Purpose: Complicated urinary tract infections (cUTIs) are among the most frequent health-care-associated infections. In patients with cUTI, Pseudomonas aeruginosa deserves special attention, since it can affect patients with serious underlying conditions. Our aim was to gain insight into the risk factors and prognosis of P. aeruginosa cUTIs in a scenario of increasing multidrug resistance (MDR).
Methods: This was a multinational, retrospective, observational study at 20 hospitals in south and southeastern Europe, Turkey, and Israel including consecutive patients with cUTI hospitalized between January 2013 and December 2014. A mixed-effect logistic regression model was performed to assess risk factors for P. aeruginosa and MDR P. aeruginosa cUTI. Results: Of 1,007 episodes of cUTI, 97 (9.6%) were due to P. aeruginosa. Resistance rates of P. aeruginosa were: antipseudomonal cephalosporins 35 of 97 (36.1%), aminoglycosides 30 of 97 (30.9%), piperacillin–tazobactam 21 of 97 (21.6%), fluoroquinolones 43 of 97 (44.3%), and carbapenems 28 of 97 (28.8%). The MDR rate was 28 of 97 (28.8%). Independent risk factors for P. aeruginosa cUTI were male sex (OR 2.61, 95% CI 1.60–4.27), steroid therapy (OR 2.40, 95% CI 1.10–5.27), bedridden functional status (OR 1.79, 95% CI 0.99–3.25), antibiotic treatment within the previous 30 days (OR 2.34, 95% CI 1.38–3.94), indwelling urinary catheter (OR 2.41, 95% CI 1.43–4.08), and procedures that anatomically modified the urinary tract (OR 2.01, 95% CI 1.04–3.87). Independent risk factors for MDR P. aeruginosa cUTI were age (OR 0.96, 95% CI 0.93–0.99) and anatomical urinary tract modification (OR 4.75, 95% CI 1.06–21.26). Readmission was higher in P. aeruginosa cUTI patients than in other etiologies (23 of 97 [23.7%] vs 144 of 910 [15.8%], P=0.04), while 30-day mortality was not significantly different (seven of 97 [7.2%] vs 77 of 910 [8.5%], P=0.6). Conclusion: Patients with P. aeruginosa cUTI had characteristically a serious baseline condition and manipulation of the urinary tract, although their mortality was not higher than that of patients with cUTI caused by other etiologies.

Due to population ageing and medical advances, people with advanced chronic diseases (ACD) live longer. Such patients are even more likely to face either temporary or permanent reduced functional reserve, which typically further increases their healthcare resource use and the burden of care on their caregiver(s). Accordingly, these patients and their caregiver(s) may benefit from integrated supportive care provided via digitally supported interventions. This approach may either maintain or improve their quality of life, increase their independence, and optimize the healthcare resource use from early stages. ADLIFE is an EU-funded project, aiming to improve the quality of life of older people with ACD by providing integrated personalized care via a digitally enabled toolbox. Indeed, the ADLIFE toolbox is a digital solution which provides patients, caregivers, and health professionals with digitally enabled, integrated, and personalized care, supporting clinical decisions, and encouraging independence and self-management. Here we present the protocol of the ADLIFE study, which is designed to provide robust scientific evidence on the assessment of the effectiveness, socio-economic, implementation, and technology acceptance aspects of the ADLIFE intervention compared to the current standard of care (SoC) when applied in real-life settings of seven different pilot sites across six countries. A quasi-experimental trial following a multicenter, non-randomized, non-concurrent, unblinded, and controlled design will be implemented. Patients in the intervention group will receive the ADLIFE intervention, while patients in the control group will receive SoC. The assessment of the ADLIFE intervention will be conducted using a mixed-methods approach.

Improvements in breast cancer survival rate have been achieved through a variety of multimodal therapeutic approaches, which play a key role in the patients’ healthcare pathway and their Patient-Reported Outcomes (PROs) from a Value-Based Healthcare (VBHC) perspective. This paper analyses differences in PROs of patients diagnosed with breast cancer according to their healthcare pathway. A cohort of 690 patients diagnosed with breast cancer between 2018 and 2020 at six European sites was used. PROs were assessed at baseline and 6 months using the International Consortium for Health Outcome Measures standard set. Archetypes defined by patient characteristics and treatment trajectories served as the basis for comparison. Multivariate linear regression models were used to analyse differences in PROs across archetypes. Functional scores generally worsened over 6 months, particularly in physical functioning, whereas emotional functioning improved. Archetypes undergoing mastectomy, with or without reconstruction, showed significant decreases in body image perception and satisfaction with breasts. Pain, fatigue, and peripheral symptoms were prevalent in most archetypes, with those receiving chemotherapy reporting the greatest symptom burden. Patients with in situ carcinoma and patients undergoing conservative surgery plus radiotherapy showed minimal deterioration. The use of PROs in a real-world setting enables the identification of differences across patient archetypes based on their therapeutic pathways. This information provides valuable insights for refining patient-centred care guiding VBHC strategies in oncology, developing of personalized care solutions, and facilitating Shared-Decision Making.

The value equation of value-based healthcare (VBHC) as a single figure remains ambiguous, closer to a theoretical framework than a useful tool for decision making. The challenge lies in the way patient-centred outcomes (PCOs) might be combined to produce a single value of the numerator. This paper aims to estimate the weights of PCOs to provide a single figure in the numerator, which ultimately will allow a VBHC figure to be reached. A cohort of patients diagnosed with breast cancer (n = 690) with a 6-month follow-up recruited in 2019–20 across six European hospitals was used. Patient-reported outcomes (PROs), clinical-related outcomes (CROs), and clinical and socio-demographic variables were collected. The numerator was defined as a composite indicator of the PCOs (CI-PCO), and regression analysis was applied to estimate their weights and consequently arrive at a single figure. Pain showed as the highest weight followed by physical functioning, emotional functioning, and ability to work, and then by a symptom, either arm or breast. PCOs weights were robust to sensitivity analysis. The CI-PCO value was found to be more informative than the health-related quality of life (HRQoL) value. To the best of our knowledge, this is the first research to combine the PCOs proposed by ICHOM to provide a single figure in the numerator of the value equation. This figure shows a step forward in VBHC to reach a holistic benchmarking across healthcare centres and a value-based payment. This research might also be applied in other medical conditions as a methodological pathway.