PANDEMIC 2009 INFLUENZA A(H1N1) IN ARGENTINA: A STUDY OF 337
PATIENTS ON MECHANICAL VENTILATION.
Elisa Estenssoro1, Fernando G. Ríos2, Carlos Apezteguía2, Rosa Reina1, Jorge Neira3, Daniel
H. Ceraso4,5, Cristina Orlandi6, Ricardo Valentini7, Norberto Tiribelli8, Matías Brizuela9,
Carina Balasini10, Sebastián Mare11, Gustavo Domeniconi12, Santiago Ilutovich13, Alejandro
Gómez14, Javiera Giuliani15, Cecilia Barrios16; and Pascual Valdez17.
For The Registry of the Argentinian Society of Intensive Care (SATI).
1 Hospital Interzonal San Martin de La Plata, Buenos Aires; 2 Hospital Nacional Alejandro
Posadas, El Palomar, Buenos Aires; 3 Sanatorio de la Trinidad-Palermo, Buenos Aires; 4.
Hospital Fernández, Buenos Aires, 5 Sanatorio San Lucas, Provincia de Buenos Aires; 6 Sanatorio
Lopez Lima, Gral. Roca, Río Negro; 7 CEMIC; Buenos Aires; 8 Hospital Churruca, Buenos
Aires; 9 Hospital Tránsito Cáceres de Allende, Córdoba; 10 Hospital Pirovano, Buenos Aires; 11
Sanatorio Julio Mëndez; Buenos Aires; 12 Sanatorio de la Trinidad-San Isidro, Provincia de
Buenos Aires; 13 Sanatorio de la Trinidad-Mitre, Buenos Aires; 14 Clínica de Los Arcos, Buenos
Aires;15 Hospital Italiano Garibaldi, Rosario; 16 Sanatorio Franchin, Buenos Aires, 17 Hospital
Velez Sarsfield, Buenos Aires.
CORRESPONDING AUTHOR and REQUESTS FOR REPRINTS:
Elisa Estenssoro, MD,
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Media embargo until 2 weeks after above posting date; see thoracic.org/go/embargo
AJRCCM Articles in Press. Published on March 4, 2010 as doi:10.1164/201001-0037OC
Copyright (C) 2010 by the American Thoracic Society.
Servicio de Terapia Intensiva, Hospital Interzonal de Agudos San Martín de La Plata,
42 No. 577; 1900 La Plata; Buenos Aires, Argentina.
SHORT RUNNING HEAD: Pandemic Influenza in Argentina.
DESCRIPTOR: 10.14 Pneumonia: Viral Infections
WORD COUNT OF THE MANUSCRIPT: 3751 words
This study was supported by the Argentinian Society of Intensive Care Medicine (SATI).
AT A GLANCE COMMENTARY:
Scientific Knowledge on the Subject.
Pandemic influenza A(H1N1) emerged in April of 2009 and rapidly spread throughout the world.
Though the majority of the patients undergo a benign course of disease, some present with acute
respiratory failure requiring ICU admission for mechanical ventilation, with a subsequent high
What This Study Adds to the Field.
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This study, one of the largest cohorts of the sickest patients with 2009 Influenza A(H1N1),
characterized these patients as middle-aged, and predominantly male, with frequent comorbidities
and severe ARDS. Most patients died primarily of refractory hypoxemia; but nonpulmonary
organ failure, expressed as shock and acute kidney failure, sometimes requiring hemodyalisis,
were also very common. Late ICU admission and coexistent infection with S.pneumoniae on
admission worsened patient outcome
This article has an online data supplement which is available from this issue’s table of content
online at www.atsjournals.org
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Rationale: The rapid spread of the 2009 Influenza A(H1N1) around the world underscores the
need for a better knowledge of epidemiology, clinical features, outcomes, and mortality
predictors, especially in the most severe presentations.
Objectives: To describe these characteristics in patients with confirmed, probable, and
suspected viral pneumonia caused by 2009 influenza A(H1N1) admitted to 35 intensive care
units with acute respiratory failure requiring mechanical ventilation in Argentina, between June
3 and September 7.
Methods: Inception-cohort study including 337 consecutive adult patients. Data were collected
in a form posted on the Argentinian Society of Intensive Care website.
Measurements and main results: Proportions of confirmed, probable, or suspected cases
were 39%, 8%, and 53% and had similar outcomes. APACHE II was 18±7; age 47±17 years;
56% were male; and 64% had underlying conditions, with obesity (24%), chronic obstructive
respiratory disease (18%), and immunosupression (15%) being the commonest. Seven percent
were pregnant. On admission, patients had severe hypoxemia (PaO2/FIO2140[87-200]),
extensive lung radiologic infiltrates (2.87±1.03 quadrants) and bacterial coinfection, (25%;
mostly with S.pneumoniae). Use of adjuvants such as recruitment maneuvers (40%) and prone
positioning (13%); and shock (72%) and acute kidney injury requiring hemodialysis (17%),
were frequent. Mortality was 46%, and was similar across all ages. APACHE II, lowest
PaO2/FIO2, shock, hemodialysis, prone positioning, and S.pneumoniae coinfection
independently predicted death.
