A Comparison of 5 Algorithmic Methods and Machine Learning Pattern Recognition for Artifact Detection in Electronic Records of 5 Different Vital Signs: A Retrospective Analysis.

BACKGROUND: Research on electronic health record physiological data is common, invariably including artifacts. Traditionally, these artifacts have been handled using simple filter techniques. The authors hypothesized different artifact detection algorithms, including machine learning, may be necessary to provide optimal performance for various vital signs and clinical contexts. MATERIALS AND METHODS: In a retrospective single center study, intraoperative OR and ICU electronic health record datasets including heart rate, oxygen saturation, blood pressure, temperature, and capnometry were included. All records were screened for artifacts by at least two human experts. Classical artifact detection methods (cutoff, multiples of standard deviation (z-value), interquartile range, and local outlier factor) and a supervised learning model implementing long short-term memory neural networks were tested for each vital sign against the human expert reference dataset. For each artifact detection algorithm, sensitivity and specificity were calculated. RESULTS: A total of 106 (53 operating room and 53 ICU) patients were randomly selected, resulting in 392,808 data points. Human experts annotated 5,167 (1.3%) data points as artifacts. The artifact detection algorithms demonstrated large variations in performance. The specificity was above 90% for all detection methods and all vital signs. The neural network showed significantly higher sensitivities than the classic methods for: heart rate (ICU: 33.6%, 95% CI: 33.1-44.6), systolic invasive blood pressure (both in the OR (62.2%, 95% CI: 57.5-71.9) and ICU (60.7%, 95% CI: 57.3-71.8), and temperature in the OR (76.1%, 95% CI: 63.6-89.7). The confidence intervals for specificity overlapped for all methods. Generally, sensitivity was low, with only the z-value for oxygen saturation in the operating room reaching 88.9%. All other sensitivities were less than 80%. CONCLUSION: No single artifact detection method consistently performed well across different vital signs and clinical settings. Neural networks may be a promising artifact detection method for specific vital signs.

Ultrasound evaluation of gastric emptying time of standardized high-calorie liquid meals in healthy adults: A double-blind cross-over randomized study.

BACKGROUND AND AIMS: Commercially available high-calorie drinks containing fat and protein can be used as dietary supplements in surgical patients. According to preoperative fasting guidelines, high-calorie drinks are non-clear fluids and should not be consumed 6 h before elective procedures. The aim of this study was to evaluate the gastric emptying time of commercially available high-calorie drink formulations in healthy adults using gastric ultrasound. METHODS: 25 healthy adult volunteers were included in this double-blind, cross-over prospective study. On three study sessions, fasted volunteers ingested one of the three study products: a solution of 75 g of glucose in 200 ml of water, a fat-free liquid meal, and a nutritionally complete liquid meal with equal volume and energy content. Gastric ultrasound examinations were performed to evaluate the gastric contents qualitatively and the volume of the gastric contents was calculated from the cross-sectional area of the gastric antrum measured in right lateral position by using a validated model. Repeated gastric ultrasounds were performed at baseline and half-hourly after ingesting the products in supine and right lateral position until the criteria for an empty stomach were met. RESULTS: The glucose solution and the standard fat-free high-calorie drink with the same caloric content had a median gastric emptying time of 150 min. The nutritionally complete liquid meal had a median gastric emptying time of 180 min. Gastric emptying was complete in all participants before 6 h had elapsed since ingesting the study products. CONCLUSIONS: High calorie liquid meals have a gastric emptying time longer than the recommended fasting time for clear fluids, but shorter than the recommended fasting time for solids in healthy adults.

Accuracy of a Dual-Sensor Heat-Flux (DHF) Non-Invasive Core Temperature Sensor in Pediatric Patients Undergoing Surgery.

