Classification of Failures in the Perception of Conversational Agents (CAs) and their Implications on Patient Safety

The use of Conversational agents (CAs) in healthcare is an emerging field. These CAs seem to be effective in accomplishing administrative tasks, e.g. providing locations of care facilities and scheduling appointments. Modern CAs use machine learning (ML) to recognize, understand and generate a response. Given the criticality of many healthcare settings, ML and other component errors may result in CA failures and may cause adverse effects on patients. Therefore, in-depth assurance is required before the deployment of ML in critical clinical applications, e.g. management of medication dose or medical diagnosis. CA safety issues could arise due to diverse causes, e.g. related to user interactions, environmental factors and ML errors. In this paper, we classify failures of perception (recognition and understanding) of CAs and their sources. We also present a case study of a CA used for calculating insulin dose for gestational diabetes mellitus (GDM) patients. We then correlate identified perception failures of CAs to potential scenarios that might compromise patient safety

Prevalence of Diabetic Retinopathy and Correlation with HbA1c in Patients Admitted in Khyber Teaching Hospital Peshawar

Objective: To determine the prevalence of diabetic retinopathy in patients admitted in Khyber Teaching Hospital Peshawar and to correlate different stages of diabetic retinopathy with HbA1C levels. Methodology: This cross sectional study was conducted at Department of Ophthalmology, Khyber Teaching Hospital, MTI, Peshawar from December 2019 to May 2020. All patients over the age of 15 years who were diagnosed with diabetes mellitus were included in the study while patients with cataract or retinopathy due to other pathologies were excluded. All diabetic patients were admitted through outpatient department. In the ward their blood pressures were recorded and HbA1c levels were also measured. Visual acuity (VA) was checked. Screening for diabetic retinopathy was done by a consultant ophthalmologist by Optos Ultrawide Field Imaging of retina and Optical Coherence Tomography (OCT) of macula to establish stages of diabetic retinopathy and presence of diabetic macular edema respectively. Results: A total of 103 diabetic patients were included. Their retina was photographed, viewed and analyzed. Diabetic retinopathy, irrespective of the type, was found in 69 patients with a prevalence of 66.9%. Patients with lower ranges of HbA1c (below 6%) showed no evidence of DR. The clustering of majority of patients with diabetic retinopathy with HbA1c levels of 8 to 12 %, showed a significant relationship between high blood sugar levels and severity. Conclusion: In our study the higher frequency of retinopathy is alarming by considering it one of the leading causes of blindness in working class. It is highly recommended that routine ophthalmologic examination may be carried out along with optimal diabetic control

Microwave-assisted green synthesis and antimicrobial activity of silver nanoparticles derived from a supercritical carbon dioxide extract of the fresh aerial parts of Phyllanthus niruri L

Purpose: To synthesize and evaluate the antimicrobial activity of silver nanoparticles (AgNPs) derived from a supercritical carbon dioxide extract of the fresh aerial parts of Phyllanthus niruri. Methods: The synthesis of AgNPs of a P. niruri extract was carried out in a microwave oven. The extraction was carried out using a supercritical fluid extractor. The AgNPs were characterized by the Ultraviolet-visible (UV-vis) spectral analysis, Dynamic Light Scattering (DLS) zetasizer analysis, Transmission electron microscopy (TEM), X-ray diffraction (XRD) analysis and Fourier transform infrared (FT-IR) spectroscopy. The antimicrobial assays of AgNPs were carried out against different bacterial and fungal strains. Results: Results of various analytical techniques confirmed the synthesis of AgNPs of a P. niruri extract. The UV–vis spectroscopy showed an intense silver surface plasmon resonance band at 415 NM. The AgNPs had a mean size of 110 nm in the Zetasizer analysis. TEM images illustrated spherical AgNPs having a mean particle size of 110 nm. The X-ray diffractograms showed peaks at 38.17°, 44.28°, and 64.52°. The average crystallite size of Ag-NPs was found to be 110 nm. FT-IR spectra confirmed the stability of the AgNPs. The AgNPs demonstrated good antimicrobial effects against several tested pathogenic microbes. Conclusion: An efficiently synthesized AgNPs of P. niruri (SC-CO2) extract has been prepared by a simple, eco-friendly, cost-effective, rapid green chemistry methodology. The AgNPs of P. niruri extract possesses significant antimicrobial properties against the tested bacterial and fungal strains. Keywords: Nanoparticles, Phyllanthus niruri, Supercritical fluid extraction, Microwave, Antimicrobial activit

