Vorhersagekraft der Veränderung eines Frailty Index basierend auf Blut- und Urin-Analysen während eines Krankenhausaufenthaltes bezüglich 6-Monats- und 1-Jahres-Mortalität bei geriatrischen Patienten

Abstract Background A frailty index based solely on laboratory blood and urine tests (FI-Lab) might be an easy and quick frailty instrument in hospitalized geriatric patients. Our aims were to evaluate the predictive abilities of a FI-Lab assessed at different points in time, ie, at admission to hospital (FI-Lab21admission) and before discharge from hospital (FI-Lab21discharge), and the change of the FI-Lab during the hospital stay (FI-Lab21admission minus FI-Lab21discharge) for six-month and one-year mortality in hospitalized geriatric patients. Methods 500 patients aged ≥ 65 years hospitalized on geriatric wards were included in this analysis. Follow-up data were acquired at six months and one year after the baseline examination. Results The FI-Lab21 scores of the study participants decreased during the hospital stay from 0.33±0.15 to 0.31±0.14, P<0.001. The FI-Lab21admission and FI-Lab21discharge were both able to discriminate between patients who died and those who survived during the six-month and one-year follow-up periods (areas under the receiver operating characteristic curves (AUCs: 0.72, 0.72, 0.77 and 0.75 respectively, all P<0.001). The FI-Lab21admission revealed inferior discriminative ability for six-month and one-year mortality compared to the FI-Lab21discharge (all P<0.05). Patients with an increase of the FI-Lab21 during the hospital stay revealed higher six-month and one-year mortality rates compared to the persons who’s FI-Lab21 score did not change or decreased during the hospital stay (all P<0.05). Conclusions The FI-Lab21admission, FI-Lab21discharge and the change of the FI-Lab21 during the hospital stay of the individuals emerged as interesting and feasible approaches to stratify mortality risk in hospitalized geriatric patients.Hintergrund und Ziele Ziel der vorliegenden Studie war es, einen Frailty Index (FI-Lab21) zu untersuchen, welcher auf 21 verschiedenen routinemäßig erfassten Blut- und Urinparametern basierte. Ein solcher Frailty Index lässt sich aus Parametern konstruieren, die im klinischen Alltag routinemäßig gewonnen werden und ohne größeren Aufwand zu erheben sind. Ein Instrument, mit welchem sich ohne besondere apparative und logistische Herausforderungen und unter überschaubarem Zeitaufwand eine Risikoabschätzung bezüglich Frailty erfassen lässt, ist interessant für klinisch tätige Ärztinnen und Ärzte. Methoden (Patienten, Material und Untersuchungsmethoden) Um einen solchen Frailty Index zu entwickeln und zu validieren, wurden bei den an der Studie partizipierenden Patientinnen und Patienten die Blut- und Urinparameter bei Aufnahme und vor Entlassung erhoben. Hieraus konnte ein Frailty Index bei Aufnahme (FI-Lab21Aufnahme), ein Frailty Index vor Entlassung (FI-Lab21Entlassung) sowie die Differenz dieser beiden Frailty Indices errechnet werden (ΔFI-Lab21). Bei fünfhundert Patientinnen und Patienten wurde der FI-Lab21Aufnahme, der FI-Lab21Entlassung, sowie das ΔFI-Lab21 ermittelt. Follow-up Daten wurden nach sechs Monaten und nach zwölf Monaten erhoben. Zur Datenanalyse wurden ROC-Kurven (Reciever operating characteristic curves) für den FI-Lab21Aufnahme, den FI-Lab21Entlassung und den ΔFI-Lab21 bezüglich der 6- bzw. 12-Monats-Mortalität berechnet. Vergleiche zwischen ROC-Kurven wurden nach der Methode von Hanley und McNeil erstellt. Kaplan-Meier-Überlebenskurven wurden angewendet, um die Sterblichkeit in Abhängigkeit des FI-Lab21-Wertes darzustellen. Ergebnisse und Beobachtungen Durch die statistischen Analysen lassen sich zusammenfassend folgende Resultate festhalten. Sowohl der FI-Lab21Aufnahme als auch der FI- Lab21Entlassung zeigten sich prädiktiv für sechs-Monats- bzw. zwölf-Monats-Mortalität (alle P<0,05). Der FI-Lab21Entlassung war hierbei jeweils ein stärkerer Indikator für Mortalität als der FI-Lab21Aufnahme (P<0,05). Patientinnen und Patienten mit gleichbleibendem oder sich verringerndem FI-Lab21 während der stationären Behandlung wiesen niedrigere Mortalitätsraten nach sechs- bzw. zwölf Monaten auf als Individuen, deren Frailty Index über die stationäre Therapie zunahm (jeweils P<0,05). Schlussfolgerungen Zusammenfassend stellte sich heraus, dass der FI-Lab21Aufnahme, sowie der FI-Lab21Entlassung, als auch das ΔFI-Lab21 während der stationären Behandlung als interessante und nützliche Instrumente zur Risikostratifizierung bezüglich Mortalität bei älteren stationär behandelten Personen auf geriatrischen Stationen dienen konnten

