Predicting mortality in critically ill COVID-19 patients in a low-resources setting

Since its molecular isolation on January 7, 2020, the novel coronavirus SARS-CoV-2 has spread rapidly, taking governments worldwide off-guard. The virus arrived in low and middle-income countries violently, especially in Latin America. Ecuador received the worst outbreak in the world if we count excess mortality per capita. Although one study has reported the epidemiological impact of COVID-19 in Ecuador, there is no clinical course or outcome data among intensive care patients with COVID-19 in Ecuador. This study describes the clinical, epidemiological, and therapeutical features of 89 patients hospitalized in a secondary-level hospital in Quito, Ecuador. We We collected health records data from adult patients with severe COVID-19 admitted to the intensive care unit (ICU) in Quito, Ecuador, during the rst ve months of the SARS-CoV-2 outbreak in Ecuador. All patients had a conrmed SARS-CoV-2 RNA infection diagnostic, a positive real-time RT-PCR, and pulmonary imaging suggesting COVID-19. We used the Chi-square test or a Fisher's exact statistic to analyze risk and associations between survivors and non-survivors due to COVID-19. We used the ROC curve analysis to predict mortality, determining cut-off points for the parameters related to mechanical, analytical, and cytometry ventilation. At the multivariate level, we used the Wald test to evaluate model categorical predictors during the regression analysis. IL-6, the lymphocyte and platelet count at 48 hours, the neutrophil count at 48 hours, and the INL are factors associated with higher motility, increased risk of failed extubation and reintubation


Introduction
On December 31, the Wuhan Municipal Health Committee informed the World Health Organization (WHO) that 27 people had been diagnosed with a type of pneumonia never described before [1]. On January 7, 2020, Chinese scientists had isolated and sequenced the etiological agent, a novel beta coronavirus later identi ed as SARS-CoV-2 (severe acute respiratory syndrome coronavirus type -two) [2]. The genome of this RNA virus was made available on January 12, 2020, allowing laboratories in different countries to produce speci c primers for the infection diagnoses using real-time reverse transcription-polymerase chain reaction (RT-PCR) [2,3]. On March 11, 2020, the WHO declares COVID-19 a pandemic after the virus arrived in several countries rapidly [4]. Up to October 5, 2020, more than 35 million people had been infected, causing more than 1 million deaths worldwide [3] In Latin America, a region with high levels of social inequality, mortality rates, and attack rate due to COVID-19 are devastating, especially for those living in poverty [5]. Households in the lowest income group have reduced access to health services, molecular diagnosis, and treatment.
Health systems with scarce economic resources and disrupted contact tracing capabilities are often incapable of controlling outbreaks at the community level, affecting mortality and hospital admission trends [6].
In mid-February, the disease reached Latin America and hit Ecuador abruptly. The rst case in Ecuador was o cially reported on February 27th, but the only scienti c report available suggest that the virus has entered the country weeks earlier [7]. In March, the virus had spread massively within Ecuador's coastal provinces, causing thousands of deaths each day in Ecuador, highlighting Guayaquil as the rst COVID-19 epicenter in Latin America and the worst-hit country in the world [8].
In Ecuador, there is only one report exploring the epidemiological trends of COVID-19 in Ecuador, including a brief description of the clinical presentation among asymptomatic and mildly ill patients; nevertheless, no data is available in terms of the clinical features and outcome among critically ill patients [7].
This study aims to present the outcome and clinical characteristics of COVID-19 patients admitted to the intensive care unit in a secondary level hospital in Quito, Ecuador, from April 1, 2020, to July 31, 2020.

Setting
The study was carried out in the Intensive Care Unit in the secondary level hospital Pablo Arturo Suárez Hospital, Quito, Ecuador.
Quito is the capital of Ecuador and has a population of 2´781.641 million. The city is located in the province of Pichincha and has an elevation of 2,850 m above sea level, becoming the second-highest capital city in the world.

Study design
A retrospective cohort study of the clinical course and mortality due to COVID-19 among adult patients hospitalized and admitted to the ICU unit from April 1 to July 31, 2020 Population and sample size Every patient admitted to the ICU unit with a suspected diagnosis of COVID-19 was included in the study. At the end of the study, we included 89 patients that ful ll the inclusion criteria while 12 were excluded from the study.

