Clinical Rule Research Articles

Adaptive questionnaires for facilitating patient data entry in clinical decision support systems: methods and application to STOPP/START v2

Clinical decision support systems are software tools that help clinicians to make medical decisions. However, their acceptance by clinicians is usually rather low. A known problem is that they often require clinicians to manually enter a lot of patient data, which is long and tedious. Existing solutions, such as the automatic data extraction from electronic health record, are not fully satisfying, because of low data quality and availability. In practice, many systems still include long questionnaire for data entry. In this paper, we propose an original solution to simplify patient data entry, using an adaptive questionnaire, i.e. a questionnaire that evolves during user interaction, showing or hiding questions dynamically. Considering a rule-based decision support systems, we designed methods for determining the relationships between rules and translating the system’s clinical rules into display rules that determine the items to show in the questionnaire, and methods for determining the optimal order of priority among the items in the questionnaire. We applied this approach to a decision support system implementing STOPP/START v2, a guideline for managing polypharmacy. We show that it permits reducing by about two thirds the number of clinical conditions displayed in the questionnaire, both on clinical cases and real patient data. Presented to clinicians during focus group sessions, the adaptive questionnaire was found “pretty easy to use”. In the future, this approach could be applied to other guidelines, and adapted for data entry by patients.

Research Progress on the Treatment of Vascular Vertigo with Active Ingredients of Pueraria Lobata

Vascular vertigo is a common disease among middle-aged and elderly patients with vertigo, caused by cerebrovascular diseases, which seriously affects the quality of life of patients. Its pathogenesis is diverse, and there is still a lack of clear and effective therapeutic drugs in clinical practice. Pueraria lobata, as a commonly used traditional Chinese medicine for treating brain diseases, is widely used in clinical practice and has great development prospects. By summarizing the network pharmacology and clinical medication rules of vascular vertigo, it was found that Pueraria lobata is a high-frequency single traditional Chinese medicine for treating this disease. Modern pharmacological research has found that the main components of Pueraria lobata, such as isoflavones, triterpenes, coumarins, and alkaline compounds, can all play a preventive and therapeutic role in vascular dizziness. This article summarizes the published domestic and foreign papers and experiments, and takes the pathogenesis of vascular vertigo and the pharmacological characteristics of Pueraria lobata as a breakthrough point. Through sorting, it was found that Pueraria lobata exerts pharmacological effects in improving vascular endothelial function, regulating lipid metabolism, anticoagulation and antithrombotic effects, inhibiting oxidative stress, and regulating inflammatory reactions, and has significant effects on the clinical treatment of vascular vertigo.

A-195 Combination of Lean Mindset, Robotics and Digitalization allowed us to manage a 2.5 times increase in workload in our central reference lab

Abstract Background Our Agilus Diagnostics, Gurugram, India is a Central Reference Laboratory and part of the pan-India network over 400 lab in India. Our Gurugram lab delivers 3,200 tubes in the serum work area in 17 hour operations daily and is ISO 15189 and CAP accredited.In Jan 2023, our lab started to support Govt PHC Program samples and our workload increased to 8000 tubes. This was a clear operational and clinical challenge for us with a 2.5 x jump in workload. To achieve this goal, a lean mindset with process improvement steps were to be applied required across the total testing process. This lean approach was supported by cobas ® Lab Automation systems managed by navify ® Lab Operations informatics automation solution. This poster explains our journey of planning, implementing, and delivering on our goal of predictable operational efficiency when faced with this challenge. Methods We took 4 major steps We redesigned lab processes using lean process improvement operational dashboards. This poster will show the metric we track which help eliminate waste in the system. We optimized our total lab automation solution with smart load balancing across cobas ® Pro integrated analyzers and staff friendly recursive workflow. Clear and strict use of off peak hours for maintenance and QC procedures and standardized predictable schedule of operation. This poster will share our time table with key milestones across the 24 hours We built on the Informatics solution using 5 layered Auto verification rules based decision framework. IQC, Systems Flags check, Sample Quality checks, Biological Reference check, custom Auto verification Range, Critical ranges Delta check Criteria, Clinical Correlation Rule are all part of the auto verification logic framework. Results We were able to deliver the following results.Lean process design led to 53% simplification. Number of process steps reduced to 29 from 62 steps across the total testing process. Total Lab Automation has helped improve 90 percentile production TAT by 46% from 250 mins to 135 mins Our 90 % TAT CV has significantly reduced making our production predictable. Over 17,500 results / day reported are subject to auto verification with 87 % of all results auto-verified and auto-approved. Not a single additional employee was added in the analytical or post analytical areas of the lab operations Conclusions Lean Mindset complemented by Total Laboratory Automation along with Decision Automation on an Informatics solution has enhanced lab performance in terms of TAT, Efficiency, and Staff Motivation. This poster will also demonstrate using incremental effectiveness analysis comparative data of key performance indicators, such predictability in production, and efficiency of workforce, senior staff time saved, before and after technology deployment. The challenge of increase in sample workload is real in India and this approach allows for a sustainable way to ensure patient impact with minimum burden on our workforce.

