Search

Summary: Background & Aims: Diarrhea is very common in patients receiving enteral nutrition. The principle of diarrhea treatment involves implementing dietary modifications, such as reduction of the fatty component, oral and probiotic supplementations, and increase of the fiber intake, aimed at mitigating the frequency and intensity of symptoms. In this context, partially hydrolyzed guar gum (PHGG) has emerged as a potential soluble fiber maximizing the effect against GI symptoms, particularly diarrhea. Among PHGG, NOVASOURCE® GI Control is an enteral nutrition formula indicated to improve the nutritional status and intestinal symptoms in patients with (risk of) malnutrition and intestinal barrier dysfunction, or intolerance to enteral nutrition. The objective of this economic analysis was to compare costs and effects of PHGG diet (taken with NOVASOURCE® GI Control) vs standard diet (SD, without fibers), in patients who are in need of enteral nutrition, in Italy. Methods: Two different analyses were conducted to reflect the most typical settings where enteral nutrition is relevant: i) critically-ill patients admitted to the hospital for an acute, life-threatening condition; ii) medical or (post)surgical patients. A simple decision-tree analysis was developed, with some minor differences depending on the setting. Hospital perspective was used to evaluate PHGG cost-opportunity in the hospital for critically-ill patients setting, while the Italian National Health Service (NHS) to assess the product for medical or surgical patients, assuming they were predominantly treated in an outpatient setting. Health outcomes and costs of critically-ill hospitalized patients and medical or surgical patients treated in a healthcare facility were estimated over a time horizon of 20 (PHGG group) to 27 (SD arm) days and over 24 days, respectively. Results: In the critically-ill setting, the use of PHGG diet prevented ∼12 cases of diarrhea every N=100 cases treated (relative reduction: -35%). The higher acquisition costs needed for PHGG diet (+€2,992) were more than offset by savings in all the other cost items, such as costs of hospital stay, medical therapy, costs of consumables, and cost of professional care to manage diarrhea (total saving -€1,186,330). Similarly, in medical or surgical patients, the use of PHGG was found cost-saving vs SD (-€6,040), and also reduced the number of diarrhea cases (relative reduction: -60%). Conclusions: The conducted economic analysis provides confidence that PHGG is a valuable and economically sustainable asset. Its utilization ensures not only adequate nutrition but also proves effective in mitigating diarrhea, thereby improving quality of life and limiting complication costs.

Capitalizing on the widespread adoption of smartphones among farmers and the application of artificial intelligence in computer vision, a variety of mobile applications have recently emerged in the agricultural domain. This paper introduces GranoScan, a freely available mobile app accessible on major online platforms, specifically designed for the real-time detection and identification of over 80 threats affecting wheat in the Mediterranean region. Developed through a co-design methodology involving direct collaboration with Italian farmers, this participatory approach resulted in an app featuring: (i) a graphical interface optimized for diverse in-field lighting conditions, (ii) a user-friendly interface allowing swift selection from a predefined menu, (iii) operability even in low or no connectivity, (iv) a straightforward operational guide, and (v) the ability to specify an area of interest in the photo for targeted threat identification. Underpinning GranoScan is a deep learning architecture named efficient minimal adaptive ensembling that was used to obtain accurate and robust artificial intelligence models. The method is based on an ensembling strategy that uses as core models two instances of the EfficientNet-b0 architecture, selected through the weighted F1-score. In this phase a very good precision is reached with peaks of 100% for pests, as well as in leaf damage and root disease tasks, and in some classes of spike and stem disease tasks. For weeds in the post-germination phase, the precision values range between 80% and 100%, while 100% is reached in all the classes for pre-flowering weeds, except one. Regarding recognition accuracy towards end-users in-field photos, GranoScan achieved good performances, with a mean accuracy of 77% and 95% for leaf diseases and for spike, stem and root diseases, respectively. Pests gained an accuracy of up to 94%, while for weeds the app shows a great ability (100% accuracy) in recognizing whether the target weed is a dicot or monocot and 60% accuracy for distinguishing species in both the post-germination and pre-flowering stage. Our precision and accuracy results conform to or outperform those of other studies deploying artificial intelligence models on mobile devices, confirming that GranoScan is a valuable tool also in challenging outdoor conditions.

