Christophe Marti

Background: Point-of-care ultrasound (POCUS) has become an essential bedside tool in internal medicine; however, its expanding use is associated with substantial variability in training and scope of practice. Although several countries have developed consensus-based POCUS curricula and recommendations on relevant applications, no comparable national consensus currently exists in Switzerland, including on which applications should be prioritized for hospital-based general internal medicine (GIM) trainees. Methods: We conducted a three-round modified Delphi study between March and September 2025 to establish expert consensus on relevant POCUS applications for hospital-based GIM postgraduate training in Switzerland. Thirty hospital-based GIM-certified POCUS experts participated, including representatives from all Swiss university hospitals and accredited postgraduate training centers. Experts rated the clinical relevance of POCUS applications using Likert scales, allowing their classification as core, advanced, or irrelevant for GIM practice. Consensus was defined a priori as ≥70% agreement. Results: Across three Delphi rounds, 119 items were assessed. Final consensus was reached for 71 items: 24 were classified as core applications, 24 as advanced applications, and 23 as irrelevant for hospital internists. Core applications primarily included pulmonary ultrasound and ultrasound-guided procedures, along with selected focused cardiac and abdominal applications. Advanced applications reflected more context-dependent use, while obstetric/gynecologic, ocular, ear-nose-throat, and thyroid ultrasound were largely considered irrelevant. Several applications reaching core consensus are not currently included in the mandatory Swiss certification requirements. Conclusions: This national Delphi study identifies a consensus-based, prioritized set of POCUS applications for hospital-based GIM training in Switzerland. Rather than issuing prescriptive recommendations, these findings provide a structured basis to inform national dialogue and subsequent curriculum development. Considerations related to cost-effectiveness, implementation resources, and long-term sustainability were beyond the scope of this study and should be addressed in future evaluations to ensure feasible and equitable integration across institutions.

Point-of-care ultrasonography (POCUS) is increasingly used across multiple medical specialties, yet the impact of different teaching methods on learning outcomes remains unclear. Conduct a systematic review of randomized controlled trials (RCTs) comparing different methods of POCUS training and synthesize the available data. We searched MEDLINE, EMBASE, Cochrane, ERIC, and PsycINFO without language or date restrictions. Eligible studies were RCTs evaluating POCUS teaching methods for physicians. Studies focusing on pre-graduate learners, transesophageal or transvaginal ultrasound and procedural guidance were excluded. Records were screened and data were extracted by independent reviewers. Methodological quality assessment was performed using the Modified Medical Education Research Study Quality Instrument. The study protocol was prospectively registered in the international database of PROSPERO (CRD42024512650). Thirty-seven RCTs including 1,571 participants were identified. Interventions were grouped as simulation-based training (ten studies), web-based or video-assisted learning (ten studies), variations in training intensity or structure (eight studies), tele-mentoring (four studies), and other methods (five studies), mostly in comparison with traditional classroom teaching. Across most trials, interventions produced theoretical and practical skills without significant difference to traditional classroom models. Superiority was mainly observed when the intervention arm received greater training intensity or longitudinal supervision. Most studies used heterogeneous, non-standardizable assessments, precluding meta-analysis. For non-procedural postgraduate POCUS, several sustainable educational alternatives exist and may allow for similar competence when compared to traditional teaching. Training intensity, supervision, and longitudinal exposure may be more important determinants of learning outcomes than the teaching modality itself. Cognitively enriched formats may provide additional benefits. Further research is needed to define the optimal structure of POCUS curricula. Only one study assessed patient-centered outcomes, limiting conclusions regarding the clinical impact of educational interventions.