Review on Tuberculosis

Abstract: Tuberculosis (TB) is an airborne irresistible infection brought about by creatures of the Mycobacterium tuberculosis complex. Tuberculosis (TB) stays perhaps of the deadliest irresistible infection liable for a great many passings yearly across the world. Disease with M. tuberculosis can develop from control in the host, in which the microbes are segregated inside granulomas (dormant TB disease), to an infectious state, wherein the patient will show side effects that can incorporate hack, fever, night sweats and weight reduction. Just dynamic pneumonic TB is infectious. In this paper we present an overall outline of TB including the pathogenesis, conclusion, and treatment rules. In readiness of this review, we scanned PubMed for applicable articles on TB. Moreover, we looked through the sites of global establishments like the World Wellbeing Association (WHO) and the US Communities for Infectious prevention and Avoidance (CDC) for related reports and clinical rules. This paper brings been composed with the expectation to the table for general schooling to wellbeing experts, strategy creators, patients and people in general.

Efficiency of computerized clinical decision support systems involving anticoagulants: A flashmob study in Dutch hospital pharmacies.

Computerized decision support systems (CDSSs) aim to prevent adverse drug events. However, these systems generate an overload of alerts that are not always clinically relevant. Anticoagulants are frequently involved in these alerts. The aim of this study was to investigate the efficiency of CDSS alerts on anticoagulants in Dutch hospital pharmacies. A multicentre, single-day, cross-sectional study was conducted using a flashmob design in Dutch hospital pharmacies, which have CDSSs that operate on both a national medication surveillance database and on self-developed clinical rules. Hospital pharmacists and pharmacy technicians collected data on the number and type of alerts and time needed for assessing these alerts. The primary outcome was the CDSS efficiency on anticoagulants, defined as the percentage of alerts on anticoagulants that led to an intervention. Secondary outcomes where among other CDSSs efficiency related to any medications and the time expenditure. Descriptive data-analysis was used. Of the 69 hospital pharmacies invited, 42 (61%) participated. The efficiency of CDSS alerts on anticoagulants was 4.0% (interquartile range [IQR] 14.0%) for the national medication surveillance database alerts and 14.3% (IQR 40.0%) for alerts from clinical rules. For any medication, the efficiency was lower: 1.8% (IQR 7.5%) and 13.4% (IQR 21.5%) respectively. The median time for assessing the relevance of all alerts was 2 (IQR 1:21) h/day for pharmacists and 6 (IQR 5:01) h/day for pharmacy technicians. CDSS efficiency is generally low, both for anticoagulants and any medication, while the time investment is high. Optimization of CDSSs is needed.

Effectiveness of the YEARS Algorithm Added to Classical Clinical Decision-making Rules in Suspected Pulmonary Embolism

Effectiveness of the YEARS Algorithm Added to Classical Clinical Decision-making Rules in Suspected Pulmonary Embolism

GLAD TIDINGS FOR INDIAN PHARMACEUTICAL INDUSTRY

Dear Reader, It is indeed heartening to note that the Indian Government has notified Rules for fast-track launch of new, breakthrough drugs including block-buster molecules, waiving or bypassing clinical trials in India under Chapter V of the Rules, where the relevant drug has already been approved in specified countries, such as the European Union, US, UK, Japan, Australia and Canada. This decision was announced through an executive order specifying the list of developed countries under Rule 101 of the New Drugs and Clinical Trials Rules (NCDT) 2019, issued by the DCGI, Dr. Rajeev Singh Raghuvanshi. For the time being, the list of drugs covered under the order for approval of new drugs, under Chapter X are restricted to those for treatment of orphan drugs (rare diseases), new drugs for special defence purposes and those used in pandemic diseases, gene and cellular therapy products. It is further to be noted that drugs having significant therapeutic advances over the standard care, are also covered under this notification waiving domestic clinical trials. Indirectly, this waiver will not only help State Government and other public procurement agencies such as DGHS and Ayushman Bharat to reduce expenditure in their budgets, but also do away with animal trials in India in line with Indian and global initiatives. This initiative to selectively waive clinical trials will be a boon to research-based Indian Pharma companies too, for introducing generic equivalents of these drugs having significant therapeutic benefits to patients.