Abstract Objective NPRL3‐related epilepsy (NRE) is an emerging condition set within the wide GATOR‐1 spectrum with a particularly heterogeneous and elusive phenotypic expression. Here, we delineated the genotype–phenotype spectrum of NRE, reporting an illustrative familial case and reviewing pertinent literature. Methods Through exome sequencing (ES), we investigated a 12‐year‐old girl with recurrent focal motor seizures during sleep, suggestive of sleep‐related hypermotor epilepsy (SHE), and a family history of epilepsy in siblings. Variant segregation analysis was performed by Sanger sequencing. All previously published NRE patients were thoroughly reviewed and their electroclinical features were analyzed and compared with the reported subjects. Results In the proband, ES detected the novel NPRL3 frameshift variant (NM_001077350.3): c.151_152del (p.Thr51Glyfs*5). This variant is predicted to cause a loss of function and segregated in one affected brother. The review of 76 patients from 18 publications revealed the predominance of focal‐onset seizures (67/74–90%), with mainly frontal and frontotemporal (32/67–47.7%), unspecified (19/67–28%), or temporal (9/67–13%) onset. Epileptic syndromes included familial focal epilepsy with variable foci (FFEVF) (29/74–39%) and SHE (11/74–14.9%). Fifteen patients out of 60 (25%) underwent epilepsy surgery, 11 of whom achieved complete seizure remission (11/15–73%). Focal cortical dysplasia (FCD) type 2A was the most frequent histopathological finding. Significance We reported an illustrative NPRL3‐related epilepsy (NRE) family with incomplete penetrance. This condition consists of a heterogeneous spectrum of clinical and neuroradiological features. Focal‐onset motor seizures are predominant, and almost half of the cases fulfill the criteria for SHE or FFEVF. MRI‐negative cases are prevalent, but the association with malformations of cortical developments (MCDs) is significant, especially FCD type 2a. The beneficial impact of epilepsy surgery in patients with MCD‐related epilepsy further supports the inclusion of brain MRI in the workup of NRE patients.

Summary: Background & Aims: This systematic review and meta-analysis aims to evaluate the effects on mortality, length of stay in hospital (HLOS) and in intensive care unit (ICU-LOS) of early enteral nutrition (EEN) vs. late enteral nutrition (LEN) on COVID-19 patients in U.S. hospitals. Based on results, we estimated the cost differences between EEN and LEN. Methods: Searches were conducted in databases, including Web of Science, Pubmed and Embase until 28 December 2022. Two reviewers independently screened studies for eligibility, extracted data, and assessed risk of bias. We included randomized controlled trials, prospective and retrospective observational studies which compared EEN and LEN in COVID-19 critically ill adult patient in ICU. Results: We selected 4 studies reporting a timing of EEN varying from 24-72h since patient admission in ICU. For EEN initiated within 72h, the results do not support an effect on mortality with a risk ratio of 0.97 (95% CI, 0.83, 1.14, p = 0.74), while showing an effect on both HLOS and ICU-LOS with a mean difference of respectively -3.54 days (95% CI, -4.85, -2.22, p < 0.00001) and -6.35 days (95% CI, -8.12, -4.57, p =0.00001). The sensitivity analysis confirmed the results also for EEN initiated within 36h. Compared to LEN, we estimated that EEN can lead to substantial cost reduction, $21,525 with EEN

Crop models fed by seasonal forecasts to deliver yield forecasts are becoming a valuable tool to tackle food production shocks and food price spikes triggered by climate change and extreme events. However, to what extent seasonal climate prediction can be coupled to crop models in an effective climate service to provide durum wheat yield forecasting at local, regional and national scales remains unknown. Within the H2020 MED-GOLD project, based on participatory action research and through a co-designing approach, a complete assessment of raw and bias-adjusted ECMWF-System5 seasonal forecasts data in feeding the Delphi model was performed and explicitly compared with a previous version of the Delphi model fed by a historical scenario, both benchmarked with yield observation data. The 5 and 3-months lead prediction accuracies of year-to-year variations in durum wheat yield in Italy for 31 crop years were explored and evaluated for which techniques to remove biases from input data to adopt and for which areas they performed better. The raw seasonal forecast (BC0) showed better yield forecasting correlation than the historical scenarios (0.42 vs 0.17) in southern Italy, but not better accuracy (53 % for both), while a first bias-adjusted seasonal forecast (BC1) had again a positive effect in terms of correlation (r = 0.43) especially in southern Italy and generally in terms of accuracy (59 %). Finally, by the implementation of a second bias-adjusted seasonal forecast (BC2) the best yield prediction system was reached, especially for the areas of central and southern Italy with a total accuracy of 62 % and r = 0.52.