Conclusions: Patients with 2009 influenza A(H1N1) requiring mechanical ventilation were
mostly middle-aged adults, often with comorbidities, and frequently developed severe ARDS
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and multiorgan failure requiring advanced organ support. Case-fatality rate was accordingly
WORD COUNT: 250
KEYWORDS: acute lung injury; ARDS; virus; mechanical ventilation; refractory hypoxemia;
multiple organ dysfunction.
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New diseases, or diseases that acquire distinctive characteristics on their
presentation and evolution, pose a challenge to the clinician. When an emergent
infectious disease becomes pandemic and causes severe illness and significant mortality
rates, the situation evolves into a major public health problem. By January 2, 2010,
more than 208 countries worldwide had reported laboratory-confirmed cases of
pandemic 2009 influenza A(H1N1), including at least 12,220 deaths (1). The seasonal
behavior of influenza offers the opportunity to assess the outbreaks occurring during
winters in the Southern and Northern hemispheres sequentially. In Argentina, the first
case occurred on April 25, 2009; the virus started to circulate rapidly after May 17 and
peaked between June 20 and July 3, with dissemination over the entire country (2). As
of January 2, 2010, there had been 1,390,566 cases of Influenza-Like Illness (ILI; 3);
14,034 were admitted to the hospital, with 617 deaths ensuing among them [4.4%] (2).
A massive admission of patients with severe pneumonia, many of them young
and in previous good health, crowded the hospitals—within a scenario involving a lack
of epidemiological and clinical data—and generated uncertainty and stress in the
Intensive Care Unit (ICU) staff, until the early reports from Mexico were published
showing some of the distinctive features of the illness (4-6). As did other intensive-care
societies, the Society of Intensive Care of Argentina (SATI) foresaw the risks and
challenges of the situation (7) and on June 27, 2009 uploaded to the society website a
voluntary Registry of Cases in order to answer the following questions:
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(1) What was the frequency of adult patients admitted to ICUs during the 2009
Influenza A(H1N1) pandemic with acute respiratory failure with ILI and viral
pneumonia necessitating mechanical ventilation (MV)?.
(2) What were the main risk factors, the clinical and physiological
characteristics, and the complications?
(3) What was the hospital mortality, and what were the conditions independently
associated with that outcome?
Design of the study and of the Registry
This was an inception-cohort study that included patients aged 15 years or more
admitted to the ICU with ILI and acute respiratory failure requiring MV, during the
winter season in the Southern Hemisphere. Data were collected online in a form
designed by experts of the SATI that, after pilot testing, was finally posted at the
Society website on June 27. Also included was an instruction form containing
operational definitions. Information was recorded both prospectively and
retrospectively. All this information was also available, on request, in paper form. Each
participating center filled out a form describing the characteristics of the hospital and of
its ICU. Records were controlled for errors, and local researchers were contacted by the
study authors (EE and FGR), if needed.
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On ICU admission, respiratory specimens were collected from each patient and
tested for the 2009 influenza A(H1N1) virus. Most samples nationwide were submitted
initially to a central reference laboratory to perform a real-time polymerase-chain-
reaction (RT-PCR) analysis. Many could not be analyzed, however, because diagnostic
laboratories soon became overwhelmed. As of September 25, 2009 the national health
authorities had made the announcement that the novel 2009 influenza A(H1N1) virus
had displaced other respiratory viruses in patients 5 years or older and, together with
other unidentified influenza A viruses, constituted 93.4% of the samples processed (2).
A seasonal influenza A virus was found in fewer than 2% of the samples. In view of
this information, included in the study were both probable and suspected cases (8) that
fulfilled the criteria of ILI and acute respiratory failure necessitating MV. Samples were
also analyzed for the diagnosis of concomitant bacterial pneumonia.
The following data were also recorded: severity of illness by the APACHE II
score, age, gender, underlying diseases (defined as: immunosuppression, COPD;
asthma, diabetes, chronic heart failure, chronic renal failure, cirrhosis), vaccination for
seasonal influenza A within the current year, pregnancy or childbirth, habitual smoking,
height and estimated or measured body weight for body-mass-index [BMI] calculation;
or the absence of any risk factor. Obesity was defined as a BMI >30. We recorded the
time in days from symptom onset to hospital admission and from hospital admission to
MV initiation; the place in which MV was started (e. g., the ICU; the Emergency
Department (ED), or the Coronary Care Unit (CCU); and, finally, the time from
hospital admission to ICU admission. The extension of lung infiltrates on chest X-ray
Page 8 of 55
was registered as the number of quadrants involved and the Lung Injury Score
On a daily basis, we collected the results of arterial blood gases, oxygenation
variables, progression to ARDS (10), and data of MV, which included the use of non-
invasive ventilation (NIV), the concurrent use of MV adjuvants (recruitment
maneuvers, prone positioning, or tracheal gas insufflation (TGI), the occurrence of
ventilator-associated pneumonia (VAP), and the need for inotropic drugs. The use and
dosage of oseltamivir—the only neuraminidase inhibitor available in Argentina—along
with the treatment of possible concurrent bacterial pneumonia were recorded as well.
Newly developed acute kidney injury requiring hemodialysis and measurement of
creatine-kinase levels (IU/L) were also registered.
The main measurement with respect to outcome was hospital mortality. The
lengths of MV, of ICU, and of hospital stay were calculated.