Automating population dose survey processing-An Australian feasibility study.

A comprehensive collection of data on doses in adult computed tomography procedures in Australia has not been undertaken for some time. This is largely due to the effort involved in collecting the data required for calculating the population dose. This data collection effort can be greatly reduced, and the coverage increased, if the process can be automated without major changes to the workflow of the imaging facilities providing the data. Success would provide a tool to determine a truly national assessment of the dose incurred through diagnostic imaging in Australia. The aims of this study were to develop an automated tool to categorize electronic records of imaging procedures into a standardized set of broad procedure types, to validate the tool by applying it to data collected from nine facilities, and to assess the feasibility of applying the automated tool to compute population dose and determine the data manipulations required. A rule-based classifier was implemented capitalizing on semantic and clinical rules. The keyword list was initially built from 609 unique study descriptions. It was then refined using an additional 414 unique study descriptions. The classifier was then tested on an additional 1198 unique study descriptions. Input from a radiologist provided the ground truth for the refinement of the classifier. From a sample of 238139 studies containing 2794 unique study descriptions, the classifier correctly classified 2789 study types with only five misclassifications, demonstrating the feasibility of automating the process and the need for data pre-processing. Dose statistics for 21 categories were compiled using the 238139 studies. The classifier achieved excellent classification results using the testing data supplied by the facilities. However, since all data supplied were from public facilities, the performance of the classifier may be biased. The performance of the classifier is yet to be tested on a more representative mix of private and public facilities.

Bridging School and Practice? Barriers to the Integration of 'Boundary Objects' for Learning and Assessment in Clinical Nursing Education.

In clinical health professions education, portfolios, assignments and assessment standards are used to enhance learning. When these tools fulfill a bridging function between school and practice, they can be considered 'boundary objects'. In the clinical setting, these tools may be experienced as time-consuming and lacking value. This study aimed to investigate the barriers to the integration of boundary objects for learning and assessment from a Cultural-Historical Activity Theory (CHAT) perspective in clinical nursing education. Nineteen interviews and five observations were conducted with team leads, clinical educators, supervisors, students, and teachers to obtain insight into intentions and use of boundary objects for learning and assessment. Boundary objects (assessment standards, assignments, feedback/reflection/patient care/development plan templates) were collected. The data collection and thematic analysis were guided by CHAT. Barriers to the integration of boundary objects included: a) conflicting requirements in clinical competency monitoring and assessment, b) different application of analytical skills, and c) incomplete integration of boundary objects for self-regulated learning into supervision practice. These barriers were amplified by the simultaneous use of boundary objects for learning and assessment. Underlying contradictions included different objectives between school and practice, and tensions between the distribution of labor in the clinical setting and school's rules. School and practice have both convergent and divergent priorities around students' clinical learning. Boundary objects can promote continuity in learning and increase students' understanding of clinical practice. However, effective integration requires for flexible rules that allow for collaborative learning around patient care.

Evaluation and implementation of optimized antimicrobial dosing strategies in obese and underweight patients.

