Edouard Battegay

Background: The health aspects, disease frequencies, and specific health interests of prisoners and refugees are poorly understood. Importantly, access to the health care system is limited for this vulnerable population. There has been no systematic investigation to understand the health issues of inmates in Switzerland. Furthermore, little is known on how recent migration flows in Europe may have affected the health conditions of inmates. Objective: The Swiss Prison Study (SWIPS) is a large-scale observational study with the aim of establishing a public health registry in northern-central Switzerland. The primary objective is to establish a central database to assess disease prevalence (ie, International Classification of Diseases-10 codes [German modification]) among prisoners. The secondary objectives include the following: (1) to compare the 2015 versus 2020 disease prevalence among inmates against a representative sample from the local resident population, (2) to assess longitudinal changes in disease prevalence from 2015 to 2020 by using cross-sectional medical records from all inmates at the Police Prison Zurich, Switzerland, and (3) to identify unrecognized health problems to prepare successful public health strategies. Methods: Demographic and health-related data such as age, sex, country of origin, duration of imprisonment, medication (including the drug name, brand, dosage, and release), and medical history (including the International Classification of Diseases-10 codes [German modification] for all diagnoses and external results that are part of the medical history in the prison) have been deposited in a central register over a span of 5 years (January 2015 to August 2020). The final cohort is expected to comprise approximately 50,000 to 60,000 prisoners from the Police Prison Zurich, Switzerland. Results: This study was approved on August 5, 2019 by the ethical committee of the Canton of Zurich with the registration code KEK-ZH No. 2019-01055 and funded in August 2020 by the “Walter and Gertrud Siegenthaler” foundation and the “Theodor and Ida Herzog-Egli” foundation. This study is registered with the International Standard Randomized Controlled Trial Number registry. Data collection started in August 2019 and results are expected to be published in 2021. Findings will be disseminated through scientific papers as well as presentations and public events. Conclusions: This study will construct a valuable database of information regarding the health of inmates and refugees in Swiss prisons and will act as groundwork for future interventions in this vulnerable population. Trial Registration: ISRCTN registry ISRCTN11714665; http://www.isrctn.com/ISRCTN11714665 International Registered Report Identifier (IRRID): DERR1-10.2196/23973

BACKGROUND The health aspects, disease frequencies, and specific health interests of prisoners and refugees are poorly understood. Importantly, access to the health care system is limited for this vulnerable population. There has been no systematic investigation to understand the health issues of inmates in Switzerland. Furthermore, little is known on how recent migration flows in Europe may have affected the health conditions of inmates. OBJECTIVE The Swiss Prison Study (SWIPS) is a large-scale observational study with the aim of establishing a public health registry in northern-central Switzerland. The primary objective is to establish a central database to assess disease prevalence (ie, International Classification of Diseases-10 codes [German modification]) among prisoners. The secondary objectives include the following: (1) to compare the 2015 versus 2020 disease prevalence among inmates against a representative sample from the local resident population, (2) to assess longitudinal changes in disease prevalence from 2015 to 2020 by using cross-sectional medical records from all inmates at the Police Prison Zurich, Switzerland, and (3) to identify unrecognized health problems to prepare successful public health strategies. METHODS Demographic and health-related data such as age, sex, country of origin, duration of imprisonment, medication (including the drug name, brand, dosage, and release), and medical history (including the International Classification of Diseases-10 codes [German modification] for all diagnoses and external results that are part of the medical history in the prison) have been deposited in a central register over a span of 5 years (January 2015 to August 2020). The final cohort is expected to comprise approximately 50,000 to 60,000 prisoners from the Police Prison Zurich, Switzerland. RESULTS This study was approved on August 5, 2019 by the ethical committee of the Canton of Zurich with the registration code KEK-ZH No. 2019-01055 and funded in August 2020 by the “Walter and Gertrud Siegenthaler” foundation and the “Theodor and Ida Herzog-Egli” foundation. This study is registered with the International Standard Randomized Controlled Trial Number registry. Data collection started in August 2019 and results are expected to be published in 2021. Findings will be disseminated through scientific papers as well as presentations and public events. CONCLUSIONS This study will construct a valuable database of information regarding the health of inmates and refugees in Swiss prisons and will act as groundwork for future interventions in this vulnerable population. CLINICALTRIAL ISRCTN registry ISRCTN11714665; http://www.isrctn.com/ISRCTN11714665 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/23973

Clinical prediction scores support the assessment of patients in the emergency setting to determine the need for further diagnostic and therapeutic steps. During the current COVID-19 pandemic, physicians in emergency rooms (ER) of many hospitals have a considerably higher patient load and need to decide within a short time frame whom to hospitalize. Based on our clinical experiences in dealing with COVID-19 patients at the University Hospital Zurich, we created a triage score with the acronym AIFELL consisting of clinical, radiological and laboratory findings. The score was then evaluated in a retrospective analysis of 122 consecutive patients with suspected COVID-19 from March until mid-April 2020. Descriptive statistics, Student’s t-test, ANOVA and Scheffe’s post hoc analysis confirmed the diagnostic power of the score. The results suggest that the AIFELL score has potential as a triage tool in the ER setting intended to select probable COVID-19 cases for hospitalization in spontaneously presenting or referred patients with acute respiratory symptoms.