The descriptive statistics used were the means plus or minus standard deviations,
or the medians and interquartile ranges (IQR) for continuous variables of normal and
nonnormal distributions, and frequency analysis (as percentages) for categorical data.
The main comparisons performed were between survivors and nonsurvivors by means
of unpaired t test, Wilcoxon ranksum test, and either Fisher’s exact test or Chi-square
test, as appropriate. A P value of <.05 was considered significant. The proportions of
confirmed, probable, and suspected cases between survivors and nonsurvivors were
also explored. The incidence of bacterial pneumonia, and especially that of
Page 9 of 55
Streptococcus pneumoniae, was analyzed in confirmed vs. nonconfirmed (probable +
A bivariate analysis for hospital mortality was performed and variables showing
a P value of <.20 included in a multivariable logistic-regression analysis in search of
independent predictors of hospital mortality. A predictive model was built, and the
goodness-of-fit assessed with the Hosmer-Lemeshow test. Discrimination of the model
was evaluated by the area under a receiver-operating characteristic (ROC) curve. A
Kaplan-Meier curve was constructed to evaluate survival over the follow-up period.
All analyses were performed with STATA 9 software.
Since no intervention was performed, informed consent was waived by
institutional review boards.
Characteristics of the hospitals.
A brief description of the SATI and of some characteristics of the participating
centers is displayed in the Online Supplemental Data (Tables E1 and E2). Thirty-five
medical-surgical ICUs participated in the study; all constituting centers of high-acuity
care for critically ill patients. Fourteen ICUs (40%) belonged to university or
university-affiliated hospitals. The mean numbers of hospital and ICU beds were
216±143 and 13±10, respectively. The annual admissions to the ICUs were 709±539,
while 45%±20 of the patients usually require MV.
Clinical characteristics of the patients.
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Between June 6 and August 28, 2009, 337 adult patients with confirmed,
probable, or suspected cases of 2009 influenza A(H1N1) with acute respiratory failure
requiring MV were admitted to 35 ICUs. Most initiated MV in the ICU itself. The
collection of all data performed in 214 patients was prospective (60%, admitted after
June 29), while in the remaining the registry was partially prospective. Hospital and
ICU admissions were more frequent between June 21 and July 12, peaking on June 28
and then gradually decreasing (Fig. E1).
Since no differences in mortality were found among confirmed, probable, and
suspected cases (Table 1) the population was analyzed as a single group.
In all but two patients, respiratory samples were obtained with nasopharyngeal
swabs or tracheal aspirates for detection of viruses and other microorganisms.
Treatment with oseltamivir was given to 98% of patients, with 60% receiving 300
mg/day. The frequency of use and doses were similar in both survivors and
nonsurvivors. In all cases, antibiotic treatment for possible associated bacterial and
atypical pneumonia was started. Prior seasonal influenza vaccination was infrequent.
The epidemiological characteristics, severity of illness, and usual risk factors for
2009 influenza A (H1N1) for the whole population, as well as the comparisons between
survivors and nonsurvivors, are displayed in Table 1. Of note, patients were middle-
aged and predominantly male, especially in the nonsurvivor group. The most frequent
previous conditions found in 64% of the patients were habitual smoking, obesity,
COPD, and immunosuppression.
Pregnancy was common (N = 22; 7%), with 17 of the pregnant women being in
the third trimester, 4 in the second, and 1 in the first (ending in a spontaneous abortion).
Page 11 of 55
The most frequent comorbidities were asthma (N = 3) and diabetes (N = 1), and none of
these patients had received a prior seasonal influenza vaccination.
There were no differences in the distribution between survivors and nonsurvivors
with respect to underlying conditions. A risk factor could not be identified in 36% of
the patients. These latter were younger (41±16 vs. 50±17 years, P <.001) and had lower
APACHE II scores (16±7 vs. 19±8, P <.001). In the nonsurvivors, the time from
hospital admission to ICU admission was significantly longer (Table 2).
Respiratory compromise and ventilation support.
Most of the physiological variables were greatly compromised, and the whole
cohort displayed a high incidence of ARDS, extensive infiltrates on chest x-ray, and a
marked alteration in oxygenation, with the need for intensive ventilation support and
the use of MV adjuvants (Table 3). In nonsurvivors the incidence of ARDS was higher
than in survivors (96% vs. 82%, P <.001). Death was associated with a more profound
hypoxemia upon admission (PaO2/FIO2114 [70-188] vs. 152 [109-210], nonsurvivors
vs. survivors, P <.001); lower worst PaO2/FIO2values (80 [61-121] vs. 126 [98-164], P
<.001), a higher maximal PEEP (14±5 vs. 12±4 cm H2O, P <.001), and a more frequent
use of salvage therapies to reverse refractory hypoxemia; such as prone positioning,
recruitment maneuvers, and TGI (Table 3). One hundred fifty patients (45%) showed
PaO2/FIO2≤ ≤100, and this characteristic was more frequent in nonsurvivors (65% vs.
28%, RR 2.26, P <.001). This subgroup of severely compromised patients is further
described in the Online Data Supplement (Table E 3).
Page 12 of 55
NIV was used in 64 patients (19%) and was associated with a better outcome.
None of the patients received extracorporeal membrane oxygenation (ECMO), high-
frequency oscillatory ventilation (HFOV), or inhaled nitric oxide.