Mark Nuijten,1 Livia Dainelli,2 Bahareh Rasouli,3 Krysmaru Araujo Torres,4 Moreno Perugini,5 Agnieszka Marczewska2 1Health Economics and Valuation, A2M, Amsterdam, the Netherlands; 2Global Market Access & Pricing, Nestlé Health Science, Vevey, Switzerland; 3Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; 4Medical Affairs, US Nestlé Health Science, Bridgewater, MA, USA; 5Commercial and Medical Affairs, Pharmaceuticals, Nestlé Health Science, Bridgewater, MA, USACorrespondence: Mark Nuijten Email mark@a2m.nlBackground: Obesity is a disease associated with high direct medical costs and high indirect costs resulting from productivity loss. The high prevalence of obesity generates the need for payers to identify cost-effective weight loss approaches. Among various weight management techniques, the OPTI (Optifast®) program is a clinically recognised total meal replacement diet that can lead to significant weight loss and reduction in complications. This study’s objective is to assess OPTI program’s cost-effectiveness in Switzerland in comparison to “no intervention” and pharmacotherapy.Methods: An event-driven decision-analytic model was used to estimate the payer’s cost savings through the reimbursement of OPTI program over a 1-year period as well as a lifetime in Switzerland. The analysis was performed on a broad population of people with obesity with a body mass index (BMI) higher than 30 kg/m2 following the OPTI program vs two comparators (liraglutide and “no intervention”). The model incorporated a higher risk of complications due to an increased BMI and their related healthcare costs. Data sources included published literature, clinical trials, official Swiss price/tariff lists and national population statistics. The primary perspective was that of a Swiss payer. Scenario analyses – for example, for patients with existing complications (such as myocardial infarction, stroke, type 2 diabetes mellitus) or severe obesity – were conducted to test the robustness of the results.Results: The OPTI program results in cost savings of CHF 20,886 (€ 18,724) and CHF 15,382 (€ 13,790) per person compared with “no intervention” and liraglutide 3 mg, respectively. In addition, OPTI program led to 1.133 and 0.734 quality-adjusted life years (QALYs) gained respectively against its comparators. Scenario analyses showed similar outcomes with cost savings and QALYs gained.Conclusion: OPTI program is a dominant strategy compared to “no intervention” and liraglutide 3 mg as it leads to both cost savings and QALY gain. Therefore, reimbursing the OPTI program for patients with obesity would be cost-effective for Swiss payers.Keywords: obesity, cost-effectiveness, OPTI program, total meal replacement

A novel method for improving plant disease classification, a challenging and time-consuming process, is proposed. First, using as baseline EfficientNet, a recent and advanced family of architectures having an excellent accuracy/complexity trade-off, we have introduced, devised, and applied refined techniques based on transfer learning, regularization, stratification, weighted metrics, and advanced optimizers in order to achieve improved performance. Then, we go further by introducing adaptive minimal ensembling, which is a unique input to the knowledge base of the proposed solution. This represents a leap forward since it allows improving the accuracy with limited complexity using only two EfficientNet-b0 weak models, performing ensembling on feature vectors by a trainable layer instead of classic aggregation on outputs. To the best of our knowledge, such an approach to ensembling has never been used before in literature. Our method was tested on PlantVillage, a public reference dataset used for benchmarking models' performances for crop disease diagnostic, considering both its original and augmented versions. We noticeably improved the state of the art by achieving 100% accuracy in both the original and augmented datasets. Results were obtained using PyTorch to train, test, and validate the models; reproducibility is granted by providing exhaustive details, including hyperparameters used in the experimentation. A Web interface is also made publicly available to test the proposed methods.

Since 2010, more and more farmers have been using remote sensing data from unmanned aerial vehicles, which have a high spatial–temporal resolution, to determine the status of their crops and how their fields change. Imaging sensors, such as multispectral and RGB cameras, are the most widely used tool in vineyards to characterize the vegetative development of the canopy and detect the presence of missing vines along the rows. In this study, the authors propose different approaches to identify and locate each vine within a commercial vineyard using angled RGB images acquired during winter in the dormant period (without canopy leaves), thus minimizing any disturbance to the agronomic practices commonly conducted in the vegetative period. Using a combination of photogrammetric techniques and spatial analysis tools, a workflow was developed to extract each post and vine trunk from a dense point cloud and then assess the number and position of missing vines with high precision. In order to correctly identify the vines and missing vines, the performance of four methods was evaluated, and the best performing one achieved 95.10% precision and 92.72% overall accuracy. The results confirm that the methodology developed represents an effective support in the decision-making processes for the correct management of missing vines, which is essential for preserving a vineyard’s productive capacity and, more importantly, to ensure the farmer’s economic return.

