Survival Impact of an On-Site Medicalization Program in the Control of COVID-19 Outbreaks in 11 Nursing Homes.

BACKGROUND: The elderly admitted to nursing homes have especially suffered the havoc of the COVID-19 pandemic since most of them are not prepared to face such health problems. METHODS: An innovative coordinated on-site medicalization program (MP) in response to a sizeable COVID-19 outbreak in three consecutive waves was deployed, sharing coordination and resources among primary care, the referral hospital, and the eleven residences. The objectives were providing the best possible medical care to residents in their environment, avoiding dehumanization and loneliness of hospital admission, and reducing the saturation of hospitals and the risk of spreading the infection. The main outcomes were a composite endpoint of survival or optimal palliative care (SOPC), survival, and referral to the hospital. RESULTS: 587 of 1199 (49%) residents were infected, of whom 123 (21%) died. Patients diagnosed before the start of the MP presented SOPC, survival, and referrals to the hospital of 83%, 74%, and 22.4%, opposite to 96%, 84%, and 10.6% of patients diagnosed while the MP was set up. The SOPC was independently associated with an MP (OR 3.4 [1.6-7.2]). CONCLUSION: During the COVID-19 outbreak, a coordinated MP successfully obtained a better rate of SOPC while simultaneously reducing the need for hospital admissions, combining optimal medical management with a more compassionate and humanistic approach in older people.

Changes in Serum Creatinine Levels Can Help Distinguish Hypovolemic from Euvolemic Hyponatremia.

Background and Objectives: Differentiating between hypovolemic (HH) and euvolemic hyponatremia (EH) is crucial for correct diagnosis and therapy, but can be a challenge. We aim to ascertain whether changes in serum creatinine (SC) can be helpful in distinguishing HH from EH. Materials and Methods: Retrospective analysis of patients followed in a monographic hyponatremia outpatient clinic of a tertiary hospital during 1 January 2014−30 November 2019. SC changes during HH and EH from eunatremia were studied. The diagnostic accuracy of the SC change from eunatremia to hyponatremia (∆SC) was analyzed. Results: A total of 122 hyponatremic patients, median age 79 years (70−85), 46.7% women. In total, 70/122 patients had EH, 52/122 HH. During hyponatremia, median SC levels increased in the HH group: +0.18 mg/dL [0.09−0.39, p < 0.001], but decreased in the EH group: −0.07 mg/dL (−0.15−0.02, p < 0.001), as compared to SC in eunatremia. HH subjects presented a higher rate of a positive ∆SC than EH (90.4% vs. 25.7%, p < 0.001). EH subjects presented a higher rate of a negative/null ∆SC than HH (74.3% vs. 9.6%, p < 0.001). ROC curve analysis found an AUC of 0.908 (95%CI: 0.853 to 0.962, p < 0.001) for ∆SC%. A ∆SC% ≥ 10% had an OR of 29.0 (95%CI: 10.3 to 81.7, p < 0.001) for HH. A ∆SC% ≤ 3% had an OR of 68.3 (95%CI: 13.0 to 262.2, p < 0.001) for EH. Conclusions: The assessment of SC changes from eunatremia to hyponatremia can be useful in distinguishing between HH and EH.

Predicting 30-Day Readmission Risk for Patients With Chronic Obstructive Pulmonary Disease Through a Federated Machine Learning Architecture on Findable, Accessible, Interoperable, and Reusable (FAIR) Data: Development and Validation Study.

BACKGROUND: Owing to the nature of health data, their sharing and reuse for research are limited by legal, technical, and ethical implications. In this sense, to address that challenge and facilitate and promote the discovery of scientific knowledge, the Findable, Accessible, Interoperable, and Reusable (FAIR) principles help organizations to share research data in a secure, appropriate, and useful way for other researchers. OBJECTIVE: The objective of this study was the FAIRification of existing health research data sets and applying a federated machine learning architecture on top of the FAIRified data sets of different health research performing organizations. The entire FAIR4Health solution was validated through the assessment of a federated model for real-time prediction of 30-day readmission risk in patients with chronic obstructive pulmonary disease (COPD). METHODS: The application of the FAIR principles on health research data sets in 3 different health care settings enabled a retrospective multicenter study for the development of specific federated machine learning models for the early prediction of 30-day readmission risk in patients with COPD. This predictive model was generated upon the FAIR4Health platform. Finally, an observational prospective study with 30 days follow-up was conducted in 2 health care centers from different countries. The same inclusion and exclusion criteria were used in both retrospective and prospective studies. RESULTS: Clinical validation was demonstrated through the implementation of federated machine learning models on top of the FAIRified data sets from different health research performing organizations. The federated model for predicting the 30-day hospital readmission risk was trained using retrospective data from 4.944 patients with COPD. The assessment of the predictive model was performed using the data of 100 recruited (22 from Spain and 78 from Serbia) out of 2070 observed (records viewed) patients during the observational prospective study, which was executed from April 2021 to September 2021. Significant accuracy (0.98) and precision (0.25) of the predictive model generated upon the FAIR4Health platform were observed. Therefore, the generated prediction of 30-day readmission risk was confirmed in 87% (87/100) of cases. CONCLUSIONS: Implementing a FAIR data policy in health research performing organizations to facilitate data sharing and reuse is relevant and needed, following the discovery, access, integration, and analysis of health research data. The FAIR4Health project proposes a technological solution in the health domain to facilitate alignment with the FAIR principles.