Nonpulmonary organ involvement.
The high incidence of shock was remarkable (72% of patients were on
inotropics) especially in the nonsurvivors (83% vs. 62%; P <.001). Renal failure
requiring hemodialysis occurred in 17% of patients, more commonly in the
nonsurvivors (25% vs. 9%, P <.001). Age, shock, and creatine-kinase levels upon
admission were significantly higher in patients undergoing hemodialysis (Table 4).
Coexistent bacterial pneumonia on admission was diagnosed in 80/325 patients
(25%), with the proportions being similar between confirmed and nonconfirmed cases
(Table 5). Within the entire group, 28 patients (9%) had pneumonia caused by
Streptococcus pneumoniae (6% in the survivors vs. 11% in the nonsurvivors, P = .11).
Ventilator-associated pneumonia developed in 84/325 patients (26%); Acinetobacter
baumanii was the most frequently isolated microorganism (N=35), followed by
Pseudomona aeruginosa (N = 22).
Outcomes and predictors of mortality.
One hundred fifty-six patients died (46%; Table 1 and Fig. 1); 62% were male,
and 67% had a previous medical condition, of which habitual smoking and obesity were
Page 13 of 55
the most frequent. Patients with immunosuppression died earlier (Fig. 1). Mortality was
distributed evenly across all age categories, without significant differences among them
(Fig. E2). Logistic-regression analysis identified the APACHE II score, the lowest
PaO2/FIO2, the use of inotropics, hemodialysis, prone positioning, and concomitant
pneumococcal pneumonia as independent predictors of hospital mortality (Table 6).
The predictive model showed good calibration (Hosmer-Lemeshow test = 10.85; P =
.21) and discrimination (area under ROC curve = .81).
Comparison with other studies
A systematic comparison of epidemiological, clinical, and outcome data between
this study and others (11-17) is shown in Table E4 of the Online Data Supplement. The
relationship between outcome and the period elapsing from symptom onset to hospital
admission for our study and other studies (11-17) is included in Table E5 of the Online
We report on a large cohort of critically ill patients admitted to 35 ICUs of
Argentina with suspected, probable, or confirmed 2009 influenza A(H1N1) and with
acute respiratory failure requiring MV. These severely compromised patients were
typically middle-aged adults, predominantly male, and presented with great
physiological deterioration, as evidenced by high APACHE II score, bilateral lung
infiltrates on chest x-ray, and deep hypoxemia. Nonpulmonary organ dysfunctions
Page 14 of 55
requiring extracorporeal support, such as shock and renal failure, were frequent; and
mortality was correspondingly high. This evolution occurred rapidly after about one
week of ILI symptoms, a pattern that seems to be a hallmark of severe disease observed
also in other studies (11, 12).
With respect to the patients’ characteristics, 74% were between 25 and 64 years
old, but 15% were older than 65. In contrast to the usual target population of seasonal
influenza, in which children and adults aged >65 years are preferentially affected (18), a
lower mean age has been a consistent finding in populations affected by this 2009
influenza A(H1N1) virus (4, 5, 11-17). Still, the mortality was comparable across all
age groups (Figure E2).
Similar to what has been described in other reports, nearly two-thirds of the
patients had previous medical conditions (13, 14, 16); and, as in seasonal influenza,
habitual smoking and chronic lung disease were the most frequent The COPD
prevalence of 18%, however, was not higher than in the general population for the
region (20). Obesity, a novel risk factor for influenza A described during the 2009
pandemic (21), occurred in 24% of the patients and was comparable to the prevalence
of this condition in Argentina (22). Thus, obesity and chronic respiratory disease were
the two main risk factors for this novel influenza virus, which has been a consistent
report (11-17; Table E5). Immunosuppression was also frequent, and mortality occurred
earlier in this subgroup. Finally, 36% of the patients were in a previous state of good
health. The prevalence of pregnancy (7%) (11-17, 23) was higher than in the general
population (1.7% for Argentina; 24). Pregnancy is a well known risk factor for seasonal
influenza and had caused significant morbidity and mortality during past epidemics and
Page 15 of 55
pandemics (25, 26). Notably, none of the pregnant women had been previously
vaccinated for seasonal influenza.
Severe respiratory involvement was a key feature of patients infected with the
2009 influenza A(H1N1) virus and admitted to the ICU. MV was initiated generally
during the first day of hospital admission, mostly in the ICU. In 24% of the patients,
intubation occurred in other hospital locations, such as the ED or the CCU, reflecting
the acuity of the condition on admission along with the degree of congestion of the
acute-care facilities that was so frequent during the outbreak. Extensive radiological
lung infiltrates and profound hypoxemia requiring high levels of ventilation support
were the rule and were more prominent in nonsurvivors. In contrast to what is usually
described in epidemiological series of ARDS (27, 28), in which multiple organ
dysfunction is the main cause of death, in ARDS caused by the 2009 influenza
A(H1N1) virus, mortality was also highly associated with refractory hypoxemia. This
novel virus elicits a more pronounced low-tract respiratory disease in mice, ferrets, and
primates than do seasonal H1N1 viruses (29, 30). In addition, necropsy studies revealed
diffuse alveolar damage, necrotizing bronchiolitis, intense alveolar hemorrhage, and
evidence of lung abnormal immune response (31).
