Characteristics and burden of acute COVID-19 and long-COVID: Demographic, physical, mental health, and economic perspectives.

BACKGROUND: COVID-19 infection and its associated consequence, known as long-COVID, lead to a significant burden on the global healthcare system and limitations in people's personal and work lives. This study aims to provide further insight into the impact of acute and ongoing COVID-19 symptoms and investigates the role of patients' gender and vaccination status. METHODS: 416 individuals (73.9% female) between the ages of 16 and 80 years (M = 44.18, SD = 12.90) with self-reported symptoms of long-COVID participated in an online survey conducted between March and May 2022. RESULTS: 6.0%, 74.3%, and 19.7% of all respondents reported having had an asymptomatic, mild, or severe acute illness, respectively. Out of all participants, 7.8% required hospitalization. The most prevalent symptoms during the acute infection (Mdn = 23.50 symptoms, IQR = 13-39) included fatigue, exhaustion, cough, brain fog, and memory problems. The median long-COVID disease duration was 12.10 months (IQR = 2.8-17.4). Among 64 inquired long-COVID symptoms (Mdn = 17.00 symptoms, IQR = 9-27), participants reported fatigue, exhaustion, memory problems, brain fog, and dyspnea as the most common ongoing symptoms, which were generally experienced as fluctuating and deteriorating after physical or cognitive activity. Common consequences of long-COVID included financial losses (40.5%), changes in the participants' profession (41.0%), stress resistance (87.5%), sexual life (38.1%), and mood (72.1%), as well as breathing difficulties (41.3%), or an increased drug intake (e.g., medicine, alcohol; 44.6%). In addition, vaccinated individuals exhibited a shorter acute illness duration and an earlier onset of long-COVID symptoms. In general, women reported more long-COVID symptoms than men. CONCLUSION: Long-COVID represents a heterogeneous disease and impacts multiple life aspects of those affected. Tailored rehabilitation programs targeting the plurality of physical and mental symptoms are needed.

A Mobile Computerized Decision Support System to Prevent Hypoglycemia in Hospitalized Patients With Type 2 Diabetes Mellitus.

BACKGROUND: Diabetes management requires complex and interdisciplinary cooperation of health care professionals (HCPs). To support this complex process, IT-support is recommended by clinical guidelines. The aim of this article is to report on results from a clinical feasibility study testing the prototype of a mobile, tablet-based client-server system for computerized decision and workflow support (GlucoTab®) and to discuss its impact on hypoglycemia prevention. METHODS: The system was tested in a monocentric, open, noncontrolled intervention study in 30 patients with type 2 diabetes mellitus (T2DM). The system supports HCPs in performing a basal-bolus insulin therapy. Diabetes therapy, adverse events, software errors and user feedback were documented. Safety, efficacy and user acceptance of the system were investigated. RESULTS: Only 1.3% of blood glucose (BG) measurements were <70 mg/dl and only 2.6% were >300 mg/dl. The availability of the system (97.3%) and the rate of treatment activities documented with the system (>93.5%) were high. Only few suggestions from the system were overruled by the users (>95.7% adherence). Evaluation of the 3 anonymous questionnaires showed that confidence in the system increased over time. The majority of users believed that treatment errors could be prevented by using this system. CONCLUSIONS: Data from our feasibility study show a significant reduction of hypoglycemia by implementing a computerized system for workflow and decision support for diabetes management, compared to a paper-based process. The system was well accepted by HCPs, which is shown in the user acceptance analysis and that users adhered to the insulin dose suggestions made by the system.

Standardized Glycemic Management with a Computerized Workflow and Decision Support System for Hospitalized Patients with Type 2 Diabetes on Different Wards.

BACKGROUND: This study investigated the efficacy, safety, and usability of standardized glycemic management by a computerized decision support system for non-critically ill hospitalized patients with type 2 diabetes on four different wards. MATERIALS AND METHODS: In this open, noncontrolled intervention study, glycemic management of 99 patients with type 2 diabetes (62% acute admissions; 41 females; age, 67±11 years; hemoglobin A1c, 65±21 mmol/mol; body mass index, 30.4±6.5 kg/m(2)) on clinical wards (Cardiology, Endocrinology, Nephrology, Plastic Surgery) of a tertiary-care hospital was guided by GlucoTab(®) (Joanneum Research GmbH [Graz, Austria] and Medical University of Graz [Graz, Austria]), a mobile decision support system providing automated workflow support and suggestions for insulin dosing to nurses and physicians. RESULTS: Adherence to insulin dosing suggestions was high (96.5% bolus, 96.7% basal). The primary outcome measure, percentage of blood glucose (BG) measurements in the range of 70-140 mg/dL, occurred in 50.2±22.2% of all measurements. The overall mean BG level was 154±35 mg/dL. BG measurements in the ranges of 60-70 mg/dL, 40-60 mg/dL, and <40 mg/dL occurred in 1.4%, 0.5%, and 0.0% of all measurements, respectively. A regression analysis showed that acute admission to the Cardiology Ward (+30 mg/dL) and preexisting home insulin therapy (+26 mg/dL) had the strongest impact on mean BG. Acute admission to other wards had minor effects (+4 mg/dL). Ninety-one percent of the healthcare professionals felt confident with GlucoTab, and 89% believed in its practicality and 80% in its ability to prevent medication errors. CONCLUSIONS: An efficacious, safe, and user-accepted implementation of GlucoTab was demonstrated. However, for optimized personalized patient care, further algorithm modifications are required.