Quality and variation of care for chronic kidney disease in Swiss general practice: A retrospective database study

Background Chronic kidney disease (CKD) is a common condition in general practice. Data about quality and physician-level variation of CKD care provided by general practitioners is scarce. In this study, we evaluated determinants and variation of achievement of 14 quality indicators for CKD care using electronic medical records data from Swiss general practice during 2013–2019. Methods We defined two patient cohorts from 483 general practitioners, one to address renal function assessment in patients with predisposing conditions (n = 47,201, median age 68 years, 48.7% female) and one to address care of patients with laboratory-confirmed CKD (n = 14,654, median age 80 years, 57.5% female). We investigated quality indicator achievement with mixed-effect logistic regression and expressed physician-level variation as intraclass correlation coefficients (ICCs) and range odds ratios (rORs). Results We observed the highest quality indicator achievement rate for withholding non-steroidal anti-inflammatory drug prescription in patients with CKD staged G2–3b within 12 months of follow-up (82.6%), the lowest for albuminuria assessment within 18 months of follow-up (18.1%). Highest physician-level variation was found for renal function assessment during 18 months of follow-up in patients with predisposing conditions (diabetes: ICC 0.31, rOR 26.5; cardiovascular disease: ICC 0.28, rOR 17.4; hypertension: ICC 0.24, rOR 17.2). Conclusion This study suggests potentially unwarranted variation in general practice concerning RF assessment in patients affected by conditions predisposing for CKD. We further identified potential gaps in quality of CKD monitoring as well as lower quality of CKD care for female patients and patients not affected by comorbidities

Testing and Prescribing Vitamin B12 in Swiss General Practice: A Survey among Physicians

Testing and prescribing vitamin B12 (also known as cobalamin) is increasing in Switzerland but substantial variation among general practitioners (GPs) with respect to testing has been noted. In this study, we aimed at exploring GPs’ mindsets regarding vitamin B12 testing and prescribing. A cross-sectional study was conducted using an online survey distributed by e-mail to Swiss GPs. The questionnaire explored mindsets related to testing and prescribing vitamin B12 in specific clinical situations, as well as testing and prescribing strategies. The questionnaire was sent to 876 GPs and 390 GPs responded (44.5%). The most controversial domains for testing and prescribing vitamin B12 were idiopathic fatigue (57.4% and 43.4% of GPs agreed, respectively) and depressive symptoms (53.0% and 35.4% of GPs agreed, respectively). There was substantial variation among GPs with regard to testing strategies (89.5% of GPS used a serum cobalamin test, 71.3% of GPS used holotranscobalamin, and 27.6% of GPs used homocysteine or methylmalonic acid). Intramuscular injection was the predominantly prescribed route of application (median of 87.5% of the prescriptions). In this study, we focus on discordant mindsets that can be specifically targeted by using educational interventions, and research questions that still need answering specifically about the effectiveness of vitamin B12 for idiopathic fatigue

Prescription Rates, Polypharmacy and Prescriber Variability in Swiss General Practice—A Cross-Sectional Database Study

Purpose: The frequency of medication prescribing and polypharmacy has increased in recent years in different settings, including Swiss general practice. We aimed to describe patient age- and sex-specific rates of polypharmacy and of prescriptions of the most frequent medication classes, and to explore practitioner variability in prescribing.Methods: Retrospective cross-sectional study based on anonymized electronic medical records data of 111 811 adult patients presenting to 116 Swiss general practitioners in 2019. We used mixed-effects regression analyses to assess the association of patient age and sex with polypharmacy (≥5 medications) and with the prescription of specific medication classes (second level of the Anatomical Therapeutic Chemical Classification System). Practitioner variability was quantified in terms of the random effects distributions.Results: The prevalence of polypharmacy increased with age from 6.4% among patients aged 18–40 years to 19.7% (41–64 years), 45.3% (65–80 years), and 64.6% (81–92 years), and was higher in women than in men, particularly at younger ages. The most frequently prescribed medication classes were antiinflammatory and antirheumatic products (21.6% of patients), agents acting on the renin-angiotensin system (19.9%), analgesics (18.7%), and drugs for acid related disorders (18.3%). Men were more often prescribed agents targeting the cardiovascular system, whereas most other medications were more often prescribed to women. The highest practitioner variabilities were observed for vitamins, for antiinflammatory and antirheumatic products, and for mineral supplements.Conclusion: Based on practitioner variability, prevalence, and risk potential, antiinflammatory drugs and polypharmacy in older patients appear to be the most pressing issues in current drug prescribing routines