Accurate temperature measurement is crucial for the perioperative management of pediatric patients, and non-invasive thermometry is necessary when invasive methods are infeasible. A prospective observational study was conducted on 57 patients undergoing elective surgery. Temperatures were measured using a dual-sensor heat-flux (DHF) thermometer (Tcore™) and a rectal temperature probe (TRec), and the agreement between the two measurements was assessed. The DHF measurements showed a bias of +0.413 °C compared with those of the TRec. The limits of agreement were broader than the pre-defined ±0.5 °C range (-0.741 °C and +1.567 °C). Although the DHF sensors tended to overestimate the core temperature compared to the rectal measurements, an error grid analysis demonstrated that 95.81% of the DHF measurements would not have led to a wrong clinical decision, e.g., warming or cooling when not necessary. In conclusion, the low number of measurements that would have led to incorrect decisions suggests that the DHF sensor can be considered an option for continuous temperature measurement when more invasive methods are infeasible.

The promise of digital healthcare technologies.

Digital health technologies have been in use for many years in a wide spectrum of healthcare scenarios. This narrative review outlines the current use and the future strategies and significance of digital health technologies in modern healthcare applications. It covers the current state of the scientific field (delineating major strengths, limitations, and applications) and envisions the future impact of relevant emerging key technologies. Furthermore, we attempt to provide recommendations for innovative approaches that would accelerate and benefit the research, translation and utilization of digital health technologies.

The influence of explainable vs non-explainable clinical decision support systems on rapid triage decisions: a mixed methods study.

BACKGROUND: During the COVID-19 pandemic, a variety of clinical decision support systems (CDSS) were developed to aid patient triage. However, research focusing on the interaction between decision support systems and human experts is lacking. METHODS: Thirty-two physicians were recruited to rate the survival probability of 59 critically ill patients by means of chart review. Subsequently, one of two artificial intelligence systems advised the physician of a computed survival probability. However, only one of these systems explained the reasons behind its decision-making. In the third step, physicians reviewed the chart once again to determine the final survival probability rating. We hypothesized that an explaining system would exhibit a higher impact on the physicians' second rating (i.e., higher weight-on-advice). RESULTS: The survival probability rating given by the physician after receiving advice from the clinical decision support system was a median of 4 percentage points closer to the advice than the initial rating. Weight-on-advice was not significantly different (p = 0.115) between the two systems (with vs without explanation for its decision). Additionally, weight-on-advice showed no difference according to time of day or between board-qualified and not yet board-qualified physicians. Self-reported post-experiment overall trust was awarded a median of 4 out of 10 points. When asked after the conclusion of the experiment, overall trust was 5.5/10 (non-explaining median 4 (IQR 3.5-5.5), explaining median 7 (IQR 5.5-7.5), p = 0.007). CONCLUSIONS: Although overall trust in the models was low, the median (IQR) weight-on-advice was high (0.33 (0.0-0.56)) and in line with published literature on expert advice. In contrast to the hypothesis, weight-on-advice was comparable between the explaining and non-explaining systems. In 30% of cases, weight-on-advice was 0, meaning the physician did not change their rating. The median of the remaining weight-on-advice values was 50%, suggesting that physicians either dismissed the recommendation or employed a "meeting halfway" approach. Newer technologies, such as clinical reasoning systems, may be able to augment the decision process rather than simply presenting unexplained bias.

Accuracy of non-invasive sensors measuring core body temperature in cardiac surgery ICU patients - results from a monocentric prospective observational study.