NIV was used in 19% of patients at any time, in contradiction to
recommendations regarding possible aerosolization of viral particles (32, 33), and was
associated with a better outcome—possibly because attending physicians selected NIV
use for the less hypoxemic patients. NIV utilization has also been reported in other
series (11, 12, 16).
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Nonpulmonary organ involvement was unusually high. For example, inotropics
were used in 72% of the patients—in comparison to 32% , 58.6% , 62.5% (11, 12, 16),
and 69% in nonsurvivors in whom autopsy was performed (31),—or no use at all (13,
14) (Table E4). Another striking finding was the high frequency of acute kidney injury
requiring hemodialysis (17% of the patients). Three studies described this complication
(16, 17, 31)—one reporting a high mortality (17) and another being an autopsy series
from Brazil (31)—though less severe forms of renal dysfunction have also been
described (12; Table E4). Aside from shock, another possible concurrent cause of renal
failure is rhabdomyolysis, a complication that has been described in seasonal influenza
mostly in children (34). Accordingly, in our patients requiring hemodialysis, creatine-
kinase levels were significantly increased. Up to the present moment, there is no
evidence of direct viral damage to the kidney (31, 35).
Bacterial coinfection on admission has long since been reported in seasonal
influenza and is one of the presumed causes of death in pandemics (31, 35-37). A
synergistic interaction between bacteria and the influenza viruses has been described—
it involving an augmented viral replication and an increased ability to bind and invade
bacteria, especially S. pneumoniae, resulting in a globally increased inflammatory
response (31, 35, 38). In recent years, this complication is apparently rising (39). We
observed a 25% incidence of bacterial pneumonia on admission, and this proportion
was equal in both survivors and nonsurvivors. Coinfection with S. pneumoniae,
however, worsened the prognosis, despite concurrent antibiotic treatment on admission.
The mortality figure of 46% observed here is high, but we chose to focus on only
the subgroup comprising the sickest adult patients (40), those on MV. Reported
Page 17 of 55
mortalities are of 14.3% (11, 13), 21% (41), 25% (16), and 41.4% (12). Most series
report on general ICU mortality at 28 days (11, 12) whether patients were or were not
on MV; and on adult and pediatric patients together (Table E4). This last group has a
better prognosis (11). The standard consideration of 28-day mortality (12, 11) could
also cause a transient underestimation of deaths (11). By contrast, we followed up
patients all the way to either death or discharge. In a U. S. cohort of 272 hospitalized
patients (14), only 7% of the total died; but, of the 67 patients that had been admitted to
the ICU, 19 out of the 42 on MV died (45%). The distribution of different organ
failures among diverse populations could explain these differences: For example, acute
kidney injury—it very frequent in our study—is a well known risk factor for death in
the critically ill (42). Mortality rates for combined acute kidney injury and acute lung
injury might exceed 80% in critically ill patients (43). ECMO, a rescue therapy not
currently available in Argentina, has been associated with a better outcome (40), which
might also explain these results.
In the present study, the period from symptom onset to hospital admission was
about 6 [3-8] days, similar to the Mexican study (6 [4-8]); (12), but longer than the
Australian/New Zealand and Canadian reports (4 [2-7] days for both) (11,13). Longer
symptom onset–hospital admission periods were associated with increasing mortality
(Table E5). Differences in the accessibility to health-care facilities along with differing
perceptions of disease severity on the part of both the patients and the attending
physicians could account for these discrepancies. Unfortunately, since our study was
not designed to assess the relationship between the time of disease onset and the start of
Page 18 of 55
oseltamivir treatment, we cannot discard the possibility that the length of this interval
could be a yet-undetermined factor affecting outcome.
The subgroup of pregnant or postpartum patients also displayed a high mortality:
10 out of these 22 patients died (45%), consistent with a recent study from California
(44) where, of 94 pregnant or postpartum patients with 2009 influenza A(H1N1), 22
were admitted to the ICU, 16 required MV, and 8 died (50%), once again underscoring
the increased risk of severe disease within this subpopulation (11,13).
Finally, by the use of logistic-regression analysis, we identified APACHE II, the
lowest PaO2/FIO2, prone positioning, use of inotropics, hemodialysis, and coinfection
with S. pneumoniae as independent predictors of mortality. Thus, there is an association
of global severity of disease on admission with worsening oxygenation and
nonpulmonary organ failures affecting outcome. It is striking that pneumococcal
infection, long since considered the cause of death in past pandemics, is also prognostic
in this model.
The strength of this study lies in that it involves the second largest cohort of
adult mechanically ventilated patients with the 2009 influenza A(H1N1)—with these
cases described and analyzed in great detail. In addition, this is the first study
identifying independent predictors of mortality in the most severely compromised
subgroup of patients: those on MV. Other complications, such as shock and renal
compromise, are also characterized. The information was collected in a standardized
form along with the ongoing pandemic, so that most data were recorded prospectively.
This study also has its limitations: the high frequency of renal failure requiring
hemodialysis might be a regional characteristic; so findings might not be generalizable
Page 19 of 55
to other populations. No data on the timing of oseltamivir use with respect to symptom
onset was registered. Not all the patients were confirmed cases by RT-PCR analysis;
but since there were no differences in mortality between confirmed and nonconfirmed
cases, both categories were included. In this regard, other studies have used a similar
approach (12). Furthermore, difficulties in the availability of confirmatory diagnoses
once a pandemic is in progress have been well described (11).