Inclusion criteria
Every patient was admitted to the ICU unit with a positive molecular RT-PCR panel for SARS-CoV-2 detection in nasopharyngeal swabs. Evey patient also had a CT-scan suggestive of tomographic pattern related to COVID-19 (CO-RADS 4 or 5). All the patients included in the study recived conventional invasive mechanical ventilation during the duration of the observation.

Exclusion criteria
Patients with a mild clinical presentation that were not admitted to the ICU or those with respiratory symptomatology that tested negative for SARS-CoV-2 infection (RT-PCR) and had a tomographic pattern not compatible with COVID-19 (CO-RADS 0 to 3) were excluded. Those patients not requiring noninvasive mechanical ventilation who bene ted from noninvasive ventilation or high ow cannulae were treated in different clinical wards therefore excluded from the study.

Variables and measurements
Our team reviewed every patient's electronic records admitted to the ICU unit that ful ll the inclusion criteria. Information concerning epidemiological, clinical, serological, and cytometric data variables were collected. Every record was reviewed on a daily basis and data retrieved from admission to discharge or death in the ICU during the data collection period.

Statistical analysis
We performed a complete descriptive statistical analysis, absolute and relative values of every qualitative variable on a daily basis including ventilatiory parameters. Mean, and standard deviation measures were used to describe differences and dispersion of the data set.
The assumption of normality of the quantitative variables was veri ed using the Shapiro test, where the t-test was used for parametric quantitative variables and the Mann Whitney test for those with non-parametric distributions.
We used the Chi-square test or Fisher's exact statistic to compare the proportion of survivors and non-survivors due to COVID-19. An odds ratio greater than one was used to indicate that the outcome was more likely to occur in one group.
We used the ROC curve analysis to predict mortality, determining cut-off points using the Younden index for the parameters related to mechanical ventilation and cytometric parameters. At the multivariate level, the Wald method forward logistic procedure regression was used, determining predictors of mortality for COVID-19. Statistical signi cance was established for p-value < 0.05.

General results
During 121 days of follow-up, 89 patients with COVID-19 ful lled the inclusion criteria. 68,54 % (n=61) were men and 31,46% women (n=28). The average length of stay (ALOS) in those who survived was not statistically signi cant among those who survived (9.31 days) versus those who died (10.29 days). The follow-up ended with 66.29% of patients (n=59) discharged from the ICU unit, while 33.71% of them (n=30) died due to COVID-19 (Table 1).

Age and sex differences
The average age of patients admitted to the hospital was 54.7 years, and survivors were 11 years younger (50.9) than non-survivors (62.2), and this difference was statistically signi cant (p-value: 0.001). In terms of sex, men were three times more likely to die due to COVID-19 when compared to women, representing 40.98% (n=25) among men and 17.76% (n=5) among women (p-value: 0.032).

Assessment of mortality indicators
The sequential organ failure assessment (SOFA) score at 24, 48, and 72 hours after admission was found to be 7.91, 6.14, and 5.46, respectively. To mitigate end-expiratory alveolar collapse, applied extrinsic PEEP values at 48 hours were signi cantly lower (7.89 cmH2O) among survivors versus non-survivors (9.26 cmH2O) and this difference was statistically signi cant (p-value: 0.015). The maximum PCO2 at 72 hours was higher among non-survivors (49.34 mmHg), versus survivors (41.37 mmHg), is this difference statistically signi cant (p-value: 0.026) ( Survivors remained intubated for seven days while non-survivors for ten days, difference statistically signi cant (p-value: 0.002).    The cut-off points to predict mortality in the ROC curve using the Youden index of the mechanical ventilation parameters were positive for mortality if 48-hour PEEP ≥8.50 cmH20, where the sensitivity was 54% and speci city was 74% (Figure 1) Biomarkers analysis.
The area of the ROC curve for IL-6 was 0.675 (IC95% 0.542-0.809), and for LDH at 24 hours 0.691 (IC95% 0.580-0.803), these areas presented con dence intervals that do not include the value 0.5; therefore, they are signi cant in predicting mortality for COVID-19.
The cut-off points to predict mortality in the ROC curve using the Youden index of the analytical parameters were positive for mortality if IL-6 ≥117 pg. / mL, where the sensitivity was 42%, and speci city was 91%. Positive for mortality if 24-hour LDH ≥783 U / L, where the sensitivity was 90% and speci city 43% (Figure 2).