PURPOSE: Temperature monitoring in the perioperative setting often represents a compromise between accuracy, invasiveness of probe placement, and patient comfort. Transcutaneous sensors using the Zero-Heat-Flux (ZHF) and Double-Sensor (DS) technology have been developed and evaluated in a variety of clinical settings. The present study is the first to compare the performance of both sensors simultaneously with temperature measured by a Swan-Ganz catheter (PAC) in patients admitted to the intensive care unit (ICU) after cardiac surgery. METHODS: In this monocentric prospective observational study patients were postoperatively transferred to the ICU and both sensors were placed on the patients' foreheads. Core body temperature measured by intraoperatively placed PAC served as gold standard. Measurements were recorded at 5-minute intervals and up to 40 data sets per patient were recorded. Bland and Altman's method for repeated measurements was used to analyse agreement. Subgroup analyses for gender, body-mass-index, core temperature, airway status and different time intervals were performed. Lin's concordance correlation coefficient (LCCC) was calculated, as well as sensitivity and specificity for detecting hyperthermia (≥ 38 °C) and hypothermia (< 36 °C). RESULTS: Over a period of six month, we collected 1600 sets of DS, ZHF, and PAC measurements, from a total of 40 patients. Bland-Altman analysis revealed a mean bias of -0.82 ± 1.27 °C (average ± 95% Limits-of-Agreement (LoA)) and - 0.54 ± 1.14 °C for DS and ZHF, respectively. The LCCC was 0.5 (DS) and 0.63 (ZHF). Mean bias was significantly higher in hyperthermic and hypothermic patients. Sensitivity and specificity were 0.12 / 0.99 (DS) and 0.35 / 1.0 (ZHF) for hyperthermia and 0.95 / 0.72 (DS) and 1.0 / 0.85 (ZHF) for hypothermia. CONCLUSION: Core temperature was generally underestimated by the non-invasive approaches. In our study, ZHF outperformed DS. In terms of agreement, results for both sensors were outside the range that is considered clinically acceptable. Nevertheless, both sensors might be adequate to detect postoperative hypothermia reliably when more invasive methods are not available or appropriate. TRIAL REGISTRATION: German Register of Clinical Trials (DRKS-ID: DRKS00027003), retrospectively registered 10/28/2021.

Predicting Intraoperative Hypothermia Burden during Non-Cardiac Surgery: A Retrospective Study Comparing Regression to Six Machine Learning Algorithms.

BACKGROUND: Inadvertent intraoperative hypothermia is a common complication that affects patient comfort and morbidity. As the development of hypothermia is a complex phenomenon, predicting it using machine learning (ML) algorithms may be superior to logistic regression. METHODS: We performed a single-center retrospective study and assembled a feature set comprised of 71 variables. The primary outcome was hypothermia burden, defined as the area under the intraoperative temperature curve below 37 °C over time. We built seven prediction models (logistic regression, extreme gradient boosting (XGBoost), random forest (RF), multi-layer perceptron neural network (MLP), linear discriminant analysis (LDA), k-nearest neighbor (KNN), and Gaussian naïve Bayes (GNB)) to predict whether patients would not develop hypothermia or would develop mild, moderate, or severe hypothermia. For each model, we assessed discrimination (F1 score, area under the receiver operating curve, precision, recall) and calibration (calibration-in-the-large, calibration intercept, calibration slope). RESULTS: We included data from 87,116 anesthesia cases. Predicting the hypothermia burden group using logistic regression yielded a weighted F1 score of 0.397. Ranked from highest to lowest weighted F1 score, the ML algorithms performed as follows: XGBoost (0.44), RF (0.418), LDA (0.406), LDA (0.4), KNN (0.362), and GNB (0.32). CONCLUSIONS: ML is suitable for predicting intraoperative hypothermia and could be applied in clinical practice.

Patent landscape review of non-invasive medical sensors for continuous monitoring of blood pressure and their validation in critical care practice.

Objectives: Continuous non-invasive monitoring of blood pressure is one of the main factors in ensuring the safety of the patient's condition in anesthesiology, intensive care, surgery, and other areas of medicine. The purpose of this work was to analyze the current patent situation and identify directions and trends in the application of non-invasive medical sensors for continuous blood pressure monitoring, with a focus on clinical experience in critical care and validation thereof. Materials and methods: The research results reflect data collected up to September 30, 2022. Patent databases, Google Scholar, the Lens database, Pubmed, Scopus databases were used to search for patent and clinical information. Results: An analysis of the patent landscape indicates a significant increase in interest in the development of non-invasive devices for continuous blood pressure monitoring and their implementation in medical practice, especially in the last 10 years. The key players in the intellectual property market are the following companies: Cnsystems Medizintechnik; Sotera Wireless INC; Tensys Medical INC; Healthstats Int Pte LTD; Edwards Lifesciences Corp, among others. Systematization of data from validation and clinical studies in critical care practice on patients with various pathological conditions and ages, including children and newborns, revealed that a number of non-invasive medical sensor technologies are quite accurate and comparable to the "gold standard" continuous invasive blood pressure monitoring. They are approved by the FDA for medical applications and certified according to ISO 81060-2, ISO 81060-3, and ISO/TS 81060-5. Unregistered and uncertified medical sensors require further clinical trials. Conclusion: Non-invasive medical sensors for continuous blood pressure monitoring do not replace, but complement, existing methods of regular blood pressure measurement, and it is expected to see more of these technologies broadly implemented in the practice in the near future.