Taking a Closer Look--Continuous Glucose Monitoring in Non-Critically Ill Hospitalized Patients with Type 2 Diabetes Mellitus Under Basal-Bolus Insulin Therapy.

BACKGROUND: Inpatient glucose management is based on four daily capillary blood glucose (BG) measurements. The aim was to test the capability of continuous glucose monitoring (CGM) for assessing the clinical impact and safety of basal-bolus insulin therapy in non-critically ill hospitalized patients with type 2 diabetes mellitus (T2DM). MATERIALS AND METHODS: Eighty-four patients with T2DM (age, 68±10 years; glycosylated hemoglobin, 72±28 mmol/mol; body mass index, 31±7 kg/m(2)) were treated with basal-bolus insulin. CGM was performed with the iPro(®)2 system (Medtronic MiniMed, Northridge, CA) and calibrated retrospectively. RESULTS: A remarkable consistency between CGM and BG measurements and therapy improvement was shown over the study period of 501 patient-days. The number of CGM and BG measurements (CGM/BG) in the range from 3.9-10 mmol/L increased from 67.7%/67.2% (on Day 1) to 77.5%/78.6% (on the last day) (P<0.04). The number of low glycemic episodes (3.3 to <3.9 mmol/L) during nighttime detected by CGM was 15-fold higher, and the number of episodes >13.9 mmol/L detected by CGM during night was 12.5-fold higher than the values from the BG measurements. Ninety-nine percent of data points were in the clinically accurate or acceptable Clarke Error Grid Zones A+B, and the relative numbers of correctly identified episodes of <3.9 and >13.9 mmol/L detected by CGM (sensitivity) were 47.3% and 81.5%, respectively. CONCLUSIONS: Our data exhibit a good agreement between overall CGM and BG measurements, but there were a high number of missed hypo- and hyperglycemic episodes with BG measurements, particularly during nighttime. Overall assessment of glycemic control using CGM is feasible, whereas the use of CGM for individualized therapy decisions needs further improvement.

Automatic system testing of a decision support system for insulin dosing using Google Android.

Hyperglycaemia in hospitalized patients is a common and costly health care problem. The GlucoTab system is a mobile workflow and decision support system, aiming to facilitate efficient and safe glycemic control of non-critically ill patients. Being a medical device, the GlucoTab requires extensive and reproducible testing. A framework for high-volume, reproducible and automated system testing of the GlucoTab system was set up applying several Open Source tools for test automation and system time handling. The REACTION insulin titration protocol was investigated in a paper-based clinical trial (PBCT). In order to validate the GlucoTab system, data from this trial was used for simulation and system tests. In total, 1190 decision support action points were identified and simulated. Four data points (0.3%) resulted in a GlucoTab system error caused by a defective implementation. In 144 data points (12.1%), calculation errors of physicians and nurses in the PBCT were detected. The test framework was able to verify manual calculation of insulin doses and detect relatively many user errors and workflow anomalies in the PBCT data. This shows the high potential of the electronic decision support application to improve safety of implementation of an insulin titration protocol and workflow management system in clinical wards.

Self-management of oral anticoagulation in elderly patients - effects on treatment-related quality of life.