We aimed to develop and implement dosing recommendations for antimicrobials in obese and underweight patients within an academic hospital, and assess their impact on antibiotic prescribing. A multi-step approach project was performed. First, obese and underweight patient prevalence and antimicrobial prescription frequency was determined in a point prevalence study. Second and third, a literature review and e-survey provided dosing evidence. Fourth, a consensus meeting was organized to formulate dosing recommendations. Fifth, these were implemented in our clinical validation service as six clinical rules continuously screening patients' records for potentially inappropriate prescriptions (PIPs). Uptake was evaluated by documenting the number of advices and acceptance rate. Last, an interrupted time series analysis (ITS) compared pre- and post-implementation periods to measure the impact of the intervention on residual PIPs/day. A residual PIP was defined as a PIP which persisted up to 48h. First, 41% of 15.896 hospitalized patients received antimicrobials over 20days; of which 12% were obese and 9% underweight. Antibiotics were predominantly prescribed according to standard dosing regimens, adjusted to renal function. Next, six dosing recommendations, derived from literature, survey, and consensus, were implemented. In the fifth step, during an 18-week period, 219 advices were given, with 86% acceptance rate. Last, in the ITS analysis, at preintervention, a median of 75% residual PIPs/day existed, reduced to 0% postintervention. Use of clinical rules resulted in a significant immediate 84% relative reduction in residual PIPs (95% CI 0.55-0.94). After conducting a literature review, e-survey, and seeking consensus from a panel of experts, dosing recommendations for antimicrobial treatment in both obese and underweight patients were developed. These recommendations have been successfully implemented into clinical practice, addressing the specific needs of these patient populations.

Fifty-five cases of hepatic alveolar echinococcosis combined with lymph node metastasis: A retrospective study.

Lymph node metastasis is a specific type of metastasis in hepatic alveolar echinococcosis (AE). Currently, there is a scarcity of describing the clinical characteristics and lymph node metastasis rules of patients with hepatic AE combined with lymph node metastasis and its mechanism and management are still controversial. Radical hepatectomy combined with regional lymph node dissection is a better treatment. To analyse the clinical features of hepatic AE combined with lymph node metastasis to explore its treatment and efficacy. A total of 623 patients with hepatic AE admitted to the First Affiliated Hospital of Xinjiang Medical University from 1 January 2012 to 1 January 2022 were retrospectively analysed. Fifty-five patients with combined lymph node metastasis were analysed for their clinical data, diagnosis and treatment methods, follow-up efficacy, and characteristics of lymph node metastasis. Finally, we comparatively analysed the lymph node metastasis rates at different sites. Categorical variables are expressed as frequencies and percentages, and the analysis of difference was performed using the χ 2 test. The Bonferroni method was used for pairwise comparisons when statistical differences existed between multiple categorical variables. A lymph node metastasis rate of 8.8% (55/623) was reported in patients with hepatic AE, with a female predilection (69.1%) and a statistically significant sex difference (χ 2 = 8.018, P = 0.005). Of the 55 patients with lymph node metastasis, 72.7% had a parasite lesion, neighbouring organ invasion, and metastasis stage of P3N1M0 and above, of which 67.3%, 78.2%, and 34.5% of hepatic AE lesions invaded the bile ducts, blood vessels, and distant metastases, respectively. Detection rates of lymph node metastasis of 16.4%, 21.7%, and 34.2% were reported for a preoperative abdominal ultrasound, magnetic resonance imaging, and computed tomography examinations. All patients were intraoperatively suspected with enlarged lymph nodes and underwent radical hepatectomy combined with regional lymph node dissection. After surgery, a routine pathological examination was conducted on the resected lymph nodes. A total of 106 positive lymph nodes were detected in six groups at various sites, including 51 single-group metastasis cases and four multi-group metastasis cases. When the metastasis rates at different sites were statistically analysed, we observed that the metastasis rate in the para-hepatoduodenal ligament lymph nodes was significantly higher than that of the other sites (χ 2 = 128.089, P = 0.000 < 0.05). No statistical difference was observed in the metastasis rate between the five other groups. Clavien-Dindo grade IIIa complication occurred in 14 cases, which improved after administering symptomatic treatment. Additionally, lymph node dissection-related complications were not observed. Recurrence after 2 years was observed in one patient. Lymph node metastasis is a rare form of metastasis in hepatic AE, which is more frequent in women. Para-hepatoduodenal ligament lymph nodes are commonly observed. Radical hepatectomy combined with regional lymph node dissection is a safe, effective, and feasible treatment for liver AE combined with lymph node metastasis.

Cancer Trials Ecosystem in India-Ready for Prime Time?

Executing global clinical trials for cancer is a long, expensive, and complex undertaking. While selecting countries global studies, sponsors must consider several aspects including patient pool, quality of trained investigators, competing trials, availability of infrastructure, and financial investment versus returns. With a large, often treatment-naïve, and diverse patient pool, relatively low cost, good quality health care facilities in urban areas, and a robust and well-trained workforce, India offers several advantages for conducting oncology clinical trials. However, there remains challenges, including a shifting regulatory environment in recent decades. With the implementation of the New Drugs and Clinical Trial Rules in 2019, India's regulatory atmosphere seems to have stabilized. In this article, we present a review of the evolving clinical trial landscape in India, highlight the current regulatory scenario, and discuss the advantages and challenges of selecting India as a potential location for conducting global oncology clinical trials.