Are dental x-rays safe? Content analysis of English and Chinese YouTube videos.

Objective: This study provided a content analysis of English and Chinese YouTube videos related to dental radiation safety. Method: The search string, entered in English and Chinese respectively, was: (dental x-ray safe). The searches were performed and exported with Apify YouTube scraper. By screening the resultant videos and their related videos (as recommended by YouTube), a total of 89 videos were screened. Finally, 45 videos (36 English and nine Chinese) were included and analyzed. The specific information regarding dental radiation was evaluated. The Patient Education Material Assessment Tool for Audiovisual Materials was used to assess understandability and actionability. Results: There was no significant difference between the English and Chinese videos in terms of view count, like count, comment count, and video duration. Half of the videos explicitly reassured the audience that dental x-rays are safe. Two of the English videos specifically stated that dental x-rays do not cause cancers. Numerous analogies were made in regard to radiation dose, such as equivalence to taking a flight or eating some bananas. About 41.7% of the English videos and 33.3% of the Chinese videos mentioned that patients could be further protected from scatter radiation by wearing a lead apron and thyroid collar. Videos had a good understandability score (91.3) but a poor actionability score (0). Conclusions: Some of the analogies and the claimed radiation dose were questionable. One Chinese video even wrongly stated that dental x-rays are nonionizing radiation. The videos generally did not mention their information sources or the underlying radiation protection principles.

Public interest in different types of masks and its relationship with pandemic and policy measures during the COVID-19 pandemic: a study using Google Trends data.

Google Trends data have been used to investigate various themes on online information seeking. It was unclear if the population from different parts of the world shared the same amount of attention to different mask types during the COVID-19 pandemic. This study aimed to reveal which types of masks were frequently searched by the public in different countries, and evaluated if public attention to masks could be related to mandatory policy, stringency of the policy, and transmission rate of COVID-19. By referring to an open dataset hosted at the online database Our World in Data, the 10 countries with the highest total number of COVID-19 cases as of 9th of February 2022 were identified. For each of these countries, the weekly new cases per million population, reproduction rate (of COVID-19), stringency index, and face covering policy score were computed from the raw daily data. Google Trends were queried to extract the relative search volume (RSV) for different types of masks from each of these countries. Results found that Google searches for N95 masks were predominant in India, whereas surgical masks were predominant in Russia, FFP2 masks were predominant in Spain, and cloth masks were predominant in both France and United Kingdom. The United States, Brazil, Germany, and Turkey had two predominant types of mask. The online searching behavior for masks markedly varied across countries. For most of the surveyed countries, the online searching for masks peaked during the first wave of COVID-19 pandemic before the government implemented mandatory mask wearing. The search for masks positively correlated with the government response stringency index but not with the COVID-19 reproduction rate or the new cases per million.

Impact of #PsychTwitter in promoting global psychiatry: A hashtag analysis study.

