Artificial intelligence (AI) has the potential to enhance clinical decision-making, including in infectious diseases. By improving antimicrobial resistance prediction and optimizing antibiotic prescriptions, these technologies may support treatment strategies and address critical gaps in healthcare. This study evaluates the effectiveness of AI in guiding appropriate antibiotic prescriptions for infectious diseases through a systematic literature review.

We conducted a systematic review of studies evaluating AI (machine learning or large language models) used for guidance on prescribing appropriate antibiotics in infectious disease cases. Searches were performed in PubMed, CINAHL, Embase, Scopus, Web of Science, and Google Scholar for articles published up to October 25, 2024. Inclusion criteria focused on studies assessing the performance of AI in clinical practice, with outcomes related to antimicrobial management and decision-making.

Seventeen studies used machine learning as part of clinical decision support systems (CDSS). They improved prediction of antimicrobial resistance and optimized antimicrobial use. Six studies focused on large language models to guide antimicrobial therapy; they had higher prescribing error rates, patient safety risks, and needed precise prompts to ensure accurate responses.

AI, particularly machine learning integrated into CDSS, holds promise in enhancing clinical decision-making and improving antimicrobial management. However, large language models currently lack the reliability required for complex clinical applications. The indispensable role of infectious disease specialists remains critical for ensuring accurate, personalized, and safe treatment strategies. Rigorous validation and regular updates are essential before the successful integration of AI into clinical practice.

Antimicrobial resistance (AMR) renders many bacterial infections untreatable and results in substantial morbidity and mortality worldwide. Understanding antibiotic use in clinical settings including hospitals is critical to optimize antibiotic use and prevent resistance.

Hospital antibiotic point prevalence survey (PPS).

The study was conducted in two large, teaching hospitals in Addis Ababa, Ethiopia. We performed two survey rounds in December 2021 and January 2022 through real-time chart review using the World Health Organization PPS methodology. Data were collected using a web-based database, and descriptive statistics were performed to analyze antibiotic use by various characteristics.

Among 1020 hospitalized patients, 318 (32%) were ≤14 years and 370 (36%) had surgery during the current hospitalization. A total of 662 (65%) were receiving an antibiotic on the day of survey and 346 (39%) were receiving ≥2 antibiotics. A community-acquired infection (43%) was the most common indication for an antibiotic followed by surgical prophylaxis (27%) and hospital-acquired infection (23%). Antibiotic use was highest among those ≤24 months in age and among patients in trauma, surgical, and pediatric wards. Cephalosporin (42%) and penicillin (16%) antibiotics were the most frequently prescribed classes. Only 11% of patients on antibiotics had samples collected for microbiological testing; hence, almost all antibiotic therapy was empiric.

Despite global and national efforts to improve antimicrobial stewardship, antibiotic use remains high in urban teaching hospitals in Ethiopia. Implementation of antimicrobial stewardship activities and microbiology utilization are needed to guide antimicrobial selection and curtail antibiotic overuse.

Domestic violence is a major public health problem. The situation is alarming in Arab countries: the prevalence of domestic violence is 39.3% in Saudi Arabia, 55% in Morocco and 62.2% in Egypt.

In Tunisia, a national survey carried out by the national family planning office in 2010, published in July 2011, drew attention for the first time to the frequency of this phenomenon in Tunisia and the recurrent nature of this form of violence. Unfortunately, few studies have focused on domestic violence during pregnancy and its impact on the mental health of expectant mothers.

To study the prevalence of domestic violence during pregnancy among Tunisian women consulting in the context of medical expertise and its association with anxiety.

Our study was descriptive and analytical cross-sectional, carried out with women examined in the context of medical expertise following domestic violence at ‘Hedi Chaker hospital’,Sfax , from May 2021 until January 2022.

An anonymous survey was asked to these ladies, it included a section for collecting socio-demographic data.

The HADS questionnaire was used to screen for anxiety.

122 responses was collected. The average age of victims was 35.66 ± 9.94 years.

All the women in our population study were married, and each one was a victim of at least one form of violence. The majority (86.1%) had children. Most of them had secondary (44.3%) or university (31.1%) level education.

More than half of the women (63.9%) had no occupation.

Sixty-five women (53.3%) were assaulted during pregnancy, 43% of whom suffered from complications of varying severity.

Different consequences on pregnancy were reported with decreasing prevalence: 16.9% hospitalization in a gynecological ward, 13.8% abortion, 6.2% fetal death in utero and premature delivery in 4.6% of cases.