Involving logical clinical knowledge into deep neural networks to improve bladder tumor segmentation

Segmentation of bladder tumors from medical radiographic images is of great significance for early detection, diagnosis and prognosis evaluation of bladder cancer. Deep Convolution Neural Networks (DCNNs) have been successfully used for bladder tumor segmentation, but the segmentation based on DCNN is data-hungry for model training and ignores clinical knowledge. From the clinical view, bladder tumors originate from the mucosal surface of bladder and must rely on the bladder wall to survive and grow. This clinical knowledge of tumor location is helpful to improve the bladder tumor segmentation. To achieve this, we propose a novel bladder tumor segmentation method, which incorporates the clinical logic rules of bladder tumor and bladder wall into DCNNs to harness the tumor segmentation. Clinical logical rules provide a semantic and human-readable knowledge representation and are easy for knowledge acquisition from clinicians. In addition, incorporating logical rules of clinical knowledge helps to reduce the data dependency of the segmentation network, and enables precise segmentation results even with limited number of annotated images. Experiments on bladder MR images collected from the collaborating hospital validate the effectiveness of the proposed bladder tumor segmentation method.

A clinical decision instrument for head CT in intoxicated patients presenting to the emergency department: the DITCH study

Performing head CT in intoxicated patients presenting to the emergency department (ED) is common, yet low yield. In our previous study, acute findings were found only in patients with at least one of: neurological Deficits, Intubation, Trauma, Convulsions or Headache. We hypothesise that the absence of these DITCH clinical features rules out the need for immediate CT. We collected data for intoxicated patients attending EDs in our district from March 2021 to May 2022 inclusive. We recorded clinical presentation features, agents, disposition and head CT results. There were 1,308 intoxicated patients out of a total of 219,273 ED presentations. Median age was 38 years. Common ingestions were ethanol, stimulants, GABA-ergics and opioids. 407 patients (31%) had head CT, with 31 patients (7.6%) having 36 acute findings: 19 intracranial haemorrhages, 8 fractures, 2 cerebral oedema and 7 haematomas. All patients with acute CT findings had one of the DITCH features, and all had trauma. The sensitivity and NPV of the hypothesis were 100%. In patients that were not scanned, there were no re-presentations.Our internal validation study is further evidence that acute findings on head CT in intoxicated patients presenting to the ED are only found in those who had one of the DITCH features.

Childhood internalizing, externalizing and attention symptoms predict changes in social and nonsocial screen time.

While accumulating research has tested the hypothesis that screen time causes psychiatric symptoms in children, less attention has been paid to the hypothesis that children with psychiatric symptoms change their patterns of screen time and digital media use. We aimed to test whether children with psychiatric symptoms subsequently change their patterns of screen time and digital media use. N = 9,066 children primarily aged 9-10 in the Adolescent Brain Cognitive Development Study at baseline and 1-year later. Psychiatric symptoms included internalizing, attention, and externalizing symptoms. Screen time was measured as ordinally defined weekday and weekend time on social and nonsocial [e.g., YouTube] digital media). Models assessed psychiatric symptoms as predictors of screen time, and screen time as predictors of psychiatric symptoms, controlled for baseline measures of each, sex, age, race/ethnicity, and income. Children with psychiatric symptoms spent more time on non-social media one year later compared with peers. Considering total psychiatric problems, clinical levels of problems predicted higher levels of weekday (OR = 1.22, 95% CI 1.22-1.23) and weekend (OR = 1.10, 95% CI 1.09-1.11) nonsocial screen time. For nearly all analyses of psychiatric symptoms predicting screen time, associations were highest for a non-social screen time outcome rather than a social screen time outcome (Highest OR = 1.65, 95% CI 1.63-1.67, clinical rule breaking predicting weekday nonsocial screen time). Comparable magnitude associations were observed for social and nonsocial media use predicting future psychiatric symptoms, suggesting bidirectionality. Children with psychiatric symptoms have different subsequent media use patterns, including higher rates of subsequent nonsocial engagement. Ensuring that ongoing data collection and analysis efforts attend to temporality and transitions in the relation between media use and psychiatric symptoms will accelerate progress in the field.