Discussion.
This original research is the rst report of the clinical characteristics of severely ill patients with COVID-19 who have been clinically managed in a secondary-level hospital ICU unit in Quito, Ecuador. The results showed that older age and sex is positively associated with mortality. These results are similar to several reports available [9,10]. The average age of our admitted patients was 54 years, considerably younger populations than other countries. In China, two reports found that the mean age of patients admitted to the ICU was between 64 and 66 years, on average ten years older than our population [11,12]. In other continents, the age of the admitted patients is also higher. For instance, in Italy and Spain, the available information reports an average age of 63 years, while in the USA, the average age is 79 years. [10,[13][14][15][16]. Mejia et al. 2020 published the only available study similar to ours in a cohort of Peruvian patients. They found that the median age of the admitted patients was 59 years [17]. Although there is no clear information on why older men are at higher risk of dying due to COVID-19, a higher proportion of comorbidities among men may play a signi cant role, and the presence of unhealthier lifestyles. It has also been hypothesized that men the angiotensinconverting enzyme-2 (ACE-2) receptor might play an important role. Previsluty published studies suggest that the ACE-2 receptor plays a role in other coronaviruses-related diseases such as Severe acute respiratory syndrome (SARS) or Middle East Respiratory Syndrome (MERS), nding higher concentrations of ACE-2 receptors among men [18,19].
In terms of respiratory daily parameters, persisting hypercapnia for more than 72 hours, the PaFiO 2 ratio at 24 and 72 hours < 140 mmHg and PEEP greater than 9 cmH 2 O were also associated with increased risk of mortality. External positive pressure ventilation increases intrathoracic pressure and does so more potently when the lungs are highly compliant [20]. Moderate PEEP levels are required to ventilate adequately and achieve normoxia. In our results, maintaining PEEP levels greater than 8 mmHg after 48 hours was associated with poorer prognosis. Although the impact of COVID-19 within the lungs is not quite the same as other diseases causing ARDS, the role of adequate ventilatory management is fundamental.
Gatinonni et al 2020 de ned two phenotypic patterns in the clinical presentation of COVID-19, a Low (L) phenotype in which there is low elastacy, low shunt and poor recruitability with little response to PEEP and a High (H) phenotype, with high elastance, high shunt and favorable response to alveolar recruitment with PEEP [21,22].
Regarding the presentation of the L and H phenotypes in ARDS due to COVID 19, we consider that their presentation was variable, if we take into account the relationship between compliance and PaO2 / O2 as reported by Panwar [23], patients with PaO2 / FiO2 lower, like those with low compliance died, however these variables can be very heterogeneous, because there could be H patterns with PaO2 / FiO2 greater than 150 and in other L phenotypes with PaO 2 /FiO 2 <150mmHg. Both PaO 2 / FiO 2 as well as compliance have always been considered as a marker of severity, in our work, the patients who had lower values were the most serious and of them, those who died, had low compliance from admission as mentioned. in other studies, those whom improved PaO 2 / FiO 2 and improved their compliance pattern L, had better survival [22,23].
In our study we also found that elevated levels of IL6, LDH at 24 hours, lymphopenia at 48 hours, neutrophilia at 24 hours, and high INL from admission to 72 hours were also associated with greater mortality. This has been evaluated in previous works which may indirectly indicate a reaction due to the massive in ammatory response or the cytokine storm constantly related with more severe clinical presentations [24,25].
These results are similar to the others previously reported worldwide; however, it is interesting to note that ferritin and the D-dimer biomarker have not achieved enough statistical power to predict mortality [12,26]. Furthermore, our ndings support the use of cytometric analysis that are often affordable and available in low-resource settings.
Several laboratory data are identi ed as predictors of severity and mortality in COVID-19 such as: elevated D-dimer, lymphopenia, increased LDH, thrombocytopenia, increased C-reactive protein, elevated ferritin and interleukin 6, among others [27][28][29][30][31][32][33][34]. In our study, the factors associated with mortality were LDH values at 24 hours, IL-6, the lymphocyte and platelet count at 48 hours, the neutrophil count at 48 hours, and the INL in all its measurements; the latter, together with IL6, reached a predictive level. Results that are consistent with the existing evidence in the world. It was striking that D-dimer and ferritin at 24 and 48 hours did not present a signi cant association with mortality, which is far from the existing evidence at that time.
The most frequent comorbidities in our patients were: hypertension, obesity and diabetes mellitus (DM). For diabetes and hypertension there was no statistically signi cant difference in terms of risk of mortality, nevertheless, when evaluating body mass index, higher BMI was associated with greater risk of dying (Table 1) as described in other studies [26]. A clincal report from Wang, et.al 2020 showed statistically signi cant differences in terms of mortality among those with chronic hypertension [12]. On the other hand, other study found that hypertension was not an independent factor in terms of increasing mortality, opposing to hypercholesterolemia and DM [10].
In general terms, the overall mortality in our center seems to be adecuate when comparted to other countries. In Ecuador, we found that 33.7% of patients succumbed in the ICU unit due to COVID-19. This are encouraging ndings since Ecuador is a developing country with limited resources, conditions that can jeopardize clinical management due to the scarcity of resources and trained personnel [35]. A recently published report from China, including 517 patients reported a an overall mortality rate of 37.7% [12,13]. These numbers seem to be lower than other reports coming from Europe. For instance, In Italy, Grasselli et al, 2020 included 1,715 patients and they found that the overall mortality was superior to 48% [10].
In Spain, a national cohort of 736 patients reported mortality rates greater than 42% [14]. On the other hand, information emerging from the USA shows that mortality was signi cantly lower in a cohort of 1,392 patients. They reported an overall mortality of 23.6% [13].
In latinamerica, reports are scarce. We found that in Peru, the overall mortality rate among severelly ill COVID-19 patients was 32.4% [36].
However, in this study, cut-off points for serological biomarkers and mechanical ventilation variables analysis were not determined, which might give a more in-depth insight into our results.
The use of some pharmacological treatments such as Interleukin-6 inhibitors (Tocilizumab) has been proposed to reduce the effects of the cytokine storm on the organism, nevertheless, in the developing world, the lack of resources and the lack local regulatiry agency approvals have excluded most of the centers from using such a treatment. At the beginning of the pandemic eventhought the use of corticosteroids was controversial for the treatment of the so-called "cytokine storm", our cente relied on this drug as the only available medicine [27,[37][38][39]. During the rst few months of the outbreak, very few scienti c societies recommended using systemic corticosteroids to treat COVID-19 related ARDS, despite this, our hospital adopted the use of esteroids due to physiopatological mechanism related to ARDS [22]. We believe that the early use of sucha a treatment could be associated with our improved mortality rates that relatively low when compared to other centers [22,[40][41][42].

