md5=e2e72311dc4ea75fbc2e13a74cd18f31&pid=1-s2.0-S2949916X24000872-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142117543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence and big data for pharmacovigilance and patient safety","authors":"Muhammad Aasim Shamim,&nbsp;Muhammad Aaqib Shamim,&nbsp;Pankaj Arora,&nbsp;Pradeep Dwivedi","doi":"10.1016/j.glmedi.2024.100139","DOIUrl":"10.1016/j.glmedi.2024.100139","url":null,"abstract":"&lt;div&gt;&lt;div&gt;Pharmacovigilance, the science of monitoring drug safety, plays a crucial role in identifying and mitigating adverse drug reactions (ADRs). However, underreporting in pharmacovigilance systems—estimated to have a median rate of 94 %—poses a significant threat to patient safety by hindering the detection of safety signals. The need to address these gaps is paramount, especially with the rising complexity of healthcare data. The advent of artificial intelligence (AI) and big data technologies offers promising solutions to overcome the limitations of traditional pharmacovigilance methods.&lt;/div&gt;&lt;div&gt;The application of AI and machine learning (ML) technologies, including natural language processing (NLP) and deep learning, has the potential to revolutionize drug safety monitoring by automating the detection of ADRs from diverse data sources, such as electronic health records (EHRs), spontaneous reporting systems, and social media. These tools can process unstructured data and uncover patterns not easily identifiable through conventional approaches. Additionally, AI can enable real-time pharmacovigilance, which is especially critical in an era of increasing polypharmacy and diverse patient populations. AI-driven models are being utilized to detect drug-drug interactions (DDIs), predict ADRs, and enhance the overall efficiency of pharmacovigilance processes.&lt;/div&gt;&lt;div&gt;Despite these advancements, several challenges remain. The performance of AI models is heavily dependent on the quality and quantity of data available. Inadequate or poorly curated datasets can lead to inaccurate ADR detection, particularly in resource-limited settings. Moreover, the heterogeneity of data sources necessitates robust AI models capable of integrating various types of data while ensuring accurate and reliable outputs. There is also a pressing need to address the transparency and explainability of AI models, as the opaque decision-making processes of current algorithms often impede their acceptance among pharmacovigilance professionals.&lt;/div&gt;&lt;div&gt;Future directions must focus on improving the quality and standardization of datasets, advancing NLP techniques for better interpretation of clinical narratives, and developing explainable AI models. Regulatory frameworks should evolve to support AI deployment in pharmacovigilance, ensuring the establishment of best practices for AI implementation and the creation of large-scale, publicly available training datasets.&lt;/div&gt;&lt;div&gt;Additionally, AI models should go beyond correlation-based approaches by integrating causal inference techniques, which will allow for a more accurate understanding of the relationship between drugs and ADRs. Human oversight will still be required to validate AI findings, but ongoing efforts to improve the robustness of AI systems will reduce dependency on manual interventions and scale the use of AI in pharmacovigilance.&lt;/div&gt;&lt;div&gt;The integration of AI and big data in pharmacovigilance has the potenti","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"3 ","pages":"Article 100139"},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence for medicine, surgery, and public health","authors":"Jagdish Khubchandani,&nbsp;Srikanta Banerjee,&nbsp;Robert Andrew Yockey,&nbsp;Kavita Batra","doi":"10.1016/j.glmedi.2024.100141","DOIUrl":"10.1016/j.glmedi.2024.100141","url":null,"abstract":"<div><div>Artificial Intelligence (AI) has rapidly transformed many sectors, including medicine, surgery, and public health. While AI has a multitude of unique characteristics that differ from the existing and most commonly used healthcare technologies worldwide, the discussion and publications on AI in healthcare have grown exponentially within the past few years. Despite its transformative potential, AI poses several challenges and there are unanswered questions related to the value and impact of AI on consumers, healthcare providers, and health systems. This editorial explores the growing applications of AI and its potential impacts on key entities in the field of healthcare and public health. Also, through this editorial, the journal editors highlight the urgent need for high-quality and real-world setting-based research on the value of AI in healthcare and public health. Finally, as AI will undoubtedly and significantly continue to impact healthcare consumers and systems, the editors are seeking submissions with rigorous and empirical evidence for AI’s impact on health services consumers and providers, and clinical care facilities or public health organizations. The editors believe that unless scholars worldwide generate robust evidence on the value and impact of AI in healthcare, providing the highest benefits of AI to health services consumers will remain an elusive goal.</div></div>","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"3 ","pages":"Article 100141"},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial Intelligence and the Dehumanization of Patient Care","authors":"Adewunmi Akingbola,&nbsp;Oluwatimilehin Adeleke,&nbsp;Ayotomiwa Idris,&nbsp;Olajumoke Adewole,&nbsp;Abiodun Adegbesan","doi":"10.1016/j.glmedi.2024.100138","DOIUrl":"10.1016/j.glmedi.2024.100138","url":null,"abstract":"<div><p>The integration of artificial intelligence (AI) into healthcare is rapidly transforming patient care, offering numerous advantages in diagnostics, efficiency, and clinical decision-making. However, this technological shift raises significant concerns about the potential erosion of the doctor-patient relationship, a cornerstone of effective medical practice. AI’s increasing role risks depersonalizing healthcare, as the emphasis on data-driven decisions may overshadow the empathy, trust, and personalized care traditionally provided by human clinicians. The \"black-box\" nature of AI algorithms further exacerbates this issue, as the lack of transparency in AI decision-making processes can undermine patient trust. Additionally, AI systems trained on biased datasets may inadvertently widen health disparities, particularly for underrepresented populations. While AI has the potential to streamline routine tasks and reduce the burden on healthcare providers, it is essential to ensure that these advancements do not come at the cost of the human connection vital to patient care. To address these challenges, future research and development should focus on creating AI systems that enhance, rather than replace, the compassionate aspects of healthcare. This balanced approach is crucial to preserving the integrity of the doctor-patient relationship while harnessing the benefits of AI, ultimately ensuring that technological progress aligns with the core values of medical practice.</p></div>","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"3 ","pages":"Article 100138"},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949916X24000914/pdfft?md5=707efee72649c5150fa05ce58c065d61&pid=1-s2.0-S2949916X24000914-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142136385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}