According to the HADS, seventy-six of women surveyed (62.3%) had anxiety symptoms.

Anxiety was significantly associated with exposure to violence during pregnancy (p=0.03).

Our results showed a significant incidence of domestic violence during pregnancy and a significant association with anxiety.

Different actions must be taken towards these anxious women such as: Identify a “referent” in maternity wards to screen for domestic violence and directing women to structures and shelters that can help and, above all, protect them.

None Declared

Type 1 diabetes mellitus (T1DM) patients are treated via insulin which could result in weight gain. Studies have coined a new term, “Diabulimia” which refers to the limitation or skipping of insulin doses, with the objective of weight control. A previous meta-analysis has found that eating disorders (ED) are significantly associated with T1DM (Mannucci, E et al. J Endocrinol Invest 2005; 417-9), while a more recent one, has shown an insignificant association between ED and T1DM on analysis of diabetes-adapted questionnaires only (Young V, et al. Diabet Med. 2013:189-198)

We aimed to re-analyze the association between ED and T1DM, whilst taking into account recently published literature and the type of questionnaire utilized.

A literature search of PubMed, Scopus, and Web of Science was conducted on 17th January 2023, using the key terms “ T1DM”, “Eating Disorders”, and “ Bulimia”. Only Observational controlled studies were included.

T1DM was associated with increased risk of ED compared to non-diabetic individuals (RR = 2.47, 95% CI = 1.84 to 3.32, p-value < 0.00001), especially bulimia nervosa (RR = 2.80, 95% CI = 1.18 to 6.65, p-value = 0.02) and binge eating (RR = 1.53, 95% CI = 1.18 to 1.98, p-value = 0.001), while no significant association was seen between T1DM and anorexia nervosa. Our sensitivity analysis has shown that increased risk of ED among T1DM persisted regardless of the questionnaire used to diagnose ED; DM-validated questionnaires (RR = 2.80, 95% CI = 1.91 to 4.12, p-value <0.00001) and generic questionnaires (RR = 2.03, 95% CI = 1.27 to 3.23, p-value = 0.003). Furthermore, the Eating Attitudes Test-26 (EAT) showed a significant increase in the dieting subscale (MD = 2.95, 95% CI = 1.84 to 4.06, p-value < 0.00001) and bulimia subscale (MD = 0.78, 95% CI = 0.12 to 1.44, p-value = 0.02) among T1DM patients. Additionally, the Bulimic Investigatory Test, Edinburg (BITE) showed a significant increase in the symptom subscale (MD = 0.31, 95% CI = 0.12 to 0.50, p-value = 0.001), however, no significant difference was detected between T1DM and controls in the severity subscale. Prevalence of insulin omission/misuse was 10.3% (95% CI = 8.1-13); diabetic females demonstrated significantly higher risk of insulin omission (RR = 14.21, 95% CI = 2.66 to 76.04, p-value = 0.002) and insulin misuse (RR = 6.51, 95% CI = 1.14 to 37.31, p-value = 0.04) compared with diabetic males. Analysis of other potentially unhealthy weight control behaviors showed insignificant associations between fasting, excessive exercise, dieting pills misuse, diuretics misuse, and T1DM.

T1DM patients are at higher risk of developing ED according to both generic and diabetes-validated questionnaires. Moreover, female diabetics are at higher risk of insulin misuse/omission. Subsequently, patients should be regularly screened and early psychiatric management is warranted.

None Declared

Early detection of ST-segment elevation myocardial infarction (STEMI) on the prehospital electrocardiogram (ECG) improves patient outcomes. Current software algorithms optimize sensitivity but have a high false-positive rate. The authors propose an algorithm to improve the specificity of STEMI diagnosis in the prehospital setting.

A dataset of prehospital ECGs with verified outcomes was used to validate an algorithm to identify true and false-positive software interpretations of STEMI. Four criteria implicated in prior research to differentiate STEMI true positives were applied: heart rate <130, QRS <100, verification of ST-segment elevation, and absence of artifact. The test characteristics were calculated and regression analysis was used to examine the association between the number of criteria included and test characteristics.

There were 44,611 cases available. Of these, 1,193 were identified as STEMI by the software interpretation. Applying all four criteria had the highest positive likelihood ratio of 353 (95% CI, 201-595) and specificity of 99.96% (95% CI, 99.93-99.98), but the lowest sensitivity (14%; 95% CI, 11-17) and worst negative likelihood ratio (0.86; 95% CI, 0.84-0.89). There was a strong correlation between increased positive likelihood ratio (r2 = 0.90) and specificity (r2 = 0.85) with increasing number of criteria.