STUDY AIMS: The COVID-19 pandemic required healthcare systems to reorganise around patient surges. Previous evidence associated these reorganisations with worse clinical outcomes for non-COVID-19 patients, to varying degrees. This exploratory study aimed to quantify the effects of successive COVID-19 waves on mortality, length of stay and transfers to intermediate and intensive care units among non-COVID-19 patients by comparing COVID-19 and non-COVID-19 periods in a Swiss hospital. METHODS: This retrospective monocentric cohort study extracted electronic health data of patients hospitalised in a Swiss tertiary hospital from 1 January 2019 to 1 March 2023, whose primary discharge diagnosis was non-COVID-19, excluding patients from psychiatry and women-mother-child departments. Patients were then classified into COVID-19 wave periods based on the weekly average number of COVID admissions. Multivariable regressions were performed to compare in-hospital mortality, transfer rates to intermediate and intensive care units, and length of stay, adjusting for sex, age, insurance class, region of residence, level of care, Charlson comorbidity index, hospital department and main diagnosis. RESULTS: A total of 22,972 non-COVID-19 patients hospitalised during three COVID-19 waves were included and compared to 51,252 pre-COVID-19 patients, 46,753 patients in the inter-wave period and 39,844 post-COVID-19 patients. Compared to the pre-COVID-19 period, adjusted in-hospital mortality among non-COVID-19 patients increased significantly during all COVID-19 waves, peaking in the first wave (OR: 1.27, 95% CI: 1.07–1.51), and decreased during inter-wave periods (OR: 0.91, 95% CI: 0.85–0.97). Transfers to intermediate care units increased throughout the COVID-19 period and normalised post-COVID-19, whereas transfers to intensive care units decreased significantly from the second wave onwards. Compared to the pre-COVID-19 period, length of stay did not differ during the first wave but was shorter in subsequent periods. CONCLUSIONS: Worse outcomes among non-COVID-19 patients during COVID-19 waves highlight the need for protocols that ensure continuity and quality of care during future healthcare crises.

Background: Global population aging places an increasing burden on health care systems. This is driven by multimorbidity, frailty, and polypharmacy. Older adults, particularly those aged 65 years or older, use emergency departments (EDs) more frequently and experience poorer outcomes. In this population, decisions regarding admission to monitored acute care units—intensive care units, intermediate care units, and operating rooms—are frequent and complex. While ED and intensive care unit use are well documented, data on monitored acute care units as a whole remain limited. Evidence on admission trends, patient characteristics, and outcomes in older adults is scarce. Objective: This study aimed to describe temporal trends in monitored acute care unit admissions, identify predictors of such admissions, and assess outcomes following these admissions. Methods: We conducted a retrospective cohort study using routinely collected electronic health record data. We included patients aged 65 years or older who visited the EDs of the Geneva University Hospitals, Switzerland, between 2009 and 2019. The primary outcome was admission to a monitored acute care unit. The secondary outcomes were hospital length of stay, 7-day mortality, and 1-year mortality. Logistic regression models were used to identify factors associated with monitored acute care unit admission and to assess the association between age and mortality. Results: During the 10-year period, 701,838 ED visits were recorded. Annual visits increased from 56,944 to 76,368 (+34.1%). The increase was greater among patients aged 65 years or older (+56.1%) than among younger patients (+26.5%). A total of 180,189 older patients presented to the ED. Of these, 887 (0.5%) died in the ED, 97,238 (54.0%) were discharged home, 63,025 (35.0%) were admitted to a ward, and 19,039 (10.6%) were admitted to a monitored acute care unit. Monitored acute care unit admissions increased from 1379 (10.3%) in 2009 to 2240 (11.1%) in 2019. This represented an absolute increase of 62.4% and a relative increase of 0.8%. Predictors of monitored acute care unit admission included younger age, male sex, ambulance arrival, higher triage level, being married or in a relationship, not residing in a nursing home, and French as the primary language. Among patients admitted to a monitored acute care unit, mortality was 5.8% (1105/19,039) at 7 days and 22.3% (4251/18,039) at 1 year. Older age was associated with higher 7-day mortality (adjusted odds ratio 1.55, 95% CI 1.14‐2.10) and 1-year mortality (adjusted odds ratio 1.28, 95% CI 1.08‐1.51). Conclusions: Admissions to monitored acute care units among older patients increased over time. These findings indicate a growing demand for high-level care in this population. Hospitals should adapt infrastructure and resource allocation to address the needs of an aging population.