Robust Intent Classification using Bayesian LSTM for Clinical Conversational Agents (CAs)

Conversational Agents (CAs) are software programs that replicate hu-man conversations using machine learning (ML) and natural language processing (NLP). CAs are currently being utilised for diverse clinical applications such as symptom checking, health monitoring, medical triage and diagnosis. Intent clas-sification (IC) is an essential task of understanding user utterance in CAs which makes use of modern deep learning (DL) methods. Because of the inherent model uncertainty associated with those methods, accuracy alone cannot be relied upon in clinical applications where certain errors may compromise patient safety. In this work, we employ Bayesian Long Short-Term Memory Networks (LSTMs) to calculate model uncertainty for IC, with a specific emphasis on symptom checker CAs. This method provides a certainty measure with IC prediction that can be utilised in assuring safe response from CAs. We evaluated our method on in-distribution (ID) and out-of-distribution (OOD) data and found mean uncer-tainty to be much higher for OOD data. These findings suggest that our method is robust to OOD utterances and can detect non-understanding errors in CAs

An integrative comparative study between ultrasound-guided regional anesthesia versus parenteral opioids alone for analgesia in emergency department patients with hip fractures: A systematic review and meta-analysis

BackgroundEmergency physicians play a major role in managing patients with hip fractures. The most commonly used pain management option is parenteral opioids. However, parenteral opioids are subjected to several adverse effects. New pain management techniques such as regional anesthesia are used as alternatives to parenteral opioids. Anatomical landmarks were used to administer regional anesthesia; however, ultrasound guidance has shown promising results with regional anesthesia. Objectiveof the Review: The present study compares the efficacy of ultrasound-guided regional anesthesia (USGRA) to parenteral opioids in analgesia of hip fractures patients. MethodsA literature search for original and relevant articles carried out through six electronic databases, yielded 710 articles which were then assessed using the eligibility criteria resulting in 8 studies eligible for inclusion. ResultsA Meta-analysis of the seven studies showed that ultrasound-guided femoral nerve block was more effective than parenteral opioids in relieving pain. Similarly, meta-analysis of data from two studies shows that US-guided FICB significantly reduced pain scores than parenteral opioids. A subgroup analysis of adverse events showed no significant difference in nausea/vomiting and respiratory complications. However, a subgroup analysis on hypotension showed that the incidence of hypotension was significantly lower in USGRA than parenteral opioids. The present study also revealed that patients in the USGRA group required less frequent rescue analgesia than the patients in the parenteral opioids group. ConclusionResults of the present study show that USGRA is superior to parenteral opioids in reducing pain and the need for rescue analgesia in patients with hip fractures.The publication of this article is funded by the Qatar National Library

Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial

SummaryBackground Azithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatoryactions. We aimed to evaluate the safety and efficacy of azithromycin in patients admitted to hospital with COVID-19.Methods In this randomised, controlled, open-label, adaptive platform trial (Randomised Evaluation of COVID-19Therapy [RECOVERY]), several possible treatments were compared with usual care in patients admitted to hospitalwith COVID-19 in the UK. The trial is underway at 176 hospitals in the UK. Eligible and consenting patients wererandomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once perday by mouth or intravenously for 10 days or until discharge (or allocation to one of the other RECOVERY treatmentgroups). Patients were assigned via web-based simple (unstratified) randomisation with allocation concealment andwere twice as likely to be randomly assigned to usual care than to any of the active treatment groups. Participants andlocal study staff were not masked to the allocated treatment, but all others involved in the trial were masked to theoutcome data during the trial. The primary outcome was 28-day all-cause mortality, assessed in the intention-to-treatpopulation. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936.Findings Between April 7 and Nov 27, 2020, of 16 442 patients enrolled in the RECOVERY trial, 9433 (57%) wereeligible and 7763 were included in the assessment of azithromycin. The mean age of these study participants was65·3 years (SD 15·7) and approximately a third were women (2944 [38%] of 7763). 2582 patients were randomlyallocated to receive azithromycin and 5181 patients were randomly allocated to usual care alone. Overall,561 (22%) patients allocated to azithromycin and 1162 (22%) patients allocated to usual care died within 28 days(rate ratio 0·97, 95% CI 0·87–1·07; p=0·50). No significant difference was seen in duration of hospital stay (median10 days [IQR 5 to >28] vs 11 days [5 to >28]) or the proportion of patients discharged from hospital alive within 28 days(rate ratio 1·04, 95% CI 0·98–1·10; p=0·19). Among those not on invasive mechanical ventilation at baseline, nosignificant difference was seen in the proportion meeting the composite endpoint of invasive mechanical ventilationor death (risk ratio 0·95, 95% CI 0·87–1·03; p=0·24).Interpretation In patients admitted to hospital with COVID-19, azithromycin did not improve survival or otherprespecified clinical outcomes. Azithromycin use in patients admitted to hospital with COVID-19 should be restrictedto patients in whom there is a clear antimicrobial indication