Introduction: Multiple studies have shown how valuable Twitter hashtags can be for promoting content related to different themes in the online community. This arena has grown into a rich data source for public health observation and understanding key trends in healthcare on a global scale. In the field of mental health in particular, it would be of benefit to understand and report the key stakeholders' (individual mental health professionals, academic organizations and their countries) trends and patterns of psychiatric knowledge and information dissemination using #PsychTwitter. Objective: In this study, we aim to evaluate the achieved outreach of psychiatry-related tweets using the hashtag #PsychTwitter. Methods: We utilized the Symplur Signals research analytics tool to characterize tweets containing #PsychTwitter from the 20th of August, 2019, to the 20th of August, 2022. Results: The #PsychTwitter movement resulted in 125,297 tweets that were shared by 40,058 Twitter users and generated a total of 492,565,230 impressions (views). The three largest identified groups of contributors were Doctors (13.8% of all tweets), Org. Advocacy (6.2% of all tweets), and Researcher/Academic (4% of all tweets) stakeholders. The top influential accounts consisted of 55 psychiatrists and 16 institutional or organizational accounts. The top 5 countries from where most of the tweets containing #PsychTwitter were shared include the United States (54.3% of all users), the United Kingdom (10.4% of all users), Canada (4.9% of all users), India (2% of all users), and Australia (1.8% of all users). Conclusion: This is the first of its kind study featuring the influence and usage of #PsychTwitter and covering its global impact in the field of psychiatry using the Twitter platform. Our results indicate that Twitter represents a broadly used platform for mental health-related discussions.

Intraoperative Hypotension Is Associated with Postoperative Nausea and Vomiting in the PACU: A Retrospective Database Analysis.

Multiple risk factors for postoperative nausea and vomiting (PONV)-a very distressing and outcome-related complication-have been identified, including female sex, absence of a history of smoking, history of PONV, and postoperative opioid use. Evidence of association of intraoperative hypotension with PONV is contradictory. A retrospective analysis of the perioperative documentation of 38,577 surgeries was conducted. The associations between different characterizations of intraoperative hypotension and PONV in the postoperative care unit (PACU) were investigated. First, the relationship between different characterizations of intraoperative hypotension with regard to PONV in the PACU was investigated. Secondly, the performance of the optimal characterization was assessed in an independent dataset derived via random split. The vast majority of characterizations showed an association of hypotension with the incidence of PONV in the PACU. In a multivariable regression, time with a MAP under 50 mmHg showed the strongest association with PONV in terms of the cross-validated Brier score. The adjusted odds for PONV in the PACU were estimated to be 1.34 times higher (95% CI: 1.33-1.35) when a MAP was under 50 mmHg for at least 1.8 min than when a MAP remained above 50 mmHg. The finding indicates that intraoperative hypotension may yet be another risk factor for PONV and therefore emphasizes the importance of intraoperative blood pressure management not only in patients at risk for cardiovascular complications but also in young and healthy patients at risk of PONV.

Bibliometric analysis and evidence of clinical efficacy and safety of digital pills.

Objectives: Digital pills are new technologies that aim to improve healthcare by increasing medication adherence. The aim of the work was a bibliometric analysis of clinical studies of digital pills and an assessment of the level of evidence of their effectiveness, safety, and prospects for the future. Materials and Methods: The studies were conducted using online databases such as ClinicalTrials.gov, Dimensions, and Web of Science for the period January 2012 to July 2022. The VOSviewer tool for building and visualizing bibliometric networks was used. Results: Bibliometric analysis of the scientific literature revealed that over the past 10 years, the number of publications about digital pills has noticeably increased, which indicates the increasing importance of this field of knowledge. The leading positions in this area are occupied by scientists from the United States, the United Kingdom, and India. Sources of financial support for authors of publications in the field of digital pills are funds from leading developer companies, budget allocations, and funds from non-commercial organizations. Public-private partnerships are an important path to develop and implement digital pills. The four main clusters of digital pill studies were highlighted and visualized: efficacy and safety analysis for serious mental disorders; treatment and costs of tuberculosis therapy; features of the treatment of diabetes, cardiovascular diseases, and AIDS; and usage monitoring. Available publications demonstrate the efficacy potential and safety of digital pills. Nevertheless, the effects of digital pills have not yet been fully studied. Conclusion: Priority areas for future research are further randomized controlled clinical trials and meta-analyses, which are necessary for a high level (I level) of evidence for therapeutic applications of digital pills, as well as pharmacoeconomic studies.

Development of a Reinforcement Learning Algorithm to Optimize Corticosteroid Therapy in Critically Ill Patients with Sepsis.

