Vaccination and mortality from COVID-19: a comparative study between hemodialysis, peritoneal dialysis, and non-dialysis adult population in Panama

Courville, Karen; Bustamante, Norman; Núñez-Samudio, Virginia; Pecchio, Maydelin; Landires, Iván; Viggiano, Carlos; Durán, Herna; Novoa, Nadji; Alvarado, Ernesto; Vargas, Francisco Suso; Salado, Dayan; Manzanares, José; Haughton, Kelly; Cuero, César; Niedda, María; Valdés, Régulo

doi:10.1007/s11255-023-03529-w

Cited by 3 publications

(2 citation statements)

References 18 publications

(18 reference statements)

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“…However, other researchers state that the COVID-19 pandemic led to increased death [24,25]. During the severe period of the COVID-19 pandemic, the mortality rate of patients with PD at our centre was 2.64%, whereas no significant changes were observed in the mortality rate of patients with PD (5.13%) over the same period.…”

Section: Discussioncontrasting

confidence: 52%

Machine learning algorithms for the prediction of adverse prognosis in patients undergoing peritoneal dialysis

Yang,

Wan,

Feng

et al. 2024

BMC Med Inform Decis Mak

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Background An appropriate prediction model for adverse prognosis before peritoneal dialysis (PD) is lacking. Thus, we retrospectively analysed patients who underwent PD to construct a predictive model for adverse prognoses using machine learning (ML). Methods A retrospective analysis was conducted on 873 patients who underwent PD from August 2007 to December 2020. A total of 824 patients who met the inclusion criteria were included in the analysis. Five commonly used ML algorithms were used for the initial model training. By using the area under the curve (AUC) and accuracy (ACC), we ranked the indicators with the highest impact and displayed them using the values of Shapley additive explanation (SHAP) version 0.41.0. The top 20 indicators were selected to build a compact model that is conducive to clinical application. All model-building steps were implemented in Python 3.8.3. Results At the end of follow-up, 353 patients withdrew from PD (converted to haemodialysis or died), and 471 patients continued receiving PD. In the complete model, the categorical boosting classifier (CatBoost) model exhibited the strongest performance (AUC = 0.80, 95% confidence interval [CI] = 0.76–0.83; ACC: 0.78, 95% CI = 0.72–0.83) and was selected for subsequent analysis. We reconstructed a compression model by extracting 20 key features ranked by the SHAP values, and the CatBoost model still showed the strongest performance (AUC = 0.79, ACC = 0.74). Conclusions The CatBoost model, which was built using the intelligent analysis technology of ML, demonstrated the best predictive performance. Therefore, our developed prediction model has potential value in patient screening before PD and hierarchical management after PD.

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Section: Discussioncontrasting

confidence: 52%

Machine learning algorithms for the prediction of adverse prognosis in patients undergoing peritoneal dialysis

Yang,

Wan,

Feng

et al. 2024

BMC Med Inform Decis Mak

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“…Patients with ESKD show an increased tendency to develop severe forms of infection with COVID-19 with a lethal outcome compared to the healthy population, which is why it is still necessary to shed light on the mechanisms that predominate towards an unfavorable outcome in this group of patients [ 17 ]. The significance of this research is also greater due to the fact that PD as a modality of KRT is a less frequently applied form of treatment compared to the much more prevalent HD both globally and in the Republic of Serbia, and the favorable circumstances of conducting the dialysis procedure at home became more obvious during the pandemic.…”

Section: Discussionmentioning

confidence: 99%

The Importance of Natural and Acquired Immunity to SARS-CoV-2 Infection in Patients on Peritoneal Dialysis

Baralić,

Laušević,

Ćujić

et al. 2024

Vaccines

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The pandemic caused by the SARS-CoV-2 virus had a great impact on the population of patients treated with peritoneal dialysis (PD). This study demonstrates the impact of infection and vaccination in 66 patients treated with PD and their outcomes during a 6-month follow-up. This is the first research that has studied the dynamics of anti-SARS-CoV-2 IgG in serum and effluent. In our research, 57.6% of PD patients were vaccinated, predominantly with Sinopharm (81.6%), which was also the most frequently administered vaccine in the Republic of Serbia at the beginning of immunization. During the monitoring period, the level of anti-SARS-CoV-2 IgG antibodies in the PD patients had an increasing trend in serum. In the group of vaccinated patients with PD, anti-SARS-CoV-2 IgG antibodies had an increasing trend in both serum and effluent, in contrast to non-vaccinated patients, where they decreased in effluent regardless of the trend of increase in serum, but statistical significance was not reached. In contrast to vaccinated (immunized) patients who did not acquire infection, the patients who only underwent the COVID-19 infection, but were not immunized, were more prone to reinfection upon the outbreak of a new viral strain, yet without severe clinical presentation and with no need for hospital treatment.

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Correlation between Vaccination and Child Mortality Rate Using Multivariate Linear Regression Model

Revathi,

Kaladevi,

Vimaladevi

et al. 2024

J. Info. Know. Mgmt.

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Population has increased drastically over the years and new diseases compete with the population. Immunisation is a preventive measure, which makes the person resistant or immune to the disease. Vaccination stimulates our own immune system against infection or diseases. Vaccines are available for more than twenty life-threatening diseases and it saves millions of lives throughout the world. In the 70th World Assembly conducted in the year 2017, around 194 countries participated and took the oath to strengthen vaccination thereby achieving goals of Global Vaccine Action Plan (GVAP). In spite of remarkable immunisation progress, approximately 20 million infants are not exposed to vaccination every year. The immunisation progress has stalled or even reversed in some countries, and there is a real risk that complacency will undermine past achievements. This paper considered the database of vaccine consumption rate from many countries issued by WHO to analyse the reason for poor access to vaccine with respect to the morality and poverty levels. For this analysis, the relation between vaccine consumption by children below five years, the children’s death rate record issued by the United Nations Children’s Education Fund (UNICEF), poverty index issued by the United Nations are considered. Multivariate linear regression algorithm is used to identify the correlation between datasets. The result shows that an increase in vaccination coverage results in reduction on mortality rate in most of the countries. A correlation coefficient of 0.7 was found between IMR and the vaccine dosages. Sub-Sahara countries’ poverty index has direct impact on the declined view of vaccination coverage.

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Vaccination and mortality from COVID-19: a comparative study between hemodialysis, peritoneal dialysis, and non-dialysis adult population in Panama

Cited by 3 publications

References 18 publications

Machine learning algorithms for the prediction of adverse prognosis in patients undergoing peritoneal dialysis

Machine learning algorithms for the prediction of adverse prognosis in patients undergoing peritoneal dialysis

The Importance of Natural and Acquired Immunity to SARS-CoV-2 Infection in Patients on Peritoneal Dialysis

Correlation between Vaccination and Child Mortality Rate Using Multivariate Linear Regression Model

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