Importance of different electronic medical record components for chronic disease identification in a Swiss primary care database: a cross-sectional study

BACKGROUND Primary care databases collect electronic medical records with routine data from primary care patients. The identification of chronic diseases in primary care databases often integrates information from various electronic medical record components (EMR-Cs) used by primary care providers. This study aimed to estimate the prevalence of selected chronic conditions using a large Swiss primary care database and to examine the importance of different EMR-Cs for case identification. METHODS Cross-sectional study with 120,608 patients of 128 general practitioners in the Swiss FIRE ("Family Medicine Research using Electronic Medical Records") primary care database in 2019. Sufficient criteria on three individual EMR-Cs, namely medication, clinical or laboratory parameters and reasons for encounters, were combined by logical disjunction into definitions of 49 chronic conditions; then prevalence estimates and measures of importance of the individual EMR-Cs for case identification were calculated. RESULTS A total of 185,535 cases (i.e. patients with a specific chronic condition) were identified. Prevalence estimates were 27.5% (95% CI: 27.3-27.8%) for hypertension, 13.5% (13.3-13.7%) for dyslipidaemia and 6.6% (6.4-6.7%) for diabetes mellitus. Of all cases, 87.1% (87.0-87.3%) were identified via medication, 22.1% (21.9-22.3%) via clinical or laboratory parameters and 19.3% (19.1-19.5%) via reasons for encounters. The majority (65.4%) of cases were identifiable solely through medication. Of the two other EMR-Cs, clinical or laboratory parameters was most important for identifying cases of chronic kidney disease, anorexia/bulimia nervosa and obesity whereas reasons for encounters was crucial for identifying many low-prevalence diseases as well as cancer, heart disease and osteoarthritis. CONCLUSIONS The EMR-C medication was most important for chronic disease identification overall, but identification varied strongly by disease. The analysis of the importance of different EMR-Cs for estimating prevalence revealed strengths and weaknesses of the disease definitions used within the FIRE primary care database. Although prioritising specificity over sensitivity in the EMR-C criteria may have led to underestimation of most prevalences, their sex- and age-specific patterns were consistent with published figures for Swiss general practice

Erfassung von Wissensorganisationssystemen in BARTOC - Ergebnis eines Projektseminars an der Hochschule Hannover

Das Basel Register of Thesauri, Ontologies &amp; Classifications (BARTOC) hat sich innerhalb weniger Jahre mit mehr als 2.700 Einträgen zu einem umfangreichen Verzeichnis von Wissensorganisationssystemen entwickelt. Im Sommersemester 2017 wurde diese Entwicklung von einem Projektseminar mit Bachelor-Studierenden der Hochschule Hannover begleitet. Eine Revision und Erweiterung der Inhalte von BARTOC führte zu einer besseren Abdeckung ausgewählter Metadatenfelder. Darüber hinaus wurden verschiedene Statistiken, Informationsmaterialien und ein neues Logo erstellt

In-context learning enables multimodal large language models to classify cancer pathology images

Medical image classification requires labeled, task-specific datasets which are used to train deep learning networks de novo, or to fine-tune foundation models. However, this process is computationally and technically demanding. In language processing, in-context learning provides an alternative, where models learn from within prompts, bypassing the need for parameter updates. Yet, in-context learning remains underexplored in medical image analysis. Here, we systematically evaluate the model Generative Pretrained Transformer 4 with Vision capabilities (GPT-4V) on cancer image processing with in-context learning on three cancer histopathology tasks of high importance: Classification of tissue subtypes in colorectal cancer, colon polyp subtyping and breast tumor detection in lymph node sections. Our results show that in-context learning is sufficient to match or even outperform specialized neural networks trained for particular tasks, while only requiring a minimal number of samples. In summary, this study demonstrates that large vision language models trained on non-domain specific data can be applied out-of-the box to solve medical image-processing tasks in histopathology. This democratizes access of generalist AI models to medical experts without technical background especially for areas where annotated data is scarce.Comment: 40 pages, 5 figure