Acute Respiratory Distress Syndrome (ARDS) caused by COVID-19 is substantially different from ARDS caused by other diseases and its treatment is dissimilar and challenging. As many studies showed conflicting results regarding the use of Non-invasive ventilation in COVID-19-associated ARDS, no unquestionable indications by operational guidelines were reported. The aim of this study was to estimate the use and success rate of Helmet (h) Continuous Positive Airway Pressure (CPAP) in COVID-19-associated ARDS in medical regular wards patients and describe the predictive risk factors for its use and failure. In our monocentric retrospective observational study, we included patients admitted for COVID-19 in medical regular wards. hCPAP was delivered when supplemental conventional or high-flow nasal oxygen failed to achieve respiratory targets. The primary outcomes were hCPAP use and failure rate (including the need to use Bilevel (BL) PAP or oro-tracheal intubation (OTI) and death during ventilation). The secondary outcome was the rate of in-hospital death and OTI. We computed a score derived from the factors independently associated with hCPAP failure. Out of 701 patients admitted with COVID-19 symptoms, 295 were diagnosed with ARDS caused by COVID-19 and treated with hCPAP. Factors associated with the need for hCPAP use were the PaO2/FiO2 ratio < 270, IL-6 serum levels over 46 pg/mL, AST > 33 U/L, and LDH > 570 U/L; age > 78 years and neuropsychiatric conditions were associated with lower use of hCPAP. Failure of hCPAP occurred in 125 patients and was associated with male sex, polypharmacotherapy (at least three medications), platelet count < 180 × 109/L, and PaO2/FiO2 ratio < 240. The computed hCPAP-f Score, ranging from 0 to 11.5 points, had an AUC of 0.74 in predicting hCPAP failure (significantly superior to Call Score), and 0.73 for the secondary outcome (non-inferior to IL-6 serum levels). In conclusion, hCPAP was widely used in patients with COVID-19 symptoms admitted to medical regular wards and developing ARDS, with a low OTI rate. A score computed combining male sex, multi-pharmacotherapy, low platelet count, and low PaO2/FiO2 was able to predict hCPAP failure in hospitalized patients with ARDS caused by COVID-19.

Abstract Following publication of the original article [1], the authors reported an error in Table 1.

Abstract Background Unhealthy diet is a risk factor for adverse health outcomes. Reformulation of processed foods has the potential to improve population diet, but evidence of its impact is limited. The purpose of this review was to explore the impact of reformulation on nutrient intakes, health outcomes and quality of life; and to evaluate the quality of modelling studies on reformulation interventions. Methods A systematic review of peer-reviewed articles published between January 2000 and December 2017 was performed using MEDLINE, ScienceDirect, Embase, Scopus, Cochrane, and the Centre for Reviews and Dissemination of the University of York. Additional studies were identified through informal searches on Google and specialized websites. Only simulation studies modelling the impact of food reformulation on nutrient intakes and health outcomes were included. Included articles were independently extracted by 2 reviewers using a standardized, pre-piloted data form, including a self-developed tool to assess study quality. Results A total of 33 studies met the selected inclusion criteria, with 20, 5 and 3 studies addressing sodium, sugar and fats reformulation respectively, and 5 studies addressing multiple nutrients. Evidence on the positive effects of reformulation on consumption and health was stronger for sodium interventions, less conclusive for sugar and fats. Study features were highly heterogeneous including differences in methods, the type of policy implemented, the extent of the reformulation, and the spectrum of targeted foods and nutrients. Nonetheless, partial between-study comparisons show a consistent relationship between percentages reformulated and reductions in individual consumption. Positive results are also shown for health outcomes and quality of life measures, although comparisons across studies are limited by the heterogeneity in model features and reporting. Study quality was often compromised by short time-horizons, disregard of uncertainty and time dependencies, and lack of model validation. Conclusions Reformulation models highlight relevant improvements in diets and population health. While models are valuable tools to evaluate reformulation interventions, comparisons are limited by non-homogeneous designs and assumptions. The use of validated models and extensive scenario analyses would improve models’ credibility, providing useful insights for policy-makers. Review Registration A research protocol was registered within the PROSPERO database (ID number CRD42017057341).

