Seven Epidemic Waves of COVID-19 in a Hospital in Madrid: Analysis of Severity and Associated Factors.

(1) Background: COVID-19 has evolved during seven epidemic waves in Spain. Our objective was to describe changes in mortality and severity in our hospitalized patients. (2) Method: This study employed a descriptive, retrospective approach for COVID-19 patients admitted to the Hospital de Fuenlabrada (Madrid, Spain) until 31 December 2022. (3) Results: A total of 5510 admissions for COVID-19 were recorded. The first wave accounted for 1823 (33%) admissions and exhibited the highest proportion of severe patients: 65% with bilateral pneumonia and 83% with oxygen saturation under 94% during admission and elevated levels of CRP, IL-6, and D-dimer. In contrast, the seventh wave had the highest median age (79 years) and comorbidity (Charlson: 2.7), while only 3% of patients had bilateral pneumonia and 3% required intubation. The overall mortality rate was 10.3%. The first wave represented 39% of the total. The variables related to mortality were age (OR: 1.08, 1.07-1.09), cancer (OR: 1.99, 1.53-2.60), dementia (OR: 1.82, 1.20-2.75), the Charlson index (1.38, 1.31-1.47), the need for high-flow oxygen (OR: 6.10, 4.94-7.52), mechanical ventilation (OR: 11.554, 6.996-19.080), and CRP (OR: 1.04, 1.03-1.06). (4) Conclusions: The variables associated with mortality included age, comorbidity, respiratory failure, and inflammation. Differences in the baseline characteristics of admitted patients explained the differences in mortality in each wave. Differences observed between patients admitted in the latest wave and the earlier ones suggest that COVID-19 has evolved into a distinct disease, requiring a distinct approach.

Comparative Study of Vaccinated and Unvaccinated Hospitalised Patients: A Retrospective Population Study of 500 Hospitalised Patients with SARS-CoV-2 Infection in a Spanish Population of 220,000 Inhabitants.

OBJECTIVES: This study aimed to compare the characteristics of fully and partially vaccinated or unvaccinated coronavirus disease 2019 (COVID-19) patients who were hospitalised in a population of 220,000 habitants. METHODS: Retrospective, observational, and population studies were conducted on patients who were hospitalised due to COVID-19 from March to October 2021. We assessed the impact of vaccination and other risk factors through Cox multivariate analysis. RESULTS: A total of 500 patients were hospitalised, among whom 77 (15.4%) were fully vaccinated, 86 (17.2%) were partially vaccinated, and 337 (67.4%) were unvaccinated. Fully vaccinated (FV) patients were older and had a higher Charlson index than those of partially vaccinated and unvaccinated patients (NFV). Bilateral pneumonia was more frequent among NFV (259/376 (68.9%)) than among FV patients (32/75 (42.7%)). The former had more intensive care unit admissions (63/423) than the latter (4/77); OR: 2.80; CI (1.07-9.47). Increasing age HZ: 1.1 (1.06-1.14)) and haematological disease at admission HZ: 2.99 (1.26-7.11)) were independent risk factors for higher mortality during the first 30 days of hospitalisation. The probability of an earlier discharge in the subgroup of 440 patients who did not die during the first 30 days of hospitalisation was related to age (older to younger: HZ: 0.98 (0.97-0.99)) and vaccination status. CONCLUSIONS: Among the patients hospitalised because of COVID-19, complete vaccination was associated with less severe forms of COVID-19, with an earlier discharge date. Age and haematological disease were related to a higher mortality rate during the first 30 days of hospitalisation.

Prognostic factors and combined use of tocilizumab and corticosteroids in a Spanish cohort of elderly COVID-19 patients.