Two successive COVID-19 flares occurred in Switzerland in spring and autumn 2020. During these periods, therapeutic strategies have been constantly adapted based on emerging evidence. We aimed to describe these adaptations and evaluate their association with patient outcomes in a cohort of COVID-19 patients admitted to the hospital. Consecutive patients admitted to the Geneva Hospitals during two successive COVID-19 flares were included. Characteristics of patients admitted during these two periods were compared as well as therapeutic management including medications, respiratory support strategies and admission to the ICU and intermediate care unit (IMCU). A mutivariable model was computed to compare outcomes across the two successive waves adjusted for demographic characteristics, co-morbidities and severity at baseline. The main outcome was in-hospital mortality. Secondary outcomes included ICU admission, Intermediate care (IMCU) admission, and length of hospital stay. A total of 2′983 patients were included. Of these, 165 patients (16.3%, n = 1014) died during the first wave and 314 (16.0%, n = 1969) during the second (p = 0.819). The proportion of patients admitted to the ICU was lower in second wave compared to first (7.4 vs. 13.9%, p < 0.001) but their mortality was increased (33.6% vs. 25.5%, p < 0.001). Conversely, a greater proportion of patients was admitted to the IMCU in second wave compared to first (26.6% vs. 22.3%, p = 0.011). A third of patients received lopinavir (30.7%) or hydroxychloroquine (33.1%) during the first wave and none during second wave, while corticosteroids were mainly prescribed during second wave (58.1% vs. 9.1%, p < 0.001). In the multivariable analysis, a 25% reduction of mortality was observed during the second wave (HR 0.75; 95% confidence interval 0.59 to 0.96). Among deceased patients, 82.3% (78.2% during first wave and 84.4% during second wave) died without beeing admitted to the ICU. The proportion of patients with therapeutic limitations regarding ICU admission increased during the second wave (48.6% vs. 38.7%, p < 0.001). Adaptation of therapeutic strategies including corticosteroids therapy and higher admission to the IMCU to receive non-invasive respiratory support was associated with a reduction of hospital mortality in multivariable analysis, ICU admission and LOS during the second wave of COVID-19 despite an increased number of admitted patients. More patients had medical decisions restraining ICU admission during the second wave which may reflect better patient selection or implicit triaging.

Background: Clinical decision support systems (CDSS) can help identify drug-related problems (DRPs). However, the alert specificity remains variable. Defining more relevant alerts for detecting DRPs would improve CDSS. Aim: Develop electronic queries that assist pharmacists in conducting medication reviews and an assessment of the performance of this model to detect DRPs. Method: Electronic queries were set up in CDSS using “triggers” from electronic health records: drug prescriptions, laboratory values, medical problems, vital signs, demographics. They were based on a previous study where 315 patients admitted in internal medicine benefited from a multidisciplinary medication review (gold-standard) to highlight potential DRPs. Electronic queries were retrospectively tested to assess performance in detecting DRPs revealed with gold-standard. For each electronic query, sensitivity, specificity, positive and negative predictive value were computed. Results: Of 909 DRPs, 700 (77.8%) were used to create 366 electronic queries. Electronic queries correctly detected 77.1% of DRPs, median sensitivity and specificity reached 100.0% (IQRs, 100.0%–100.0%) and 99.7% (IQRs, 97.0%–100.0%); median positive predictive value and negative predictive value reached 50.0% (IQRs, 12.5%–100.0%) and 100.0% (IQRs, 100.0%–100.0%). Performances varied according to “triggers” (p < 0.001, best performance in terms of predictive positive value when exclusively involving drug prescriptions). Conclusion: Electronic queries based on electronic heath records had high sensitivity and negative predictive value and acceptable specificity and positive predictive value and may contribute to facilitate medication review. Implementing some of these electronic queries (the most effective and clinically relevant) in current practice will allow a better assessment of their impact on the efficiency of the clinical pharmacist.

Atypical pathogens are intracellular bacteria causing community-acquired pneumonia (CAP) in a significant minority of patients. Legionella spp., Chlamydia pneumoniae and psittaci, Mycoplasma pneumoniae, and Coxiella burnetii are commonly included in this category. M. pneumoniae is present in 5–8% of CAP, being the second most frequent pathogen after Streptococcus pneumoniae. Legionella pneumophila is found in 3–5% of inpatients. Chlamydia spp. and Coxiella burnetii are present in less than 1% of patients. Legionella longbeachae is relatively frequent in New Zealand and Australia and might also be present in other parts of the world. Uncertainty remains on the prevalence of atypical pathogens, due to limitations in diagnostic means and methodological issues in epidemiological studies. Despite differences between CAP caused by typical and atypical pathogens, the clinical presentation alone does not allow accurate discrimination. Hence, antibiotics active against atypical pathogens (macrolides, tetracyclines and fluoroquinolones) should be included in the empiric antibiotic treatment of all patients with severe CAP. For patients with milder disease, evidence is lacking and recommendations differ between guidelines. Use of clinical prediction rules to identify patients most likely to be infected with atypical pathogens, and strategies of narrowing the antibiotic spectrum according to initial microbiologic investigations, should be the focus of future investigations.

