Early changes in S100B maternal blood levels can predict fetal intrauterine growth restriction.

OBJECTIVES: Intrauterine growth restriction (IUGR) represents one of the main causes of perinatal mortality and morbidity. Nowadays, IUGR early diagnosis is mandatory in order to limit the occurrence of multiorgan failure, especially the brain. Therefore, we investigated whether longitudinal S100B assessment in maternal blood could be a trustable predictor of IUGR. METHODS: We conducted a prospective study in 480 pregnancies (IUGR: n=40; small for gestational age, SGA: n=40; controls: n=400) in whom S100B was measured at three predetermined monitoring time-points (T1: 8-18 GA; T2: 19-23 GA; T3: 24-28 GA). RESULTS: Lower S100B in IUGR fetuses than SGA and controls (p<0.05, for all) at T1-T3. Receiver operating characteristic curve showed that S100B at T1 was the best predictor of IUGR (sensitivity: 100 %; specificity: 81.4 %) than T2, T3. CONCLUSIONS: The early lower S100B concentration in pregnant women lately complicated by IUGR support the notion that non-invasive early IUGR diagnosis and monitoring is becoming feasible. Results open the way to further studies aimed at diagnosing and monitoring fetal/maternal diseases at earliest time.

Ricerca scientifica ed educazione ambientale: l'approccio partecipativo dei progetti MAPS-MI nelle scuole di Milano.

The accumulated scientific evidence regarding the effects of air pollution on health calls for urgent and effective action to protect the most vulnerable part of the population, such as children and the elderly. In this context, the participatory approach represents a viable option to empower citizens and increase their level of awareness and participation. The involvement of civil society is a potential ally in tackling the still open research challenges. The MAPS-MI 2018-2019 Mapping air pollution in the catchment area of an elementary school of Milan and MAPS-MI 2022-2023 Mobility, environment and participation in the schools of Milan projects are here presented.The main targets of the projects are primary and middle school children, their parents and teachers, with some activities extended to the entire citizenship. Starting from the survey on parents' habits and opinions about mobility and air pollution, to the air quality and personal exposure assessment, and the field-testing and development of an environmental education module, the MAPS-MI approach aims to increase knowledge and awareness about air pollution and to involve stakeholders in experimenting practices towards change. The first results suggest that adopting a participatory approach in the fields of exposure science and environmental epidemiology is a winning choice in terms of quality research, participation and community impact.

Neural networks and hospital length of stay: an application to support healthcare management with national benchmarks and thresholds.

BACKGROUND: The problem of correct inpatient scheduling is extremely significant for healthcare management. Extended length of stay can have negative effects on the supply of healthcare treatments, reducing patient accessibility and creating missed opportunities to increase hospital revenues by means of other treatments and additional hospitalizations. METHODS: Adopting available national reference values and focusing on a Department of Internal and Emergency Medicine located in the North-West of Italy, this work assesses prediction models of hospitalizations with length of stay longer than the selected benchmarks and thresholds. The prediction models investigated in this case study are based on Artificial Neural Networks and examine risk factors for prolonged hospitalizations in 2018. With respect current alternative approaches (e.g., logistic models), Artificial Neural Networks give the opportunity to identify whether the model will maximize specificity or sensitivity. RESULTS: Our sample includes administrative data extracted from the hospital database, collecting information on more than 16,000 hospitalizations between January 2018 and December 2019. Considering the overall department in 2018, 40% of the hospitalizations lasted more than the national average, and almost 3.74% were outliers (i.e., they lasted more than the threshold). According to our results, the adoption of the prediction models in 2019 could reduce the average length of stay by up to 2 days, guaranteeing more than 2000 additional hospitalizations in a year. CONCLUSIONS: The proposed models might represent an effective tool for administrators and medical professionals to predict the outcome of hospital admission and design interventions to improve hospital efficiency and effectiveness.

Impact of septic episodes caused by Acinetobacter baumannii, Klebsiella pneumoniae and Pseudomonas aeruginosa in a tertiary hospital: clinical and economic considerations in years 2018-2020.

OBJECTIVE: To evaluate incidence, therapy and antibiotic resistance trends in septic episodes caused by three multi-drug resistant bacteria in a tertiary hospital, by also estimating their economic impact. METHODS: An observational, retrospective-cohort analysis was based on data related to patients admitted to the "SS. Antonio e Biagio e Cesare Arrigo" Hospital in Alessandria (Italy) between 2018 and 2020, that developed sepsis from multi-drug resistant bacteria of the examined species. Data were retrieved from medical records and from the hospital's management department. RESULTS: Inclusion criteria led to enrolment of 174 patients. A relative increase in A. baumannii cases (p < 0.0001) and an increasing resistance trend for K. pneumoniae (p < 0.0001) were detected in 2020 compared to 2018-2019. Most patients were treated with carbapenems (72.4%), although the use of colistin rose significantly in 2020 (62.5% vs 36%, p = 0.0005). Altogether, these 174 cases caused 3295 additional hospitalisation days (mean 19 days/patient): the consequent expenditure attained ≈ 3 million Euros, 85% of which (≈2.5 million Euros) due to the cost of extra hospital stay. Specific antimicrobial therapy accounted for 11.2% of the total (≈336,000 €). CONCLUSIONS: Healthcare-related septic episodes cause a considerable burden. Moreover, a trend could be spotted towards higher relative incidence of complex cases recently.