Coronavirus disease 2019 (COVID-19) infection in elderly patients is more aggressive and treatments have shown limited efficacy. Our objective is to describe the clinical course and to analyze the prognostic factors associated with a higher risk of mortality of a cohort of patients older than 80 years. In addition, we assess the efficacy of immunosuppressive treatments in this population. We analyzed the data from 163 patients older than 80 years admitted to our institution for COVID-19, during March and April 2020. A Lasso regression model and subsequent multivariate Cox regression were performed to select variables predictive of death. We evaluated the efficacy of immunomodulatory therapy in three cohorts using adjusted survival analysis. The mortality rate was 43%. The mean age was 85.2 years. The disease was considered severe in 76.1% of the cases. Lasso regression and multivariate Cox regression indicated that factors correlated with hospital mortality were: age (hazard ratio [HR] 1.12, 95% confidence interval [CI]: 1.03-1.22), alcohol consumption (HR 3.15, 95% CI: 1.27-7.84), CRP > 10 mg/dL (HR 2.67, 95% CI: 1.36-5.24), and oxygen support with Venturi Mask (HR 6.37, 95% CI: 2.18-18.62) or reservoir (HR 7.87, 95% CI: 3.37-18.38). Previous treatment with antiplatelets was the only protective factor (HR 0.47, 95% CI: 0.23-0.96). In the adjusted treatment efficacy analysis, we found benefit in the combined use of tocilizumab (TCZ) and corticosteroids (CS) (HR 0.09, 95% CI: 0.01-0.74) compared to standard treatment, with no benefit of CS alone (HR 0.95, 95% CI: 0.53-1.71). Hospitalized elderly patients suffer from a severe and often fatal form of COVID-19 disease. In this regard, several parameters might identify high-risk patients upon admission. Combined use of TCZ and CS could improve survival.

Diagnosing hospital bacteraemia in the framework of predictive, preventive and personalised medicine using electronic health records and machine learning classifiers.

Background: The bacteraemia prediction is relevant because sepsis is one of the most important causes of morbidity and mortality. Bacteraemia prognosis primarily depends on a rapid diagnosis. The bacteraemia prediction would shorten up to 6 days the diagnosis, and, in conjunction with individual patient variables, should be considered to start the early administration of personalised antibiotic treatment and medical services, the election of specific diagnostic techniques and the determination of additional treatments, such as surgery, that would prevent subsequent complications. Machine learning techniques could help physicians make these informed decisions by predicting bacteraemia using the data already available in electronic hospital records. Objective: This study presents the application of machine learning techniques to these records to predict the blood culture's outcome, which would reduce the lag in starting a personalised antibiotic treatment and the medical costs associated with erroneous treatments due to conservative assumptions about blood culture outcomes. Methods: Six supervised classifiers were created using three machine learning techniques, Support Vector Machine, Random Forest and K-Nearest Neighbours, on the electronic health records of hospital patients. The best approach to handle missing data was chosen and, for each machine learning technique, two classification models were created: the first uses the features known at the time of blood extraction, whereas the second uses four extra features revealed during the blood culture. Results: The six classifiers were trained and tested using a dataset of 4357 patients with 117 features per patient. The models obtain predictions that, for the best case, are up to a state-of-the-art accuracy of 85.9%, a sensitivity of 87.4% and an AUC of 0.93. Conclusions: Our results provide cutting-edge metrics of interest in predictive medical models with values that exceed the medical practice threshold and previous results in the literature using classical modelling techniques in specific types of bacteraemia. Additionally, the consistency of results is reasserted because the three classifiers' importance ranking shows similar features that coincide with those that physicians use in their manual heuristics. Therefore, the efficacy of these machine learning techniques confirms their viability to assist in the aims of predictive and personalised medicine once the disease presents bacteraemia-compatible symptoms and to assist in improving the healthcare economy.

Lymphoproliferative response after stimulation with soluble leishmania antigen (SLA) as a predictor of visceral leishmaniasis (VL) relapse in HIV+ patients.

The introduction of HAART resulted in the decrease of Leishmania/HIV co-infection cases; nevertheless, the number of relapses remains high and secondary prophylaxis is recommended. However, secondary prophylaxis is not necessary in all patients, and presents a high risk of toxicity and an elevated cost. Our aim was to study whether specific cellular response to Leishmania infantum (measured by cell proliferation response after stimulation with soluble Leishmania antigen (SLA)), could be a useful tool to attempt a secondary prophylaxis withdrawal. In June 2009 an outbreak of leishmaniasis by Leishmania infantum was declared in the southeast of Madrid, and since January 2013, we recruited 10 HIV+ patients that had been treated for visceral leishmaniasis. 6 patients had positive SLA-cell proliferation test. The mean CD4 cell counts of those patients with positive SLA were 140 cel/mm3 and 40 cel/mm3 in those with negative SLA test. 3 patients with positive SLA-cell proliferation test (CD4 count: 336, 307, 625) were not on prophylaxis, and the other 3 patients (CD4 count: 152, 189, 359) were on secondary prophylaxis that was withdrawn after the positive SLA-cell proliferation test with no posterior relapses (mean follow up 60 weeks). From the 4 patients, which had negative SLA-cell proliferation test and continued on prophylaxis, 3 had positive PCR for Leishmania at the end of the follow-up and 2 presented clinical relapses. The performance of SLA-cell proliferation test can be a useful tool that can permit us to try withdrawal of the prophylaxis in Leishmania/HIV co-infected patients with low CD4+ counts under clinical supervision, diminishing risk of toxicity and cost.

