Predictors of mortality among inpatients with COVID-19 infection in a tertiary referral center in the Philippines

Malundo, Anna Flor G.; Abad, Cybele Lara; Salamat, Maria Sonia S.; Sandejas, Joanne Carmela M.; Poblete, Jonnel B.; Planta, Jose Eladio G.; Morales, Shayne Julieane L.; Gabunada, Ron Rafael W.; Evasan, Agnes Lorrainne M.; Cañal, Johanna Patricia A.; Santos, Julian A.; Manto, Jeffrey T.; Mercado, Maria Elizabeth P.; Rojo, Raniv D.; Ornos, Eric David B.; Alejandria, Marissa M.

doi:10.1016/j.ijregi.2022.07.009

Cited by 4 publications

(6 citation statements)

References 29 publications

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“…This general trend has been documented in previous studies. 1,6,11,29,30 However, we noticed a pattern similar to a previous Philippine study 20 on cases of the ancestral variant: the CFRs of the lowest age group (i.e., 0-4 years) tend to be up to 6 times the CFR of the baseline (i.e., 18-29 years), with the lowest CFRs seen in the 5-17 age group. The US Centers for Disease Control and Prevention 29 shows a generally increasing trend in CFR but a study by Khera et al (2021) supports our findings and attributed this “U-shaped” phenomenon to several factors such as children having differential expression of ACE-2 receptors, more robust innate immune system (except for newborns), and lesser exposure due to public health measures.…”

Section: Discussionsupporting

confidence: 88%

“…The Philippines has been considered a hotspot for the coronavirus disease 2019 (COVID-19) in the Western Pacific region. 1 As of December 1, 2022, the country’s Department of Health (DOH) has reported a total of 4,037,547 cases, including 64,658 reported deaths. 2 Meanwhile, the World Health Organization (WHO) has tallied 639,572,819 confirmed cases and 6,615,258 deaths globally.…”

Section: Introductionmentioning

confidence: 99%

“…COVID-19 mortality is influenced by several factors like advanced age, sex, presence of pre-existing comorbid illness, and history of smoking and alcohol consumption. 1 More recently, studies have surfaced highlighting the differences in mortality rates among cases with different vaccination statuses 4,5 and among those who were previously infected. 5 According to SeyedAlighani and his colleagues (2021), mortality rates are additionally influenced by adequacy of health care delivery, political decisions, and epidemiological characteristics of the affected population.…”

Section: Introductionmentioning

confidence: 99%

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COVID-19 infection wave mortality from surveillance data in the Philippines using machine learning

Migriño,

Batangan,

Abello

2023

Preprint

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ObjectiveThe Philippines has had several COVID-19 infection waves brought about by different strains and variants of SARS-CoV-2. This study aimed to describe COVID-19 outcomes by infection waves using machine learning.MethodsWe used a cross-sectional surveillance data review design using the DOH COVID DataDrop data set as of September 24, 2022. We divided the data set into infection wave data sets based on the predominant COVID-19 variant(s) of concern during the identified time intervals: ancestral strain (A0), Alpha/Beta variant (AB), Delta variant (D), and Omicron variant (O). Descriptive statistics and machine learning models were generated from each infection wave data set.ResultsOur final data set consisted of 3 896 206 cases and ten attributes including one label attribute. Overall, 98.39% of cases recovered while 1.61% died. The Delta wave reported the most deaths (43.52%), while the Omicron wave reported the least (10.36%). The highest CFR was observed during the ancestral wave (2.49%), while the lowest was seen during the Omicron wave (0.61%). Higher age groups generally had higher CFRs across all infection waves. The A0, AB and D models had up to four levels with two or three splits for each node. The O model had eight levels, with up to 16 splits in some nodes. Of the ten attributes, only age was included in all the decision tree models, while region of residence was included in the O model. F-score and specificity were highest using naïve Bayes in all four data sets. Area under the curve (AUC) was highest in the naïve Bayes models for the A0, AB and D models, while sensitivity was highest in the decision tree models for the A0, AB and O models.DiscussionThe ancestral, Alpha/Beta and Delta variants seem to have similar transmission and mortality profiles. The Omicron variant caused lesser deaths despite being more transmissible. Age remained a significant predictor of death regardless of infection wave. We recommend constant timely analysis of available data especially during public health events and emergencies.