Infection Control Through Clinical Pipelines Built with Arden Syntax MLM Building Blocks.

Healthcare-associated infections (HAIs) may have grave consequences for patients. In the case of sepsis, the 30-day mortality rate is about 25%. HAIs cost EU member states an estimated 7 billion Euros annually. Clinical decision support tools may be useful for infection monitoring, early warning, and alerts. MONI, a tool for monitoring nosocomial infections, is used at University Hospital Vienna, but needs to be clinically and technically revised and updated. A new, completely configurable pipeline-based system for defining and processing HAI definitions was developed and validated. A network of data access points, clinical rules, and explanatory output is arranged as an inference network, a clinical pipeline as it is called, and processed in a stepwise manner. Arden-Syntax-based medical logic modules were used to implement the respective rules. The system was validated by creating a pipeline for the ECDC PN5 pneumonia rule. It was tested on a set of patient data from intensive care medicine. The results were compared with previously obtained MONI output as a suitable reference, yielding a sensitivity of 93.8% and a specificity of 99.8%. Clinical pipelines show promise as an open and configurable approach to graphically-based, human-readable, machine-executable HAI definitions.

Recognition of Glaucomatous Fundus Images Using Machine Learning Methods Based on Optic Nerve Head Topographic Features.

Machine learning classifiers are an effective approach to detecting glaucomatous fundus images based on optic disc topographic features making it a straightforward and effective approach. Retrospective case-control study. The aim was to compare the effectiveness of clinical discriminant rules and machine learning classifiers in identifying glaucomatous fundus images based on optic disc topographic features. The study used a total of 800 fundus images, half of which were glaucomatous cases and the other half non-glaucomatous cases obtained from an open database and clinical work. The images were randomly divided into training and testing sets with equal numbers of glaucomatous and non-glaucomatous images. An ophthalmologist framed the edge of the optic cup and disc, and the program calculated five features, including the vertical cup-to-disc ratio and the width of the optic rim in four quadrants in pixels, used to create machine learning classifiers. The discriminative ability of these classifiers was compared with clinical discriminant rules. The machine learning classifiers outperformed clinical discriminant rules, with the extreme gradient boosting method showing the best performance in identifying glaucomatous fundus images. Decision tree analysis revealed that the cup-to-disc ratio was the most important feature for identifying glaucoma fundus images. At the same time, the temporal width of the optic rim was the least important feature. Machine learning classifiers are an effective approach to detecting glaucomatous fundus images based on optic disc topographic features and integration with an automated program for framing and calculating the required parameters would make it a straightforward and effective approach.

Comparing accuracy of clinical prediction rules to predict pneumonia in children and adolescents with acute febrile respiratory illness

AbstractBackgroundIt is a common challenge for emergency physicians to differentiate pneumonia from simple upper respiratory tract infections. Several clinical prediction rules exist to assist the diagnosis process and guide the clinical decisions of ordering investigations such as chest X‐ray (CXR).ObjectiveThis study aims to validate and compare the accuracy of various prediction rules in the setting of children and adolescents presenting with acute febrile respiratory illness (AFRI).MethodThis was a prospective multicentre study. Three hundred and fifty‐five patients, aged 6–18 years, were recruited. Patients with immunocompromised state or hypoxia were excluded. Pneumonia was defined as diagnosis by CXR or subsequent diagnosis of pneumonia upon re‐attendance within 7 days. Clinical rules including Diehr rule, Heckerling rule, Bilkis simpler rule, the AFRI rule, the paediatric acute febrile respiratory illness rule (PAFRI) were compared in terms of accuracy of predicting pneumonia in the recruited subjects and presented as receiver operating characteristic curves.ResultsFive patients were excluded. In the 350 patients included, 38 were diagnosed as pneumonia by CXR and 1 was subsequently diagnosed as pneumonia upon re‐attendance. The area under the receiver operating characteristic curve of Diehr rule, Heckerling rule, Bilkis simpler rule, AFRI rule and PAFRI rule were 0.703, 0.565, 0.59, 0.807 and 0.846 respectively. The PAFRI rule is superior to other prediction rules in terms of diagnostic accuracy. At the cut‐off of PAFRI ≥0, the rule has high sensitivity of 97.44% and negative predictive value of 99.09%.ConclusionAmong the rules compared, the PAFRI rule has the highest diagnostic accuracy in assisting emergency physicians to identify pneumonia among children and adolescents aged 6–18 years presenting with AFRI.