Osteomalacia provocada por un tumor hiperfosfatúrico / Osteomalacia produced by a hyperphosphaturic tumor

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Clinical diagnostic accuracy of suspected sources of bacteremia and its effect on mortality.

BACKGROUND: Although much has been written about bacteremia, evidence of the clinical diagnostic accuracy of bacteremia sources in the absence of microbiological results and the impact of diagnostic accuracy on mortality is scarce. METHODS: This is a retrospective study of bacteremia episodes over a 2-year period at a general hospital in Madrid. Congruence analyses between clinically presumed and definite sources, acquisition, causative organism, empirical treatment and progression to death were performed. RESULTS: The study included 323 bacteremia episodes. Clinicians' diagnostic accuracy was higher for gastrointestinal (88.8%; 95% CI: 79%-84%), respiratory (93.9%; 95% CI: 79%-99%) and urinary tract sources (83.6%; 95% CI: 75%-89%) and lower for skin and soft tissues (77.2%; 95% CI: 54%-92%) and, notably, intravascular sources (56%; 95% CI: 39%-71%). Overall, a non-significant (3.45%; 95% CI: -0.6%-13.5%, p=0.47) increase in mortality was observed in the incorrectly suspected bacteremia source group. Mortality related to a definitive source was significantly higher when an intravascular origin was not suspected, resulting in a 26% increase in mortality (95% CI: 1%-52%, p=0.03). Differences in mortality related to inaccurate source assumptions were non-significant when the definitive bacteremia sources were gastrointestinal, urinary, respiratory, skin and soft tissues or unknown. Mortality in the group receiving appropriate empirical antimicrobial treatment was 10.6% compared with 19.7% mortality in the group receiving inappropriate empirical antimicrobial treatment (OR 2; 95% CI: 1.01-4.25). CONCLUSIONS: The diagnostic accuracy of bacteremia sources is high in all but intravascular sources. A non-suspected intravascular source and inappropriate empirical treatment are related to a higher mortality.

Imported malaria in pregnancy in Madrid.

BACKGROUND: Malaria in pregnancy is associated with maternal and foetal morbidity and mortality in endemic areas, but information on imported cases to non-endemic areas is scarce.The aim of this study was to describe the clinical and epidemiological characteristics of malaria in pregnancy in two general hospitals in Madrid, Spain. METHODS: Retrospective descriptive study of laboratory-confirmed malaria in pregnant women at the Fuenlabrada University Hospital and the Príncipe de Asturias University Hospital, in Madrid, over a six- and 11-year period, respectively. Relevant epidemiological, clinical and laboratory data was obtained from medical records. RESULTS: There were 19 pregnant women among 346 malaria cases (5.4%). The average age was 27 years. The gestational age (trimester) was: 53% 3rd, 31% 1st, 16% 2nd. All but one were multigravidae. Three were HIV positive. All were sub-Saharan immigrants: two were recently arrived immigrants and seventeen (89%) had visited friends and relatives. None had taken prophylaxis nor seeked pre-travel advice. PRESENTATION: 16 symptomatic patients (fever in fourteen, asthenia in two), three asymptomatic. Median delay in diagnosis: 7.5 days. Laboratory tests: anaemia (cut off Hb level 11 g/dl) 78.9% (mild 31.6%, moderate 31.6%, severe 15.8%) thrombocytopaenia 73.7%, hypoglycaemia 10.5%. All cases were due to Plasmodium falciparum, one case of hyperparasitaemia. Quinine + clindamycin prescribed in 84%. OUTCOMES: no severe maternal complications or deaths, two abortions, fifteen term pregnancies, no low-birth-weight newborns, two patients were lost to follow-up. CONCLUSIONS: Though cases of malaria in pregnancy are uncommon, a most at risk group is clearly defined: young sub-Saharan mothers visiting friends and relatives without pre-travel counselling and recently-arrived immigrants. The most common adverse maternal and foetal effects were anaemia and stillbirth. Given that presentation can be asymptomatic, malaria should always be considered in patients with unexplained anaemia arriving from endemic areas. These findings could help Maternal Health programme planners and implementers to target preventive interventions in the immigrant population and should create awareness among clinicians.