Prehospital ECGs with a high probability of true STEMI can be accurately identified using these four criteria: heart rate <130, QRS <100, verification of ST-segment elevation, and absence of artifact. Applying these criteria to prehospital ECGs with software interpretations of STEMI could decrease false-positive field activations, while also reducing the need to rely on transmission for physician over-read. This can have significant clinical and quality implications for Emergency Medical Services (EMS) systems.

Major depressive disorder (MDD) contributes to suicide risk. Treating MDD effectively is considered a key suicide prevention intervention. Yet many patients with MDD do not respond to their initial medication and require a ‘next-step’. The relationship between next-step treatments and suicidal thoughts and behaviors is uncharted.

The VA Augmentation and Switching Treatments for Depression trial randomized 1522 participants to one of three next-step treatments: Switching to Bupropion, combining with Bupropion, and augmenting with Aripiprazole. In this secondary analysis, features associated with lifetime suicidal ideation (SI) and attempts (SA) at baseline and current SI during treatment were explored.

Compared to those with SI only, those with lifetime SI + SA were more likely to be female, divorced, or separated, unemployed; and to have experienced more childhood adversity. They had a more severe depressive episode and were more likely to respond to ‘next-step’ treatment. The prevalence of SI decreased from 46.5% (694/1492) at baseline to 21.1% (315/1492) at end-of-treatment. SI during treatment was associated with baseline SI; low positive mental health, more anxiety, greater severity and longer duration of current MDD episode; being male and White; and treatment with S-BUP or C-BUP as compared to A-ARI.

SI declines for most patients during next-step medication treatments. But about 1 in 5 experienced emergent or worsening SI during treatment, so vigilance for suicide risk through the entire 12-week acute treatment period is necessary. Treatment selection may affect the risk of SI.

We performed a systematic literature review and meta-analysis on the effectiveness of coronavirus disease 2019 (COVID-19) vaccination against post-COVID conditions (long COVID) among fully vaccinated individuals.

Systematic literature review/meta-analysis.

We searched PubMed, Cumulative Index to Nursing and Allied Health, EMBASE, Cochrane Central Register of Controlled Trials, Scopus, and Web of Science from December 1, 2019, to June 2, 2023, for studies evaluating the COVID-19 vaccine effectiveness (VE) against post-COVID conditions among fully vaccinated individuals who received two doses of COVID-19 vaccine. A post-COVID condition was defined as any symptom that was present four or more weeks after COVID-19 infection. We calculated the pooled diagnostic odds ratio (DOR) (95% confidence interval) for post-COVID conditions between fully vaccinated and unvaccinated individuals. Vaccine effectiveness was estimated as 100% x (1-DOR).

Thirty-two studies with 775,931 individuals evaluated the effect of vaccination on post-COVID conditions, of which, twenty-four studies were included in the meta-analysis. The pooled DOR for post-COVID conditions among fully vaccinated individuals was 0.680 (95% CI: 0.523–0.885) with an estimated VE of 32.0% (11.5%–47.7%). Vaccine effectiveness was 36.9% (23.1%–48.2%) among those who received two doses of COVID-19 vaccine before COVID-19 infection and 68.7% (64.7%–72.2%) among those who received three doses before COVID-19 infection. The stratified analysis demonstrated no protection against post-COVID conditions among those who received COVID-19 vaccination after COVID-19 infection.

Receiving a complete COVID-19 vaccination prior to contracting the virus resulted in a significant reduction in post-COVID conditions throughout the study period, including during the Omicron era. Vaccine effectiveness demonstrated an increase when supplementary doses were administered.

Cost-effective treatments are needed to reduce the burden of depression. One way to improve the cost-effectiveness of psychotherapy might be to increase session frequency, but keep the total number of sessions constant.

To evaluate the cost-effectiveness of twice-weekly compared with once-weekly psychotherapy sessions after 12 months, from a societal perspective.

An economic evaluation was conducted alongside a randomised controlled trial comparing twice-weekly versus once-weekly sessions of psychotherapy (cognitive–behavioural therapy or interpersonal psychotherapy) for depression. Missing data were handled by multiple imputation. Statistical uncertainty was estimated with bootstrapping and presented with cost-effectiveness acceptability curves.