In conclusion, this study highlights important points deserving consideration for
future health-resource planning in similar scenarios: First, late admission to the ICU is
associated with a greater likelihood of nonsurvival; so planning for an increase in ICU
beds in advance seems warranted, especially when a great volume of patients is
anticipated (45, 46). We, as others (13), have registered that the peak in admissions to
the ICU is to be expected 4 to 6 weeks after the first case. Second, limited diagnostic
resources should be redirected to the most severe cases in order to improve general
management and decrease uncertainty in the health-care workers and in patients' and
their relatives. Third, the identification of key risk factors will aid in health-resource
preparedness in general and in vaccination planning in particular. Fourth, efforts should
be targeted at improving vaccination against seasonal influenza in pregnant women
since they constitute a subpopulation at particular risk for all types of influenza A.
Finally, the need for sufficient equipment appropriated for advanced ventilation support
should be considered, given that mortality was highly associated with refractory
Page 20 of 55
The Registry of the Argentinian Society of Intensive (SATI). Collaborative Clinicians:
Javier Osatnik (Hospital Aleman, Buenos Aires), Miguel Blasco (Hospital Britanico, Buenos
Aires ); Martin Deheza (Hospital Rivadavia, Buenos Aires); Guillermo Chiappero (Hospital
Universidad Abierta Interamericana, Buenos Aires ); Mario Kenar (Clínica San Camilo,
Buenos Aires ), Mariano Setten (CEMIC, Buenos Aires ), Marcos Zec Baskard (Hospital Velez
Sarsfield, Buenos Aires ); Fernando Saldarini (Hospital Santojanni, Buenos Aires ). Fernando
Villarejo (Clínica Olivos, Olivos); LiIiana Aguilar, Daniel Pezzola (Hospital Nacional
Alejandro Posadas, El Palomar); Damian Violi; Martin Lugaro (Hospital Guemes, Haedo);
Marina Chuburu (Hospital San Juan de Dios, La Plata); Pablo Gomez, Marcelo Palavecino
(Sanatorio Juncal, Temperley); Javier Alvarez, Pablo Pratesi (Hospital Universitario Austral,
Pilar); Maria Eugenia Gonzalez (Hospital Privado de la Comunidad, Mar del Plata); Daniel
Fainstein (Sanatorio del Sur, Bahia Blanca). Graciela Zakalik, Ariel Chena (Hospital
Lagomaggiore, Mendoza); Jorge LLensa (Clínica Cuyo, Mendoza). Alan Zazu, Luciano
Capponcelli (Clinica de Especialidades de Villa María ,Córdoba). Sergio Benítez (Hospital San
Carlos, Bariloche). Daniel Rovira (Sanatorio Julio Corzo, Rosario).
Page 21 of 55
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Page 28 of 55
Figure 1. Survival curve of patients with 2009 Influenza A (H1N1).
A: For the entire population.
B. Grouped according to the presence of immunosuppression.
Page 29 of 55
TABLE 1. EPIDEMIOLOGY, RISK FACTORS AND OSELTAMIVIR USE IN THE
ENTIRE POPULATION, AND COMPARISONS BETWEEN SURVIVORS AND NON-
47 ± 17 47 ± 17 46 ± 17
90/91 (50/50) 59/97 (38/62) .03
APACHE II score
18 ± 7 16 ± 6 20 ± 8
.67 prob. vs.
.52 susp. vs.
Previous seasonal influenza
14/334 (4) 7/180 (4) 7/157 (5) .77
Habitual smoking 49/191 (26) 26/102 (26) 23/89 (26) .96
COPD 61/337 (18) 33/181 (18) 28/156 (18) .81
Asthma 18/337 (5) 9/181 (5) 9/156 (6) .75
Immunosuppressiona 50/332 (15) 21/176 (12) 29/156 (19) .09
Obesity (BMI > 30) 80/337 (24) 39/181 (22) 41/156 (26) .31
Diabetes 41/337 (12) 23/181 (13) 18/156 (12) .74
Chronic heart failure 35/337 (10) 17/181 (9) 18/156 (12) .52
Page 30 of 55
Chronic renal failure in
15/337 (4) 7/181 (4) 8/156 (5) .58
Cirrhosis 9/337 (3) 3/181 (2) 6/156 (4) .21
Pregnancy 22/337 (7) 12/181 (7) 10/156 (6) .93
No known risk factor 121/336 (36) 71/181 (39) 51/156 (33) .24
Concomitant pneumonia with
S. pneumoniae on admission
28 (8.3) 11 (6.1) 17 (10.9) .11
Oseltamivir use 328/336 (98) 178/181(98) 150/155 (97) .35
.58 150 vs. 300
.21 <150 vs. 300
Data are expressed as number, (%), or mean ± standard deviation
Abbreviations: APACHE; Acute Physiology and Chronic Health Evaluation; prob., probable;
conf., confirmred; susp., suspected; COPD, Chronic obstructive pulmonary disease, BMI;
body mass index, calculated as weight in kilograms divided by height in squared meters..
a Includes oncohematologic disease (leukemia, lymphoma and others); bone marrow
transplantation; solid organ transplantation; human immunodeficiency virus infection;
treatment with immunosuppressants, radiation or chemotherapy; recent treatment with high
dose corticosteroids, or prolonged treatment with a daily dose of, or equivalent to, 1 mg/kg or
40 mg/day of prednisone.