Classification of Failures in the Perception of Conversational Agents (CAs) and Their Implications on Patient Safety

The use of Conversational agents (CAs) in healthcare is an emerging field. These CAs seem to be effective in accomplishing administrative tasks, e.g. providing locations of care facilities and scheduling appointments. Modern CAs use machine learning (ML) to recognize, understand and generate a response. Given the criticality of many healthcare settings, ML and other component errors may result in CA failures and may cause adverse effects on patients. Therefore, in-depth assurance is required before the deployment of ML in critical clinical applications, e.g. management of medication dose or medical diagnosis. CA safety issues could arise due to diverse causes, e.g. related to user interactions, environmental factors and ML errors. In this paper, we classify failures of perception (recognition and understanding) of CAs and their sources. We also present a case study of a CA used for calculating insulin dose for gestational diabetes mellitus (GDM) patients. We then correlate identified perception failures of CAs to potential scenarios that might compromise patient safety

Pattern of Shareholding and Leverage: Context of the Energy Sector of Pakistan

This paper attempts to empirically test the impact of shareholding pattern using ownership concentration and managerial ownership as proxies of pattern of shareholding, on capital structure of energy sector firms listed at Pakistan Stock Exchange (PSX) during period 2008 – 2018. We use ordinary least square (OLS) and system generalized method of moments (SGMM) to estimate our results to ensure robustness and to control for the potential endogeneity bias. Our results suggest that ownership concentration leads to higher debt ratio, whereas, managerial ownership leads to lower debt ratio. Our findings can be helpful for the policymakers to devise policies to separate the ownership and control from management to protect the rights of the minority shareholders.&nbsp

Clinical assessment and risk stratification for prehospital use of methoxyflurane versus standard analgesia in adult patients with trauma pain

Oligoanalgesia, the undertreatment of trauma-related pain using standard analgesics in prehospital and emergency departments, has been extensively documented as one of the major challenges affecting the effective treatment of trauma-related pain. When administered in low doses, methoxyflurane has been highlighted by numerous medical works of literature to provide an effective, nonopioid, nonnarcotic treatment alternative to standard analgesics for prehospital and emergency department use. Low-dose methoxyflurane has been associated with fast-pain relief in adult patients manifesting moderate-to-severe pain symptoms. This systematic review and meta-analysis aimed to assess the clinical implication of low-dose methoxyflurane use in prehospital and emergency departments in adult patients with moderate-to-severe trauma-related pain. Moreover, the review aimed at assessing the risk stratification associated with using low-dose methoxyflurane in prehospital and emergency departments. The systematic review and meta-analysis performed a comprehensive search for pertinent literature assessing the implications and risks of using low-dose methoxyflurane in adult patients exhibiting moderate-to-severe trauma-related pain in prehospital settings. A comparison between the use of low-dose methoxyflurane and standard-of-care analgesics, placebo, in prehospital settings was reported in four clinically conducted randomized controlled trials (RCTs). These RCTs included the STOP! trial, InMEDIATE, MEDIATA, and the PenASAP trials. A meta-analysis comparing the time taken to achieve first pain relief on initial treatment of patients with moderate-to-severe trauma-related pain favored the use of low-dose methoxyflurane to the standard-of-care analgesics (mean difference = -6.63, 95% confidence interval = -7.37, -5.09) on time taken to establish effective pain relief. Low-dose methoxyflurane has been associated with superior and faster pain relief in prehospital and emergency departments in adult patients exhibiting moderate-to-severe trauma-related pain compared to other standard analgesics