Background The SARS-CoV-2 pandemic led to a steep increase in hospital and intensive care unit (ICU) admissions for acute respiratory failure worldwide. Early identification of patients at risk of clinical deterioration is crucial in terms of appropriate care delivery and resource allocation. We aimed to evaluate and compare the prognostic performance of Sequential Organ Failure Assessment (SOFA), Quick Sequential Organ Failure Assessment (qSOFA), Confusion, Uraemia, Respiratory Rate, Blood Pressure and Age ≥65 (CURB-65), Respiratory Rate and Oxygenation (ROX) index and Coronavirus Clinical Characterisation Consortium (4C) score to predict death and ICU admission among patients admitted to the hospital for acute COVID-19 infection. Methods and analysis Consecutive adult patients admitted to the Geneva University Hospitals during two successive COVID-19 flares in spring and autumn 2020 were included. Discriminative performance of these prediction rules, obtained during the first 24 hours of hospital admission, were computed to predict death or ICU admission. We further exluded patients with therapeutic limitations and reported areas under the curve (AUCs) for 30-day mortality and ICU admission in sensitivity analyses. Results A total of 2122 patients were included. 216 patients (10.2%) required ICU admission and 303 (14.3%) died within 30 days post admission. 4C score had the best discriminatory performance to predict 30-day mortality (AUC 0.82, 95% CI 0.80 to 0.85), compared with SOFA (AUC 0.75, 95% CI 0.72 to 0.78), qSOFA (AUC 0.59, 95% CI 0.56 to 0.62), CURB-65 (AUC 0.75, 95% CI 0.72 to 0.78) and ROX index (AUC 0.68, 95% CI 0.65 to 0.72). ROX index had the greatest discriminatory performance (AUC 0.79, 95% CI 0.76 to 0.83) to predict ICU admission compared with 4C score (AUC 0.62, 95% CI 0.59 to 0.66), CURB-65 (AUC 0.60, 95% CI 0.56 to 0.64), SOFA (AUC 0.74, 95% CI 0.71 to 0.77) and qSOFA (AUC 0.59, 95% CI 0.55 to 0.62). Conclusion Scores including age and/or comorbidities (4C and CURB-65) have the best discriminatory performance to predict mortality among inpatients with COVID-19, while scores including quantitative assessment of hypoxaemia (SOFA and ROX index) perform best to predict ICU admission. Exclusion of patients with therapeutic limitations improved the discriminatory performance of prognostic scores relying on age and/or comorbidities to predict ICU admission.

Risk stratification is one of the cornerstones of the management of acute pulmonary embolism (PE) and determines the choice of both diagnostic and therapeutic strategies. The first step is the identification of patent circulatory failure, as it is associated with a high risk of immediate mortality and requires a rapid diagnosis and prompt reperfusion. The second step is the estimation of 30-day mortality based on clinical parameters (e.g., original and simplified version of the pulmonary embolism severity index): low-risk patients without right ventricular dysfunction are safely managed with ambulatory anticoagulation. The remaining group of hemodynamically stable patients, labeled intermediate-risk PE, requires hospital admission, even if most of them will heal without complications. In recent decades, efforts have been made to identify a subgroup of patients at an increased risk of adverse outcomes (intermediate-high-risk PE), who might benefit from a more aggressive approach, including reperfusion therapies and admission to a monitored unit. The cur-rent approach, combining markers of right ventricular dysfunction and myocardial injury, has an insufficient positive predictive value to guide primary thrombolysis. Sensitive markers of circulatory failure, such as plasma lactate, have shown interesting prognostic accuracy and may play a central role in the future. Furthermore, the improved security of reduced-dose thrombolysis may enlarge the indication of this treatment to selected intermediate–high-risk PE.