Differences between the two groups in depressive symptoms, physical and social functioning, and quality-adjusted life-years (QALY) at 12-month follow-up were small and not statistically significant. Total societal costs in the twice-weekly session group were higher, albeit not statistically significantly so, than in the once-weekly session group (mean difference €2065, 95% CI −686 to 5146). The probability that twice-weekly sessions are cost-effective compared with once-weekly sessions was 0.40 at a ceiling ratio of €1000 per point improvement in Beck Depression Inventory-II score, 0.32 at a ceiling ratio of €50 000 per QALY gained, 0.23 at a ceiling ratio of €1000 per point improvement in physical functioning score and 0.62 at a ceiling ratio of €1000 per point improvement in social functioning score.

Based on the current results, twice-weekly sessions of psychotherapy for depression are not cost-effective over the long term compared with once-weekly sessions.

The ability to extinguish a maladaptive conditioned fear response is crucial for healthy emotional processing and resiliency to aversive experiences. Therefore, enhancing fear extinction learning has immense potential emotional and health benefits. Mindfulness training enhances both fear conditioning and recall of extinguished fear; however, its effects on fear extinction learning are unknown. Here we investigated the impact of mindfulness training on brain mechanisms associated with fear-extinction learning, compared to an exercise-based program.

We investigated BOLD activations in response to a previously learned fear-inducing cue during an extinction paradigm, before and after an 8-week mindfulness-based stress reduction program (MBSR, n = 49) or exercise-based stress management education program (n = 27).

The groups exhibited similar reductions in stress, but the MBSR group was uniquely associated with enhanced activation of salience network nodes and increased hippocampal engagement.

Our results suggest that mindfulness training increases attention to anticipatory aversive stimuli, which in turn facilitates decreased aversive subjective responses and enhanced reappraisal of the memory.

cocaine is a widely used illegal drug, known for its fast ability to induce euphoria and arousal. However, cocaine exposure can contribute to several mental and physical effects. Cocaine induced brain damage can be divided into 3 mechanisms: direct effect leading to toxic encephalopathy, secondary to vascular damage causing vasculitis, stroke and vasospasm, and tertiary effect due to hypoxia through a cardiovascular collapse.

Here, we report 2 young men who developed a subacute encephalopathy with different clinical and radiological presentation after a cocaine overdose

a case serie

we present two men aged respectively of 28 (P1) and 42 years-old (P2). Both had a history of alcohol consumption and toxicomania (mainly cocaine) during the past year. They manifested, 2 weeks following a cocaine overdose, with gait disorder and confusion. On examination, P1 was apathic and confused. He had a subcortical frontal syndrome with gait apraxia and grasping reflex, along with a quadri-pyramidal syndrome. While patient P2 developed a cognitive decline, parkinsonism with dystonic posture of the trunk and the right limbs, and a pseudobulbar syndrome. Brain MRI was performed in both patients and showed a bilateral multifocal leukoencephalopathy (P1) and the presence of bilateral hyper T2 and FLAIR weighted images affecting basal ganglia, the mesencephalon and the periventricular cerebral white matter. Cerebrospinal fluid (CSF) analysis showed no pleocytosis and normal proteinorrachia. Electroencephalogram was also normal. Infectious differential diagnosis including Human Immunodeficiency Virus (HIV) and syphilis were excluded and metabolic screening including copper analysis, serum and CSF lactate were normal. The urine toxic screening, performed 20 days following the drug overdose, was negative. Both patients were treated with benzodiazepine and fluids without significative improvement. They were discharged with major cognitive and motor impairment.

cocaine toxicity is associated with high morbidity and mortality. Usually, cocaine abuse can lead to cardio-vascular, pulmonary and nervous complication. Neuropsychiatric sequelae are uncommon with less recovery potential. To date, there is no drug to prevent or cure cocaine addiction. The key is to educate the patient when he or she presents to the emergency department. Patients should be urged to seek drug counseling.

None Declared

International guidelines recommend that prospective organ transplant patients receive a psychosocial assessment to optimise outcomes. There is limited consensus regarding the criteria for psychosocial evaluation. The Stanford Integrated Psychosocial Assessment for Transplantation (SIPAT) tool was developed to enhance the pre-transplant psychosocial workup. The Mater Hospital is the National Centre for heart and lung transplantation in Ireland. The consultation-liaison psychiatry (CLP) service provides screening of pre-transplant candidates using a biopsychosocial assessment, SIPAT and cognitive screening tools. Post-transplant patients are reviewed on a referral basis.

To identify the psychosocial needs of heart and lung transplant recipients and CLP service input over a one year period.