BACKGROUND: The optimal indication, dose, and timing of corticosteroids in sepsis is controversial. Here, we used reinforcement learning to derive the optimal steroid policy in septic patients based on data on 3051 ICU admissions from the AmsterdamUMCdb intensive care database. METHODS: We identified septic patients according to the 2016 consensus definition. An actor-critic RL algorithm using ICU mortality as a reward signal was developed to determine the optimal treatment policy from time-series data on 277 clinical parameters. We performed off-policy evaluation and testing in independent subsets to assess the algorithm's performance. RESULTS: Agreement between the RL agent's policy and the actual documented treatment reached 59%. Our RL agent's treatment policy was more restrictive compared to the actual clinician behavior: our algorithm suggested withholding corticosteroids in 62% of the patient states, versus 52% according to the physicians' policy. The 95% lower bound of the expected reward was higher for the RL agent than clinicians' historical decisions. ICU mortality after concordant action in the testing dataset was lower both when corticosteroids had been withheld and when corticosteroids had been prescribed by the virtual agent. The most relevant variables were vital parameters and laboratory values, such as blood pressure, heart rate, leucocyte count, and glycemia. CONCLUSIONS: Individualized use of corticosteroids in sepsis may result in a mortality benefit, but optimal treatment policy may be more restrictive than the routine clinical practice. Whilst external validation is needed, our study motivates a 'precision-medicine' approach to future prospective controlled trials and practice.

Intravenous diclofenac and orphenadrine for the treatment of postoperative pain after remifentanil-based anesthesia : A double-blinded, randomized, placebo-controlled study.

BACKGROUND: Postoperative intravenous diclofenac reduces patient opioid demand and is commonly used in surgical units. Orphenadrine is mainly used in combination with diclofenac for musculoskeletal injuries and postoperative pain control. The objective of this study was to compare the analgesic efficacy of diclofenac-orphenadrine, diclofenac alone and saline. METHODS: We performed a double-blind, randomized, placebo-controlled, parallel-group, single-center clinical study investigating the opioid-sparing effect of a combination of diclofenac and orphenadrine versus diclofenac alone versus isotonic saline solution. Initially 72 patients were included and received total intravenous anesthesia during cruciate ligament surgery. All patients were postoperatively treated with a patient-controlled analgesia (PCA) device containing hydromorphone. Pharmacological safety was assessed by laboratory parameters, vital signs, and delirium detection scores. RESULTS: There was no significant difference between the groups in cumulative dose of PCA analgesics required after 24 h postsurgery, with 5.90 mg (SD ± 2.90 mg) in the placebo group, 5.73 mg (SD ± 4.75 mg) in the diclofenac group, and 4.13 mg (SD ± 2.57 mg) in the diclofenac-orphenadrine group. Furthermore, there was no significant difference between the groups in cumulative dose of PCA analgesics required 2 h postsurgery (n = 65). Mean dose of hydromorphone required after 2 h was 1.54 mg (SD ± 0.57 mg) in the placebo group, 1.56 mg (SD ± 1.19 mg) in the diclofenac-only group, and 1.37 mg (SD ± 0.78 mg) in the diclofenac-orphenadrine group. However, when comparing the diclofenac-orphenadrine group and the diclofenac group combined to placebo there was a significant reduction in PCA usage in the first 24 h postsurgery. In total, there were 25 adverse events reported, none of which were rated as severe. CONCLUSION: Orphenadrine-diclofenac failed to significantly reduce postoperative opioid requirements. However, in an exploratory post hoc analysis the diclofenac-orphenadrine and the diclofenac group combined versus placebo showed a tendency to reduce opioid demand in postoperative pain control. Further research is required to determine the value of orphenadrine as an adjuvant in a multimodal approach for postoperative pain management.

External validation of the ProVent score for prognostication of 1-year mortality of critically ill patients with prolonged mechanical ventilation: a single-centre, retrospective observational study in Austria.