New onset type 1 diabetes mellitus is an uncommon but possible complication triggered by SARSCoV- 2 infection. Metabolic inflammation supported by cytokine storm leading to pancreatic beta cells destruction is the most probable link between COVID-19 and diabetes. Here, we describe the case of a 51-year-old female suffering from Hashimoto thyroiditis, who came to our attenction for new onset polyuria-polydipsia syndrome associated to hyperglycemia after a mild form of COVID- 19 recognized two months before and already recovered. Type 1 diabetes was diagnosed.

The burden of end of life in Internal Medicine wards is not neglegible. However, literature evidence about end of life care in Internal Medicine wards lacks. Therefore, the aim of this study was to report on end of life management in a Internal Medicine ward. We performed a retrospective study focusing on characteristics and management of patients consecutively died in an italian Internal Medicine ward between 2018, July-1 and 2019, June-30. Demographic, co-morbidity, pharmacological treatment at hospital admission and in the last 48- hours of life and procedures during hospital stay were collected. Study population was composed by 354 patients (190 females), corresponding to about ten percent of patients admitted in the ward, with mean age ± DS 83.5 ± 10.6 years. Eighty-four percent of deaths was exepected in the last 48 hours before exitus. The main co-morbidities were blood hypertension (66.3 %), solid or haematological malignancies (40.3%), arhythmias (34.7%), pressure ulcers (31.3%) and diabetes (27.4%). The main causes of hospitalization were infectious diseases (23.1%) and cardiac or respiratory failure (20.9%). In seven percent of patients palliative cares had been already activated before the hospital admission. No patient had written living wills or advance directives. In the last 48 hours of life, the main phramacological classes prescribed were opioids (63.2%), antibiotics (46.9%) and corticosteroids (46.3%). Compared with pharmacological classes prescribed at hospital admission, in the last 48 hours of life the prescription of antibiotics, corticosteroids, opioids and benzodiazepines was significantly increased, whereas the prescription of antihypertensive agents, proton pump inhibitors and antithrombotic drugs resulted significantly reduced. Written order to withdrawal of vital parameters relevation or active treatment were found in 30.7% and 31.9%, respectively. In the last 48 hours of life, 61% of patients underwent to at least one blood assay, 34% arterial blood gas analysis and about 35% at least one of radiography, computer tomography, magnetic resonance or endoscopy. During hospital stay 9% of patients underwent to blood transfusion. Of them 28.1% of patients received blood transfusion in the last 48 hours of life. Appropriate management of end of life represents a challenge in Internal Medicine wards.

BACKGROUND:Because of a lack of preference-based health-related quality of life (HRQoL) instruments suitable for infants aged 0-12 months, we previously developed the Infant QoL Instrument (IQI). The present study aimed to generate an algorithm to estimate utilities for the IQI. METHODS:Via an online survey, respondents from the general population and primary caregivers from China-Hong Kong, the UK, and the USA were presented 10 discrete choice scenarios based on the IQI classification system. An additional sample of respondents from the general population were also asked if they considered the examined health states to be worse than death. Coefficients for the IQI item levels were obtained with a conditional logit model based on the responses of the primary caregivers for IQI states only. These coefficients were then normalized using the rank-ordered logit model based on the responses from the general population who assessed "death" as a choice option. In this way, the values were rescaled from full health (1.0) to death (0.0), and consequently, they became suitable for the computation of quality-adjusted life years. RESULTS:The total sample consisted of 1409 members of the general population and 1229 primary caregivers. Results indicated that, out of the 7 IQI items ("sleeping," "feeding," "breathing," "stooling/poo," "mood," "skin," and "interaction"), "breathing" had the highest impact on the HRQoL of infants. Moreover, except for "stooling," all item levels were statistically significant. The general population sample considered none of the health states as worse than death. The utility value for the worst health state was 0.015 (State 4444444). CONCLUSIONS:The IQI is the first generic instrument to assess overall HRQoL in 0-1-year-old infants by providing values and utilities. Using discrete choice experiments, we demonstrated that it is possible to derive utilities of infant health states. The next step will be to collect IQI values in a clinical population of infants and to compare these values with those of other instruments.