Page 31 of 55
TABLE 2. DIFFERENT TIME PERIODS ELAPSING BETWEEN HOSPITAL
ADMISSION, ICU ADMISSION AND ONSET OF MECHANICAL VENTILATION
Days from symptom start
to hospital admission
6 [3-8] 6 [3-7] 6 [4-10] .13
Days from hospital
admission to start of MV
1 [0-2] 0.5 [0-12] 1 [0-2] .33
Days from hospital to
0 [0-2] 0 [0-1,5] 1 [0-2] .05
Data are expressed as median and interquartile ranges [IQR].
Abbreviations: MV, mechanical ventilation; ICU, Intensive Care Unit.
Page 32 of 55
TABLE 3. PHYSIOLOGICAL AND MECHANICAL VENTILATION VARIABLES AND
Initiation of MV
ED vs. ICU .15
CCU vs. ICU
Lung injury score
2.62 ± 0.8 2.48 ± 0.7 2.78 ± 0.8
ARDS (AECC definition) 295/334 (88) 147/180 (82) 148/154 (96) <.001
Lung infiltrates on CXR
(number of quadrants)
2.87 ± 1.03 2.83 ± 1.03 2.90 ± 1.03 .68
Admission PaO2FIO2 140 [87-200] 152 [109-210] 114 [70-188] <.001
Lowest PaO2FIO2 107 [75-150] 126 [98-164] 80 [61-121] <.001
151 (45) 50 (28) 101(65) <.001
Admission PEEP (cm H2O)
10 ± 4 10 ± 4 11 ± 4
Admission PCO2 (mmHg)
44 ± 15 43 ± 15 45 ± 16
Maximal PEEP (cm H2O)
13 ± 5 12 ± 4 14 ± 5
Non-invasive ventilation 64/337 (19) 43/181(24) 21/156 (13) .02
Tracheal gas insufflation 16/333 (5) 1/177 (0.6) 15/156+ (10) <.001
Recruitment maneuvers 134/333 (40) 56/177 (32) 78/156 (50) <.01
Prone positioning 43/334 (13) 8/178 (4) 35/156 (22) <.001
Use of inotropic drugs 242/336 (72) 113/181 (62) 129/155 (83) <.001
Page 33 of 55
Hemodialysis 55/331 (17) 16/176 (9) 39/155 (25) <.001
Creatin-kinase (IU/L) 434 [107-1099] 255 [93-643] 754 [171-1995] 0.03
Length of MV (days) 10 [5-16] 11 [7-18] 4 [1-9] <.01
Length of ICU stay (days) 12 [6-20] 15 [9-22] 9 [4-15] <.001
Length of Hospital stay (days) 17 [8-29] 23 [16-36] 9 [4-17] <.001
Data are expressed as number, (%), or mean ± standard deviation, or median and interquartile
Abbreviations: MV, mechanical ventilation; ICU, Intensive Care Unit; ED, Emergency
Department; CCU, Coronary Care Unit; ARDS, Acute respiratory distress syndrome; AECC,
American –European Consensus Conference; CXR, chest X-ray film; PaO2, arterial partial
oxygen pressure; FIO2, Fraction of inspired oxygen; PEEP; positive end-expiratory pressure;
IU/L, international units per liter.
Page 34 of 55
TABLE 4. CHARACTERISTICS OF PATIENTS REQUIRING RENAL SUPPORT
Age 45.9 ± 17,1 51.3 ± 15,4 .03
Use of inotropic drugs 191 (69) 49 (89) .003
CK (IU/L) on day 1* 265 [94 - 765] 927 [144 - 1856] .016
Data are expressed as number, (%), or mean ± standard deviation, or median and interquartile
* Data of 98 patients.
Abbreviations: CK; Creatin Kinase levels; IU/, IU/L, international units per liter.
Page 35 of 55
TABLE 5. COEXISTENT RESPIRATORY INFECTIONS.
P Incidence in
n 325 175 150 132 190
80 (25) 40 (23) 40 (27) 0.43 37 (28) 43 (22) .19
VAP in the
84 (26) 46 (26) 38 (25) 0.78 33 (25) 51 (27) .77
Data are expressed as number, (%).
Abbreviations: VAP, Ventilator-associated pneumonia.
Page 36 of 55
TABLE 6. INDEPENDENT PREDICTORS OF HOSPITAL MORTALITY
APACHE II 1.08* <.001 1.03-1.12
Lowest PaO2FIO2 .98** <.001 .98-.99
Use of inotropic drugs 2.32 .01 1.23-4.38
Hemodialysis 2.85 <.01 1.30-6.25
Prone positioning 4.07 <.01 1.55-10.68
Coinfection with S.pneumoniae at
2.72 .04 1.05-7.06
Abbreviations: APACHE, Acute Physiology and Chronic Health Evaluation; PaO2, arterial
partial oxygen pressure; FIO2, Fraction of inspired oxygen.