OBJECTIVES: In critically ill patients requiring mechanical ventilation for at least 21 days, 1-year mortality can be estimated using the ProVent score, calculated from four variables (age, platelet count, vasopressor use and renal replacement therapy). We aimed to externally validate discrimination and calibration of the ProVent score and, if necessary, to update its underlying regression model. DESIGN: Retrospective, observational, single-centre study. SETTING: 11 intensive care units at one tertiary academic hospital. PATIENTS: 780 critically ill adult patients receiving invasive mechanical ventilation for at least 21 days. PRIMARY OUTCOME MEASURE: 1-year mortality after intensive care unit discharge. RESULTS: 380 patients (49%) had died after 1 year. One-year mortality for ProVent scores from 0 to 5 were: 15%, 27%, 57%, 66%, 72% and 76%. Area under the receiver operating characteristic curve of the ProVent probability model was 0.76 (95% CI 0.72 to 0.79), calibration intercept was -0.43 (95% CI -0.59 to -0.27) and calibration slope was 0.76 (95% CI 0.62 to 0.89). Model recalibration and extension by inclusion of three additional predictors (total bilirubin concentration, enteral nutrition and surgical status) improved model discrimination and calibration. Decision curve analysis demonstrated that the original ProVent model had negative net benefit, which was avoided with the extended ProVent model. CONCLUSIONS: The ProVent probability model had adequate discrimination but was miscalibrated in our patient cohort and, as such, could potentially be harmful. Use of the extended ProVent score developed by us could possibly alleviate this concern.

Digital Pills with Ingestible Sensors: Patent Landscape Analysis.

The modern healthcare system is directly related to the development of digital health tools and solutions. Pills with digital sensors represent a highly innovative class of new pharmaceuticals. The aim of this work was to analyze the patent landscape and to systematize the main trends in patent protection of digital pills with ingestible sensors worldwide; accordingly, to identify the patenting leaders as well as the main prevailing areas of therapy for patent protection, and the future perspectives in the field. In July 2022, a search was conducted using Internet databases, such as the EPO, USPTO, FDA and the Lens database. The patent landscape analysis shows an increase in the number of patents related to digital pills with ingestible sensors for mobile clinical monitoring, smart drug delivery, and endoscopy diagnostics. The leaders in the number of patents issued are the United States, the European Patent Office, Canada, Australia, and China. The following main areas of patenting digital pills with ingestible sensors were identified: treatment in the field of mental health; HIV/AIDS; pain control; cardiovascular diseases; diabetes; gastroenterology (including hepatitis C); oncology; tuberculosis; and transplantology. The development of scientific and practical approaches towards the implementation of effective and safe digital pills will improve treatment outcomes, increase compliance, reduce hospital stays, provide mobile clinical monitoring, have a positive impact on treatment costs and will contribute to increased patient safety.

Sexual Function in Postmenopausal Women With Symptomatic Pelvic Organ Prolapse Treated Either with Locally Applied Estrogen or Placebo: Results of a Double-Masked, Placebo-Controlled, Multicenter Trial.

BACKGROUND: Local estrogen therapy (LET) has beneficial effects on genitourinary atrophy; however it is currently unclear if LET improves sexual function in postmenopausal women with pelvic organ prolapse (POP). AIM: To evaluate if LET vs placebo results in an improved sexual function in postmenopausal women with symptomatic POP. METHODS: We performed a secondary analysis of sexual outcomes of a previous randomized controlled trial comparing LET and placebo in 120 postmenopausal women (60/group) with symptomatic POP stage ≥3 and planned prolapse surgery. Women were randomly assigned to receive local estrogen or placebo cream 6 weeks preoperatively. The effect of therapy vs placebo was assessed with ANOVA with interaction effect of time*group and a multivariable linear regression model was built to assess the impact of different variables on sexual function before therapy. OUTCOMES: We evaluated the sexual function score in sexually active women of our study population using the German Pelvic Floor Questionnaire at recruitment time and again after 6 weeks of treatment. RESULTS: Among 120 randomized women, 66 sexually active women remained for final analysis. There was no significant difference in the change of the sexual function score over time between the treatment groups (difference in changes in score from baseline to 6 weeks for Estrogen group vs control group was -0.110 with 95% CI -0.364 to 0.144) Multivariable analysis showed that no independent risk factor for unsatisfying sexual function score could be identified. CLINICAL IMPLICATIONS: Based on our results, LET has no beneficial effect on sexual function in postmenopausal women with POP. STRENGTHS AND LIMITATIONS: Main strength of our study lies in the study design and in the use of a condition- specific questionnaire. As this is a secondary analysis, this study may be insufficiently powered to identify differences in sexual data between groups. CONCLUSION: LET had no impact on female sexuality in postmenopausal women with POP. Marschalek M-L, Bodner K, Kimberger O, et al. Sexual Function in Postmenopausal Women With Symptomatic Pelvic Organ Prolapse Treated Either with Locally Applied Estrogen or Placebo: Results of a Double-Masked, Placebo-Controlled, Multicenter Trial. J Sex Med 2022;19:1124-1130.