Livia Dainelli,1 Alberto Prieto-Patron,1 Irma Silva-Zolezzi,1 Sandra G Sosa-Rubi,2 Salvador Espino y Sosa,3 Enrique Reyes-Muñoz,4 Ruy Lopez-Ridaura,5 Patrick Detzel1 1Nestlé Research Center, Lausanne, Switzerland; 2Health Economics Department, National Institute of Public Health, Cuernavaca, Morelos, Mexico; 3Clinical Research Branch, National Institute of Perinatology Isidro Espinosa de los Reyes, Mexico City, CDMX, Mexico; 4Endocrinology Department, National Institute of Perinatology Isidro Espinosa de los Reyes, Mexico City, CDMX, Mexico; 5Center for Research on Population Health, National Institute of Public Health, Cuernavaca, Morelos, Mexico Purpose: To identify the most common practices implemented for the screening and treatment of gestational diabetes mellitus (GDM) and to estimate the GDM clinician-reported proportion as a proxy of the incidence in Mexico. Materials and methods: Three hundred fifty-seven physicians in four major cities were asked about their practices regarding GDM screening, treatment, clinical exams, and health care staff involved in case of GDM diagnosis, as well as the percentage of women with GDM they care for. Data management and statistical analyses were done with Stata 13. Results: The overall GDM clinician-reported proportion was 23.7%. Regional differences were expected and consistent with the data on the epidemiology of the obesity in the country. The most common screening test was the oral glucose tolerance test 75 g one step (46.6% of total cases). Diet and exercise were sufficient to treat GDM in 40.6% of cases; the rest of the sample relied on some form of medication, especially oral hypoglycemic agents (63.0% of cases), insulin (22.0%), or a combination of these (13.0%). To educate women on how to measure glycemia and eventually take medications, an average of 2–3 hours were necessary. The three most common prenatal screening tests were the “no stress”, the “Doppler ultrasound”, and the “biophysical profile”, respectively, taken at least once by 70%, 60%, and 45% of women. Among women who were prescribed insulin, only 37% managed to keep the initial prescribed dose during the whole pregnancy. Conclusion: The survey confirmed the expected incidence and gave interesting results on the treatment of GDM. The current Mexican guidelines seem to have been partially implemented in practice, and a coherent national strategy for GDM is still missing. More studies are encouraged to investigate this topic, with the aim to better understand the importance of the monetary cost of GDM, which is currently underestimated. Keywords: GDM incidence, pharmacological treatment, prenatal test

Abstract Background The incidence of Gestational Diabetes Mellitus (GDM) is rising in all developed countries. This study aimed at assessing the short-term economic burden of GDM from the Italian healthcare system perspective. Methods A model was built over the last pregnancy trimester (i.e., from the 28th gestational week until childbirth included). The National Hospital Discharge Database (2014) was accessed to estimate delivery outcome probabilities and inpatient costs in GDM and normal pregnancies (i.e., euglycemia). International Classification of Disease-9th Revision-Clinical Modification (ICD9-CM) diagnostic codes and Diagnosis-Related Group (DRG) codes were used to identify GDM cases and different types of delivery (i.e., vaginal or cesarean) within the database. Neonatal outcomes probabilities were estimated from the literature and included macrosomia, hypoglycemia, hyperbilirubinemia, shoulder dystocia, respiratory distress, and brachial plexus injury. Additional data sources such as regional documents, official price and tariff lists, national statistics and expert opinion were used to populate the model. The average cost per case was calculated at national level to estimate the annual economic burden of GDM. One-way sensitivity analyses and Monte Carlo simulations were performed to quantify the uncertainty around base case results. Results The amount of pregnancies complicated by GDM in Italy was assessed at 54,783 in 2014 using a prevalence rate of 10.9%. The antenatal outpatient cost per case was estimated at €43.7 in normal pregnancies compared to €370.6 in GDM patients, which is equivalent to a weighted sum of insulin- (14%; €1034.6) and diet- (86%; €262.5) treated women’s costs. Inpatient delivery costs were assessed at €1601.6 and €1150.3 for euglycemic women and their infants, and at €1835.0 and €1407.7 for GDM women and their infants, respectively. Thus, the overall cost per case difference between GDM and normal pregnancies was equal to €817.8 (+ 29.2%), resulting in an economic burden of about €44.8 million in 2014 at national level. Probabilistic sensitivity analysis yielded a cost per case difference ranging between €464.9 and €1164.8 in 80% of simulations. Conclusions The economic burden of GDM in Italy is substantial even accounting for short-term medical costs only. Future research also addressing long-term consequences from a broader societal perspective is recommended.