New and changing patterns of multimorbidity (MM), i.e., multiple concurrent acute or chronic diseases in a person, are emerging in low- and middle-income countries (LMICs). The interplay of underlying population-specific factors and lifestyle habits combined with the colliding epidemics of communicable and non-communicable diseases presents new disease combinations, complexities and risks that are not common in high-income countries (HICs). The complexities and risks include those arising from potentially harmful drug-drug and drug-disease interactions (DDIs), the management of which may be considered as MM in the true sense. A major concern in LMICs is the increasing burden of leading cardiovascular diseases, prevalence of associated risk factors and co-occurrence with other morbidities. New models of MM management and integrated care can respond to the needs of specific multimorbid populations, with some LMICs making substantial progress (e.g., integration of tuberculosis and HIV services in South Africa). But there is a dearth of relevant data on the changing patterns and underlying factors and determinants of MM, the associated complexities and risks of DDIs in MM management, and the barriers to integrated care in LMICs. This requires careful attention.

Background: Caregivers encounter serious and substantial challenges in managing hypertension in patients with subclinical or clinical borderline personality disorder (BPD). These challenges include therapeutic conflicts resulting from harmful drug–drug, and drug–disease interactions. Current guidelines provide no recommendations for concurrent psychotropic and antihypertensive treatment of hypertensive BPD patients who are at even greater cardiovascular risk. Methods: We conducted a systematic literature review to assess the extent of available evidence on prevalence rates, cardiovascular risk factors, therapeutic conflicts, and evidence-based treatment recommendations for patients with co-occurring hypertension and BPD. Search terms were combined for hypertension and BPD in PubMed, MEDLINE, EMBASE, Cochrane, and PsycINFO databases. Results: We included 11 articles for full-text evaluation and found a very high prevalence of hypertension and substantial cardiovascular risk in studies on co-occurring BPD and hypertension. However, we identified neither studies on harmful drug–drug and drug–disease interactions nor studies with treatment recommendations for co-occurring hypertension and BPD. Conclusions: Increased prevalence of hypertension in BPD patients, and therapeutic conflicts of psychotropic agents strongly suggest careful evaluation of treatment strategies in this patient group. However, no studies or guidelines recommend specific therapies or strategies to resolve therapeutic conflicts in patients with hypertension and BPD. This evidence gap needs attention in this population at high risk for cardiovascular disease.

Etwa 20–25 % aller Personen und etwa 90 % aller akut in einer Klinik für Innere Medizin hospitalisierten Patienten weisen gleichzeitig mehrere akute oder chronische Erkrankungen auf. Sie sind multimorbid. Die Begegnung mit multimorbiden Patienten ist die häufigste Situation im Gesundheitssystem geworden. Theoretisch besteht bei Multimorbidität eine kaum benennbare Anzahl möglicher Erkrankungskonstellationen. Zudem nehmen die Wahrscheinlichkeit von Interaktionen zwischen Erkrankungen („disease-disease interactions“ [DDI]) und die Komplexität mit jeder hinzukommenden Erkrankung überlinear zu. Multimorbidität tritt häufig in typischen dyadischen, triadischen oder höheren charakteristischen Kombinationsmustern auf, in „Krankheitssclustern“, z. B. aus vaskulären Risikofaktoren, Herz- und Lungenerkrankungen, Frailty (Gebrechlichkeit) und Demenz oder psychiatrischen und somatischen Erkrankungen. Solche Kombinationen führen zur Verschlechterung der Gesamtprognose und oft zu schwierig handhabbaren bis lebensgefährlichen DDI. Beispiele für DDI sind: Antikoagulation und gleichzeitige schwere Blutung, Schmerz und Hypertonie oder Niereninsuffizienz, Depression und verminderte Medikamentencompliance, chronisch-obstruktive Lungenerkrankung und Depression, Frailty und Psychopharmaka sowie häufige Stürze, psychiatrische und somatische Erkrankungen in Kombination. Solche DDI sind häufig. Trotzdem gibt es dazu nur wenige Studien und klinische Leitlinien. Die Betreuung multimorbider Patienten basiert auf Leitlinien zu meist gut untersuchten Einzelerkrankungen. Multimorbidität und schwerwiegende DDI sind in diesen meist nicht thematisiert. Klinische Leitlinien können so ungewollt die Sicherheit von mehrfach erkrankten Personen gefährden. Zudem geraten Ärzte bei Therapieentscheidungen mit Bezug auf DDI in belastende Dilemmata. About 20–25% of all persons and about 90% of all patients who are acutely hospitalized in internal medicine departments have multiple acute or chronic diseases. They are multimorbid. The encounter with multimorbid patients has become the most common situation in the health care system. Theoretically, multimorbidity results in an innumerable potential disease constellations. In addition, the likelihood of interactions between diseases (disease–disease interactions, DDI) and the complexity increases overproportionately with each additional disease. However, multimorbidity often occurs in typical diadic, triadic, or higher characteristic combinations, in “disease clusters”, e. g., vascular risk factors, heart and lung diseases, Frailty and dementia, psychiatric and somatic disorders. Such combinations lead to a worsening of the overall prognosis. In addition, DDIs are often difficult to treat or are life-threatening. Examples of DDIs include the following: anticoagulation and simultaneous severe bleeding, pain treatment and hypertension or renal insufficiency, depression and reduced medication adherence, chronic obstructive pulmonary disease and depression, Frailty and neurodepressant drugs and frequent falls, and combined psychiatric and somatic disorders. Such DDIs are common. Nevertheless, there are few studies and clinical guidelines that address these issues. The care of multimorbid patients is, therefore, heavily reliant upon guidelines developed mostly for single diseases. However, multimorbidity and serious DDIs are usually not addressed in these. Clinical guidelines can thus inadvertently jeopardize the safety of persons suffering from multiple diseases. In addition, stressful dilemmas arise for physicians encountering DDIs because of difficult treatment decisions.