Progressive cholestasis and associated sclerosing cholangitis are frequent complications of COVID-19 in patients with chronic liver disease.

BACKGROUND AND AIMS: Cholestasis is associated with disease severity and worse outcome in COVID-19. Cases of secondary sclerosing cholangitis (SSC) after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have been described. APPROACH AND RESULTS: Hospitalized patients with COVID-19 between 03/2020 and 07/2021 were included. Patients were stratified as having (i) no chronic liver disease (CLD), (ii) non-advanced CLD (non-ACLD), or (iii) advanced CLD (ACLD). Patients with CLD and non-COVID-19 pneumonia were matched to patients with CLD and COVID-19 as a control cohort. Liver chemistries before (Pre) and at first, second, and third blood withdrawal after SARS-CoV-2 infection (T1-T3) and at last available time point (last) were recorded. A total of 496 patients were included. In total, 13.1% (n = 65) had CLD (non-ACLD: 70.8%; ACLD: 29.2%); the predominant etiology was NAFLD/NASH (60.0%). COVID-19-related liver injury was more common among patients with CLD (24.6% vs. 10.6%; p = 0.001). After SARS-CoV-2 infection, patients with CLD exhibited progressive cholestasis with persistently increasing levels of alkaline phosphatase (Pre: 91.0 vs. T1: 121.0 vs. last: 175.0 U/L; p < 0.001) and gamma-glutamyl transferase (Pre: 95.0 vs. T1: 135.0 vs. last: 202.0 U/L; p = 0.001). A total of 23.1% of patients with CLD (n = 15/65) developed cholestatic liver failure (cholestasis plus bilirubin ≥6 mg/dl) during COVID-19, and 15.4% of patients (n = 10/65) developed SSC. SSC was significantly more frequent among patients with CLD and COVID-19 than in patients with CLD and non-COVID-19 pneumonia (p = 0.040). COVID-19-associated SSC occurred predominantly in patients with NAFLD/NASH and metabolic risk factors. A total of 26.3% (n = 5/19) of patients with ACLD experienced hepatic decompensation after SARS-CoV-2 infection. CONCLUSIONS: About 20% of patients with CLD develop progressive cholestasis after SARS-CoV-2 infection. Patients with NAFLD/NASH and metabolic risk factors are at particular risk for developing cholestatic liver failure and/or SSC after COVID-19.

Methaemoglobinemia after Liposuction under Tumescent Local Anaesthesia - Diagnostic Value of Pulse Oximetry.

Background: Tumescent local anaesthesia with prilocain can lead to clinically significant methemoglobin levels. New generation multiple wavelength pulse oximeters (e. g. Masimo Radical 7®) can measure methemoglobin levels. Methods: In this prospective observational study we compared the venous methemoglobin levels and the corresponding pulse oximetric values of the Radical 7® in patients undergoing tumescent local anaesthesia for liposuction procedures. The measurements were performed in Hanseklinik, Luebeck, Germany between 2008 and 2011. Results: In 133 patients, we measured a maximum methemoglobin level of 18 per cent. In a Bland-Altman analysis we found a mean bias of +2.2 % (-4.1 to 8.4 limits of agreement) for pulse oximetric values compared to hemoximetry. Conclusion: Pulse oximetric measurement of methemoglobin is an early-warning tool for the detection of clinically significant methaemoglobinemia in patients with tumescent local anaesthesia.