Clinical decision support system supported interventions in hospitalized older patients: a matter of natural course and adequate timing

BackgroundDrug-related problems (DRPs) and potentially inappropriate prescribing (PIP) are associated with adverse patient and health care outcomes. In the setting of hospitalized older patients, Clinical Decision Support Systems (CDSSs) could reduce PIP and therefore improve clinical outcomes. However, prior research showed a low proportion of adherence to CDSS recommendations by clinicians with possible explanatory factors such as little clinical relevance and alert fatigue.ObjectiveTo investigate the use of a CDSS in a real-life setting of hospitalized older patients. We aim to (I) report the natural course and interventions based on the top 20 rule alerts (the 20 most frequently generated alerts per clinical rule) of generated red CDSS alerts (those requiring action) over time from day 1 to 7 of hospitalization; and (II) to explore whether an optimal timing can be defined (in terms of day per rule).MethodsAll hospitalized patients aged ≥ 60 years, admitted to Zuyderland Medical Centre (the Netherlands) were included. The evaluation of the CDSS was investigated using a database used for standard care. Our CDSS was run daily and was evaluated on day 1 to 7 of hospitalization. We collected demographic and clinical data, and moreover the total number of CDSS alerts; the total number of top 20 rule alerts; those that resulted in an action by the pharmacist and the course of outcome of the alerts on days 1 to 7 of hospitalization.ResultsIn total 3574 unique hospitalized patients, mean age 76.7 (SD 8.3) years and 53% female, were included. From these patients, in total 8073 alerts were generated; with the top 20 of rule alerts we covered roughly 90% of the total. For most rules in the top 20 the highest percentage of resolved alerts lies somewhere between day 4 and 5 of hospitalization, after which there is equalization or a decrease. Although for some rules, there is a gradual increase in resolved alerts until day 7. The level of resolved rule alerts varied between the different clinical rules; varying from > 50–70% (potassium levels, anticoagulation, renal function) to less than 25%.ConclusionThis study reports the course of the 20 most frequently generated alerts of a CDSS in a setting of hospitalized older patients. We have shown that for most rules, irrespective of an intervention by the pharmacist, the highest percentage of resolved rules is between day 4 and 5 of hospitalization. The difference in level of resolved alerts between the different rules, could point to more or less clinical relevance and advocates further research to explore ways of optimizing CDSSs by adjustment in timing and number of alerts to prevent alert fatigue.

Differentiating electrocardiographic indications of massive and submassive pulmonary embolism: A cross-sectional study in Southern Iran from 2015 to 2020.

Although using electrocardiogram (ECG) for pulmonary embolism (PE) risk stratification has shown mixed results, it is currently used as supplementary evidence in risk stratification. This cross-sectional study aimed to assess and compare ECG findings of massive and submassive PE versus segmental PE. This cross-sectional study included 250 hospitalized patients with a confirmed diagnosis of acute PE from 2015 to 2020 in Southern Iran. Demographic variables, clinical data, troponin levels, on-admission ECG findings, echocardiography findings, and ECG findings 24 h after receiving anticoagulants or thrombolytics were extracted. Patients diagnosed with submassive or massive PE exhibited significantly higher rates of right axis deviation (p = .010), abnormal ST segment (p < .0001), S1Q3T3 pattern (p < .0001), inverted T wave in leads V1-V3 (p < .0001), inverted T wave in leads V4-V6 (p < .0001), and inverted T wave in leads V1-V6 (p < .0001). In a multivariable model, inverted T wave in leads V1-V3, inverted T wave in leads V4-V6, pulse rate, and positive troponin test were the statistically independent variables for predicting submassive or massive PE. Furthermore, inverted T wave in leads V1-V3 (sensitivity: 85%, specificity: 95%, accuracy: 93%, AUC: 0.902) and troponin levels (sensitivity: 72%, specificity: 86%, accuracy: 83%, AUC: 0.792) demonstrated the best diagnostic test performance for discriminating submassive or massive PE from segmental PE. In addition to clinical rules, ECG can serve as an ancillary tool for assessing more invasive testing and earlier aggressive treatments among patients with PE, as it can provide valuable information for the diagnosis and risk stratification of submassive or massive PE.