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Section: Discussionsupporting

confidence: 88%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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COVID-19 infection wave mortality from surveillance data in the Philippines using machine learning

Migriño,

Batangan,

Abello

2023

Preprint

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“…Previous studies have already shown that elevated ferritin and D-dimer values are associated with more severe disease and poorer outcomes in COVID-19 patients [ 25 , 26 ]. A retrospective study done in 2022 also showed that a PaO 2 /FiO 2 ratio ≤ 200 is a predictor of in-hospital mortality among COVID-19 patients among other factors such as age ≥ 60 years, chronic obstructive pulmonary disease, leukocytosis, lymphopenia, neutrophilia, and declining renal status (estimated glomerular filtration rate < 90) [ 27 ].…”

Section: Discussionmentioning

confidence: 99%

Prevalence of Hospital-Acquired Pneumonia Among Patients With Severe to Critical COVID-19 Pneumonia Given Tocilizumab

Adre,

Catangui,

Bondoc

et al. 2023

Cureus

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The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has challenged healthcare systems worldwide since late 2019. The interleukin-6 inhibitor tocilizumab is one of the most studied agents with a proven benefit for patients with severe and critical coronavirus disease 2019 (COVID-19) pneumonia. Known adverse effects of this agent include upper respiratory tract infections, headache, hypertension, and transaminitis. The risk of secondary bacterial complications among patients who were given tocilizumab remains unclear. A descriptive study was done that included all laboratory-confirmed COVID-19 patients with a severe or critical severity for the year 2021 who received at least one dose of tocilizumab. Of the 1220 laboratory-confirmed COVID-19 patients admitted to Manila Doctors Hospital in the year 2021, a total of 139 patients fulfilled the inclusion criteria and were included in the study. Twenty-one patients, or 15% of the study population, were diagnosed with hospital-acquired pneumonia. This value was similar to previous studies showing the prevalence of secondary bacterial infections among patients who were given tocilizumab. These values could potentially aid clinicians when deciding whether or not to give one or two doses of tocilizumab to patients with severe or critical COVID-19 pneumonia. Given that many patients who are admitted with severe or critical COVID-19 pneumonia often have multiple decompensated comorbidities, the decision to give tocilizumab to manage severe COVID-19 should be weighed against the risk of hospital-acquired pneumonia.

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“…Despite its worldwide prevalence, however, the pandemic did not impact all nations or individuals equally, with wide variability between countries and within countries in both case counts and per capita mortality [ 1 ]. While throughout much of the pandemic, media attention focused largely on its impact in the Global North, it was actually the Global South that bore the greatest burden, though lack of access to COVID-19 diagnostics resulted in a significant underreporting of cases and deaths [ 2 ]. In fact, while low- and middle-income countries (LMICs) accounted for 4.1 million (69%) of the 5.94 million official COVID-19 deaths reported to WHO between January 1, 2020 and December 31, 2021, they accounted for 15.6 million (86%) of the 18.2 million excess deaths estimated to have resulted from the COVID-19 pandemic during this same period [ 1 ].…”

Section: Introductionmentioning

confidence: 99%

The role of civil society organizations (CSOs) in the COVID-19 response across the Global South: A multinational, qualitative study

Levine,

Park,

Adhikari

et al. 2023

PLOS Glob Public Health

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Despite receiving less attention than high-income countries, low- and middle-income countries (LMICs) experienced more than 85% of global excess deaths during the first two years of the COVID-19 pandemic. Due to the unprecedented speed and scale of the COVID-19 pandemic, which placed large demands on government capacity, many LMICs relied on civil society organizations (CSOs) to assist in implementing COVID-19 response programs. Yet few studies have examined the critical role CSOs played in mitigating the effects of the COVID-19 pandemic in low resource settings. This study explored the CSO response to COVID-19 in five of the most heavily impacted LMICs in the Global South. Interviews were conducted from May to August 2021 with a purposive sample of CSO key informants within each of the five countries. A total of 52 CSOs were selected from which 53 key informants were interviewed either via Zoom or by phone. Interviews were coded and analyzed using NVivo or MAXQDA2020. Out of the 52 CSOs selected, 24 were national organizations, 8 were regional, and 20 were local. CSOs fell into six categories: community-based organizations, non-governmental organizations, unions/professional organizations, campaigns/social movements, research organizations/think tanks, and networks/coalitions. CSOs across all five countries adapted their missions, stretched their resources, and performed a wide range of activities that fit into five programmatic areas: food security and livelihood support, public health and medical care, cash transfer programs, risk communication and community education, and needs assessment. This qualitative analysis demonstrates the critical role CSOs played in supplementing government emergency aid response by delivering necessary resources and supporting highly vulnerable populations during the COVID-19 pandemic, as well as the primary challenges they faced in doing so. Given the generally weak state of public capacity in the LMICs studied, this role was vital to responding to the pandemic.

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Predictors of mortality among inpatients with COVID-19 infection in a tertiary referral center in the Philippines

Cited by 4 publications

References 29 publications

COVID-19 infection wave mortality from surveillance data in the Philippines using machine learning

COVID-19 infection wave mortality from surveillance data in the Philippines using machine learning

Prevalence of Hospital-Acquired Pneumonia Among Patients With Severe to Critical COVID-19 Pneumonia Given Tocilizumab

The role of civil society organizations (CSOs) in the COVID-19 response across the Global South: A multinational, qualitative study

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