Limitations
Our results came from an intensive care unit of 7 beds. Therefore, the time to collect a representative sample was more prolonged than in other centers. Another limitation of our study is that additional drugs that were experimentally tested elsewhere such as Tocilizumab or Remdesivir were not available in our low resources setting.

Conclusions
The values of LDH at 24 hours, IL-6, the lymphocyte and platelet count at 48 hours, the neutrophil count at 48 hours, and the INL are factors associated with motility to these are added the failed extubation and the reintubation.
The clinical and physiopathological presentation of COVID-19 patients shares similarities with other respiratory diseases. These similarities allowed our secondary-level hospital to use corticosteroids as a therapeutic option from the beginning of the pandemic, although the WHO itself has contraindicated it, indeed inferring about the relatively low mortality rates that we have presented.
Although analytical markers such as IL 6 and LDH are acceptable and well-known parameters for managing critical patients, their use of predictive variables is a new nding. This strategy becomes a widely accessible and cost-effective way to establish the risk of mortality due to COVID-19 at a global level.

Declarations
Ethics approval and consent to participate The present study was carried out in accordance with local and international guidelines and regulations including the declaration of Helsinki and the good clinical practices (GCP). The protocol was presented to the Hospital Pablo Arturo Suarez internal ethics board and received approval (MSP-CZ9-HPASGEHO-2020-2504-M). Informed consent prior ICU unit admission was obtained from all adult's subjects including in the study.

Consent for publication
Not applicable Availability of data and materials The datasets used and analysed during the current study are available from the corresponding author on reasonable request.

Competing interests
The authors declare no con icts of interest.
Funding Figure 2 ROC curve to predict mortality for COVID-19, based on IL-6 and LDH at 24 hours.  ROC curve to predict mortality for COVID-19, based on SOFA at 48 and 72 hours.