Applying the FAIR4Health Solution to Identify Multimorbidity Patterns and Their Association with Mortality through a Frequent Pattern Growth Association Algorithm.

The current availability of electronic health records represents an excellent research opportunity on multimorbidity, one of the most relevant public health problems nowadays. However, it also poses a methodological challenge due to the current lack of tools to access, harmonize and reuse research datasets. In FAIR4Health, a European Horizon 2020 project, a workflow to implement the FAIR (findability, accessibility, interoperability and reusability) principles on health datasets was developed, as well as two tools aimed at facilitating the transformation of raw datasets into FAIR ones and the preservation of data privacy. As part of this project, we conducted a multicentric retrospective observational study to apply the aforementioned FAIR implementation workflow and tools to five European health datasets for research on multimorbidity. We applied a federated frequent pattern growth association algorithm to identify the most frequent combinations of chronic diseases and their association with mortality risk. We identified several multimorbidity patterns clinically plausible and consistent with the bibliography, some of which were strongly associated with mortality. Our results show the usefulness of the solution developed in FAIR4Health to overcome the difficulties in data management and highlight the importance of implementing a FAIR data policy to accelerate responsible health research.

The Use of Corticosteroids or Tocilizumab in COVID-19 Based on Inflammatory Markers.

BACKGROUND: The inflammatory cascade is the main cause of death in COVID-19 patients. Corticosteroids (CS) and tocilizumab (TCZ) are available to treat this escalation but which patients to administer it remains undefined. OBJECTIVE: We aimed to evaluate the efficacy of immunosuppressive/anti-inflammatory therapy in COVID-19, based on the degree of inflammation. DESIGN: A retrospective cohort study with data on patients collected and followed up from March 1st, 2020, to May 1st, 2021, from the nationwide Spanish SEMI-COVID-19 Registry. Patients under treatment with CS vs. those under CS plus TCZ were compared. Effectiveness was explored in 3 risk categories (low, intermediate, high) based on lymphocyte count, C-reactive protein (CRP), lactate dehydrogenase (LDH), ferritin, and D-dimer values. PATIENTS: A total of 21,962 patients were included in the Registry by May 2021. Of these, 5940 met the inclusion criteria for the present study (5332 were treated with CS and 608 with CS plus TCZ). MAIN MEASURES: The primary outcome of the study was in-hospital mortality. Secondary outcomes were the composite variable of in-hospital mortality, requirement for high-flow nasal cannula (HFNC), non-invasive mechanical ventilation (NIMV), invasive mechanical ventilation (IMV), or intensive care unit (ICU) admission. KEY RESULTS: A total of 5940 met the inclusion criteria for the present study (5332 were treated with CS and 608 with CS plus TCZ). No significant differences were observed in either the low/intermediate-risk category (1.5% vs. 7.4%, p=0.175) or the high-risk category (23.1% vs. 20%, p=0.223) after propensity score matching. A statistically significant lower mortality was observed in the very high-risk category (31.9% vs. 23.9%, p=0.049). CONCLUSIONS: The prescription of CS alone or in combination with TCZ should be based on the degrees of inflammation and reserve the CS plus TCZ combination for patients at high and especially very high risk.

Dorsalgia tras colangiopancreatografía retrógrada endoscópica / Back pain after endoscopic retrograde cholangiopancreatography

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Hepatocarcinoma en paciente sin fibrosis avanzada tras erradicación de VHC con tratamiento antiviral / Hepatocellular carcinoma in patients without advanced fibrosis after HCV eradication antiviral treatment

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Hepatocellular carcinoma in patients without advanced fibrosis after HCV eradication antiviral treatment.

From the last few years, hepatitis C virus and the new direct antiviral treatments are being more and more important. In consequence, case studies like the one we present, the appearance of hepatocelullar carcinoma after its eradication with fibrosis grade 2, are getting special interest. In 2007, our patient was treated with pegylated interferon α-2a and ribavirin, having a sustained virological response after it. In this way, liver fibrosis grade 2 was confirmed by a biopsy. Finally, after corroborating a good liver functioning, the patient was discharged (as, according to the guidebooks, an ultrasound scan of screeing every 6 months was not required). In 2014, the patient came to hospital because of a pain at right hypochondrium and he was diagnosed with hepatocelullar carcinoma. A hepatectomy was done objectifying the surgical piece, liver fibrosis grade 2, one more time. Subsequently, a tumour relapse through an abdominal CT scan, a tumour relapse was found and despite the Sorafenib treatment, the patient died on January 2015. This case study provokes curiosity and uncertainty about the attitude which should be taken respect to the monitoring, and hepatocelullar carcinoma screening overall, in patients with a sustained virological response after eradicator treatment and without advanced fibrosis. Nowadays, with the benefits of the new treatments, the amount of patients in this situation is increasing significantly.