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Diffuse pulmonary neuroendocrine cell hyperplasia (DIPNECH) is a rare pre-invasive disease whose pathophysiology remains unclear. We aimed to assess long-term evolution in imaging of DIPNECH, in order to propose follow-up recommendations. Patients with histologically confirmed DIPNECH from four centers, evaluated between 2001 and 2020, were enrolled if they had at least two available chest computed tomography (CT) exams performed at least 24 months apart. CT exams were analyzed for the presence and the evolution of DIPNECH-related CT findings. Twenty-seven patients, mostly of female gender (n = 25/27; 93%) were included. Longitudinal follow-up over a median 63-month duration (IQR: 31–80 months) demonstrated an increase in the size of lung nodules in 19 patients (19/27, 70%) and the occurrence of metastatic spread in three patients (3/27, 11%). The metastatic spread was limited to mediastinal lymph nodes in one patient, whereas the other two patients had both lymph node and distant metastases. The mean time interval between baseline CT scan and metastatic spread was 70 months (14, 74 and 123 months). Therefore, long-term annual imaging follow-up of DIPNECH might be appropriate to encompass the heterogeneous longitudinal behavior of this disease.

BackgroundWhile the concept of medication reconciliation seems relatively straightforward, implementing medication reconciliation has proved to be complex and challenging. In our setting, a teaching hospital with 700 beds, it seems very hard to perform extensive and complete reconciliation for every patient.PurposeThe objectives of this study were to describe the frequency and type of medication discrepancies (MD) during admission in cardiology, and to identify patients with a high risk of unintended medication discrepancies (UMD).Material and methodsMedication reconciliation was conducted at admission in the cardiology department over 4 weeks by trained pharmacists. (1) The best possible medication history (BPMH) was obtained using multiple sources (interview with the patient/family member, prescription vials, medication list, contact with general practitioner and community pharmacy, medical and pharmaceutical files). (2) Comparison of BPMH with the initial hospital prescription, identification of MD. (3) Classification of MD (intended/unintended) with the physician. Tools have been tested and validated in a pilot study. Statistical analysis examined the associations between UMD and patient reported factors (performed using R software). Statistical significance was reached if p<0.05.ResultsDuring the study period, 100 patients were included, mean age 67.6 years (SD 17.7), sex ratio (M/F) 1.3, corresponding to 746 prescription lines. Overall, 544 MD were identified, including 77 UMD (42% of patients). The most common UMD was omission (70%). Do not speak French (p=0.007), to be admitted to a hospitalisation unit (compared with intensive care unit) (p=0.019), a low level of education (p=0.004), ≥2 comorbidities (p=0.001), long term illness (p=0.042) and ≥8 drugs in the initial prescription (p=0.004) were found to be significantly associated with UMD. Level of education remained significantly and independently associated with UMD after adjusting in the multivariate analysis for factors statistically significant in the univariate analysis.ConclusionOur study allowed us to identify predicting factors for UMD. Selection of patients for medication reconciliation must take into consideration factors that have been statistically identified, but are also practical. It is difficult to obtain information about level of education. Therefore, we decided to prioritise patients with ≥ 8 drugs in the initial prescription for medication reconciliation.No conflict of interest

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