S100B Maternal Blood Levels in Gestational Diabetes Mellitus Are Birthweight, Gender and Delivery Mode Dependent.

Gestational Diabetes Mellitus (GDM) is one of the main causes of perinatal mortality/morbidity. Today, a parameter offering useful information on fetal central nervous system (CNS) development/damage is eagerly awaited. We investigated the role of brain-protein S100B in the maternal blood of GDM pregnancies by means of a prospective case-control study in 646 pregnancies (GDM: n = 106; controls: n = 530). Maternal blood samples for S100B measurement were collected at four monitoring time-points from 24 weeks of gestation to term. Data was corrected for gender and delivery mode and correlated with gestational age and weight at birth. Results showed higher (p < 0.05) S100B from 24 to 32 weeks and at term in GDM fetuses than controls. Higher (p < 0.05) S100B was observed in GDM male new-borns than in females from 24 to 32 weeks and at term, in GDM cases delivering vaginally than by caesarean section. Finally, S100B positively correlated with gestational age and weight at birth (R = 0.27; R = 0.37, respectively; p < 0.01). The present findings show the usefulness of S100B in CNS to monitor high-risk pregnancies during perinatal standard-of-care procedures. The results suggest that further investigations into its potential role as an early marker of CNS growth/damage in GDM population are needed.

The hospital care of patients with cancer: a retrospective analysis of the characteristics of their hospital stay in comparison with other medical conditions.

PURPOSE: Hospital admission is a frequent occurrence among patients with cancer, and a significant proportion of patients admitted to medical units have cancer. Their hospital stay has features that may be different compared with patients without cancer. We performed a retrospective analysis of the characteristics of patients with cancer admitted for medical conditions. PATIENTS AND METHODS: We studied the administrative data of patients with solid cancer admitted to the medical department of a large referral hospital over a 12-month period and compared them with those of patients without cancer. RESULTS: Seven thousand eight hundred two consecutive admissions were analysed, of which 1099 (14.1%) had a principal or associated diagnosis of cancer. Admissions were distributed across 12 units, with 44% concentrated in the medical oncology unit and 56% in other units. Patients with cancer were more frequently men and were younger than patients without cancer. Admission less frequently involved the emergency department (ED), while discharge was more frequently assisted. The in-hospital death rate was higher, as was the readmission rate. Length of stay was longer (11.3 days vs. 9.8 days; p < 0.0001). Patients with cancer admitted to the medical oncology unit used the ED even less, and their length of stay was shorter than that of patients with cancer admitted in other units. CONCLUSIONS: The in-hospital pathway of patients with cancer displays specific issues and adds complexity to hospital stay of patients with medical conditions. The medical oncology unit plays a role in reducing ED use and in providing efficient care. The evidence gathered should help in shaping new models of care and in improving adequate clinical competencies.

Organizational determinants of hospital stay: establishing the basis of a widespread action on more efficient pathways in medical units.

Given the high hospital costs, the increasing clinical complexity and the overcrowding of emergency departments, it is crucial to improve the efficiency of medical admissions. We aimed at isolating organizational drivers potentially targetable through a widespread improvement action. We studied all medical admissions in a large tertiary referral hospital from January 1st to December 31st, 2018. Data were retrieved from the administrative database. Available information included age, sex, type (urgent or elective) and Unit of admission, number of internal transfers, main ICD-9 diagnosis, presence of cancer among diagnoses, surgical or medical code, type of discharge, month, day and hour of admission and discharge. National Ministry of Health database was used for comparisons. 8099 admissions were analyzed. Urgent admissions (80.5% of the total) were responsible for longer stays and were the object of the multivariate analysis. The variables most influencing length-of-stay (LOS) were internal transfers and assisted discharge: they contributed, respectively, to 62% and 40% prolongation of LOS. Also, the daily and weekly kinetics of admission accounted for a significant amount of variation in LOS. Long admissions (≥ 30 days) accounted for the 15.5% of total bed availability. Type of discharge and internal transfers were again among the major determinants. A few factors involved in LOS strictly depend on the organizational environment and are potentially modifiable. Re-engineering should be focused on making more efficient internal and external transitions and at ensuring continuity of the clinical process throughout the day and the week.