A review of all heart and lung transplant recipients between January 1st and December 31st 2021 was conducted. The following data were recorded: demographics, pre-existing mental illness, SIPAT scores, and referral to the CLP service within six months of transplantation.

Twenty-eight individuals received a heart/lung transplant in 2021 (7 heart, 19 lung, 1 heart &liver, 1 heart & lung). Prior to transplant 50% (14/28) had a pre-existing mental health diagnosis, 7% (2/28) had attended a psychiatrist, and 28.6% (8/28) were on psychotropic medication. SIPAT scores were available for 20 patients. The overall mean SIPAT score was 10.8 (SD 6.1). The subscales were as follows: Patient Readiness, mean 3.2 (SD 1.7); Social Support System, mean 2.1 (SD: 1.8); Psychological Stability & Psychopathology, mean 1.6 (SD 2.7); and Lifestyle & Substance Misuse, mean 3 (SD 1.5). Based on SIPAT scores, 20% (4/20) were excellent candidates, 75% (15/20) were good candidates and 1 (1/20) was minimally acceptable. Pre-existing mental illness was associated with higher total SIPAT scores (p=0.013) and higher scores on the psychological stability subscale (p=0.032). Post-transplant, 50% (14/28) were referred for psychological support and 21.4% (6/28) were referred to the CLP service. A further 10.7% (n=3) were attending CLP prior to transplant. Referrals to CLP occurred (median) 13 days (range 1-275) post-transplant surgery. The reasons for attending CLP were anxiety (5/9), delirium (3/9) and mood (1/9).

SIPAT can be a valuable tool for use in the pre-transplant workup to help identify those that will require intensive psychosocial support post- transplant.

None Declared

Voluntary poisoning with neurotoxic products in order to achieve euphoria is common especially among young people. Neurological complications are quite likely and can be serious and irreversible.

We aim to describe the peripheral neuropathies secondary to N-Hexane intoxication in a Tunisian population.

A retrospective descriptive study was carried out in our department of neurology in the NationalInstitute of Neurology of Tunis including patients diagnosed with N-Hexane neuropathy. All patientshad a history of a N-Hexane exposure. The diagnosis was confirmed after excluding other etiologiesthrough appropriate investigations. Clinical and para-clinical data as well as follow-up were assessed.

We selected 38 patients with a mean age of 22.7 years [14-36]. Among them, 37 were glue-sniffer and 1 had a voluntary toxic exposure to paint. An associated cannabis consumption was found in 6 patients. All of them had a low socio-economic background and 17 were unemployed. Time to onset of neurological signs ranged from 5 months to 11 years. The clinical exam showed a quadriparesis (15,7%), a paraparesis (58%), sensory involvement (55,2%) amyotrophy (40%) and abolished tendon reflexes in lower limbs (81,5%). Swallowing disorder and optic neuritis were found in one case. The electroneuromyogram revealed an axono-demyelinating sensory-motor polyneuropathy (PN) in 16 cases and a demyelinating motor PN in 9 cases. Vitamin therapy, motor rehabilitation and psychotherapy sessions have been indicated. Only 6 patients showed slight clinical improvement after withdrawal. The rest of our patients did not quit; 84% of them became bedridden.

Glue-sniffer related neuropathy is very common in our country especially in adolescents and young adults with low socio-economic background. The neurological outcome is serious and usually irreversible if exposure is persistent.

None Declared

Electronic health record (EHR) data have many quality problems that may affect the outcome of research results and decision support systems. Many methods have been used to evaluate EHR data quality. However, there has yet to be a consensus on the best practice. We used a rule-based approach to assess the variability of EHR data quality across multiple healthcare systems.

To quantify data quality concerns across healthcare systems in a PCORnet Clinical Research Network, we used a previously tested rule-based framework tailored to the PCORnet Common Data Model to perform data quality assessment at 13 clinical sites across eight states. Results were compared with the current PCORnet data curation process to explore the differences between both methods. Additional analyses of testosterone therapy prescribing were used to explore clinical care variability and quality.

The framework detected discrepancies across sites, revealing evident data quality variability between sites. The detailed requirements encoded the rules captured additional data errors with a specificity that aids in remediation of technical errors compared to the current PCORnet data curation process. Other rules designed to detect logical and clinical inconsistencies may also support clinical care variability and quality programs.

Rule-based EHR data quality methods quantify significant discrepancies across all sites. Medication and laboratory sources are causes of data errors.