UNLABELLED: BACKGROUND - RATIONALE FOR STUDY: In elderly patients, long-term self-management of oral anticoagulation has been shown to reduce the number of major thromboembolic and bleeding complications and improve the quality of oral anticoagulation (OAC) control compared to routine care for a mean follow-up period of three years. This article presents the results of the predefined secondary endpoint treatment-related quality of life (QoL). METHODS AND RESULTS: The effect of self-management on five aspects of QoL was evaluated in comparison with routine care. A validated questionnaire specifically designed for patients receiving OAC was used. The evaluation was possible for 141 patients, comprising 90% of surviving patients on OAC. At baseline, all patients had high scores for the following QoL-aspects: general treatment satisfaction, self-efficacy, daily hassles and strained social network. A high proportion of patients in both groups explicitly reported high distress, indicating that general psychological distress seems to be of particular concern in this population. After about 3 years of follow-up, patients performing self-management showed a significantly greater improvement in general treatment satisfaction than controls (median score increase [25th percentile, 75th percentile]: 0.9 [0.0, 1.6] vs. 0.0 [-0.2, 0.6], p=0.002; scale 1-6). Changes in general psychological distress, self-efficacy, daily hassles and strained social network were not significant. CONCLUSION: Treatment related quality of life in elderly patients performing self-management of OAC was similar as for patients in routine care setting, with a tendency of higher general treatment satisfaction, after three years of follow up.

Diabetes management using modern information and communication technologies and new care models.

BACKGROUND: Diabetes, a metabolic disorder, has reached epidemic proportions in developed countries. The disease has two main forms: type 1 and type 2. Disease management entails administration of insulin in combination with careful blood glucose monitoring (type 1) or involves the adjustment of diet and exercise level, the use of oral anti-diabetic drugs, and insulin administration to control blood sugar (type 2). OBJECTIVE: State-of-the-art technologies have the potential to assist healthcare professionals, patients, and informal carers to better manage diabetes insulin therapy, help patients understand their disease, support self-management, and provide a safe environment by monitoring adverse and potentially life-threatening situations with appropriate crisis management. METHODS: New care models incorporating advanced information and communication technologies have the potential to provide service platforms able to improve health care, personalization, inclusion, and empowerment of the patient, and to support diverse user preferences and needs in different countries. The REACTION project proposes to create a service-oriented architectural platform based on numerous individual services and implementing novel care models that can be deployed in different settings to perform patient monitoring, distributed decision support, health care workflow management, and clinical feedback provision. RESULTS: This paper presents the work performed in the context of the REACTION project focusing on the development of a health care service platform able to support diabetes management in different healthcare regimes, through clinical applications, such as monitoring of vital signs, feedback provision to the point of care, integrative risk assessment, and event and alarm handling. While moving towards the full implementation of the platform, three major areas of research and development have been identified and consequently approached: the first one is related to the glucose sensor technology and wearability, the second is related to the platform architecture, and the third to the implementation of the end-user services. The Glucose Management System, already developed within the REACTION project, is able to monitor a range of parameters from various sources including glucose levels, nutritional intakes, administered drugs, and patient's insulin sensitivity, offering decision support for insulin dosing to professional caregivers on a mobile tablet platform that fulfills the need of the users and supports medical workflow procedures in compliance with the Medical Device Directive requirements. CONCLUSIONS: Good control of diabetes, as well as increased emphasis on control of lifestyle factors, may reduce the risk profile of most complications and contribute to health improvement. The REACTION project aims to respond to these challenges by providing integrated, professional, management, and therapy services to diabetic patients in different health care regimes across Europe in an interoperable communication platform.

Design of a mobile, safety-critical in-patient glucose management system.

Diabetes mellitus is one of the most widespread diseases in the world. People with diabetes usually have long stays in hospitals and need specific treatment. In order to support in-patient care, we designed a prototypical mobile in-patient glucose management system with decision support for insulin dosing. In this paper we discuss the engineering process and the lessons learned from the iterative design and development phases of the prototype. We followed a user-centered development process, including real-life usability testing from the outset. Paper mock-ups in particular proved to be very valuable in gaining insight into the workflows and processes, with the result that user interfaces could be designed exactly to the specific needs of the hospital personnel in their daily routine.

Enhanced information retrieval from narrative German-language clinical text documents using automated document classification.

The amount of narrative clinical text documents stored in Electronic Patient Records (EPR) of Hospital Information Systems is increasing. Physicians spend a lot of time finding relevant patient-related information for medical decision making in these clinical text documents. Thus, efficient and topical retrieval of relevant patient-related information is an important task in an EPR system. This paper describes the prototype of a medical information retrieval system (MIRS) for clinical text documents. The open-source information retrieval framework Apache Lucene has been used to implement the prototype of the MIRS. Additionally, a multi-label classification system based on the open-source data mining framework WEKA generates metadata from the clinical text document set. The metadata is used for influencing the rank order of documents retrieved by physicians. Combining information retrieval and automated document classification offers an enhanced approach to let physicians and in the near future patients define their information needs for information stored in an EPR. The system has been designed as a J2EE Web-application. First findings are based on a sample of 18,000 unstructured, clinical text documents written in German.