* per point APACHE II
** per point PaO2FIO2
Page 37 of 55
Page 38 of 55
PANDEMIC 2009 INFLUENZA A(H1N1) IN ARGENTINA: A STUDY OF 337
PATIENTS ON MECHANICAL VENTILATION.
ONLINE DATA SUPPLEMENT
AUTHORS: Elisa Estenssoro, Fernando G. Ríos, Carlos Apezteguía, Rosa Reina, Jorge Neira, Daniel H.
Ceraso, Cristina Orlandi, Ricardo Valentini, Norberto Tiribelli, Matías Brizuela, Carina Balasini,
Sebastián Mare, Gustavo Domeniconi, Santiago Ilutovich, Alejandro Gómez, Javiera Giuliani, Cecilia
Barrios; and Pascual Valdez,
on behalf of the Registry of Argentinian Society of Intensive Care (SATI).
Page 39 of 55
ON-LINE SUPPLEMENTAL TEXT
CHARACTERISTICS OF THE ARGENTINIAN SOCIETY OF INTENSIVE CARE
MEDICINE (SATI; SOCIEDAD ARGENTINA DE TERAPIA INTENSIVA).
The SATI is the scientific society that represents all members of the critical care team in
Argentina. It was funded in 1971 and has more than 1200 members that include critical care
physicians, respiratory therapists, nurses and biochemists.
The President of the Society is elected every two years by full and associated members during the
Annual General Assembly held during the national congresses. Activities are organized by an
Executive Committee (Comisión Directiva) by way of the Departments of Education, Systems
and Research. The members of the SATI participate in the different areas of Critical Care through
14 different Expert Committees.
More information about the SATI can be found at the official society website www.sati.org.ar
Page 40 of 55
TABLE E1. CHARACTERISTICS OF THE CENTERS PARTICIPATING IN THE
to the ICU
Sanatorio San Carlos 60 15000 6 350 30
Hospital Universitario CEMIC 200 9000 19 900 40
Hospital Fernandez 450 102674 10 700 80
Clínica San Lucas 60 4684 13 300 30
Clínica San Camilo 140 10000 14 1000 30
Hospital Privado del Sur de Bahía Blanca 104 11000 7 700 30
Sanatorio de los Arcos 124 15.690 16 980 16,7
Trinidad San Isidro 180 11530 20 1500 20
Trinidad Mitre 280 12460 20 750 30
Hospital Interzonal San Martín de La Plata 349 11895 16 320 68
Hospital San Juan de Dios de La Plata 129 2260 6 137 90
Hospital Nacional Alejandro Posadas 480 17880 42 1109 70
Hospital Pirovano 380 9848 8 381 75
Hospital Julio Mendez (ObSBA) 245 6552 19 370 55
Sanatorio de la Trinidad Palermo 220 13100 40 2400 30
Hospital Vélez Sarsfield 100 7330 8 450 60
Page 41 of 55
Sanatorio Victorio Franchin 227 16800 16 600 65
Hospital Rivadavia 350 10000 10 400 60
Hospital Interzonal de Agudos. Dr Luis
241 6000 12 560 51
Hospital de la Universidad Abierta
91 5350 9 450 43
Sanatorio Juncal 102 7610 16 950 20
Hospital Churruca 450 18000 18 710 30
Hospital Lopez Lima 137 7289 7 364 32
Hospital Lagomaggiore 408 14284 8 406 47,2
Hospital Alemán 212 9400 14 1450 42
Hospital Transito Cáceres de Allende 114 12484 12 1251 34
Clínica Olivos 47 4532 12 668 15
Clinica de Cuyo 60 4600 6 244 32
Hospital Italiano Garibaldi 95 7780 9 500 37
Hospital Julio Corzo 90 7800 10 510 36
Mean values 216 13435 13 709 45
SD 143 19431 10 539 20
Page 42 of 55
TABLE E2. PATIENTS INCLUDED IN THE STUDY, BY CENTER.
Percent Cumulative frequency.
Hospital Aleman, Buenos Aires 5 1.48 1.48
Hospital Austral. Buenos Aires 7 2.08 3.56
Hospital Britanico, Buenos Aires 9 2.67 6.23
Hospital CEMIC, Buenos Aires 19 5.64 11.87
Clinica Olivos, Provincia de Buenos
5 1.48 13.35
Hospital Guemes, Haedo, Provincia de
4 1.19 14.54
Hospital Privado de Comunidad, Mar
del Plata, Provincia de Buenos Aires
3 0.89 15.43
Hospital Lagomaggiore, Mendoza 4 1.19 16.62
Hospital Nacional Alejandro Posadas,
El Palomar, Provincia de Buenos Aires
49 14.54 31.16
Hospital Rivadavia, Buenos Aires 5 1.48 32.64
Page 43 of 55
Sanatorio Juncal, Buenos Aires 6 1.78 34.42
Sanatorio de los Arcos, Buenos Aires 7 2.08 36.50
Hospital Santojanni, Buenos Aires 7 2.08 38.58
Hospital Velez Sarsfield, Buenos Aires
11 3.26 41.84
Hospital Pirovano, Buenos Aires 15 4.45 46.29
Snatorio San Lucas, Buenos Aires 1 0.30 46.59
Hospital Churruca, Buenos Aires 17 5.04 51.63
Clinica de Especialidades, Cordoba 5 1.48 53.12
Hospital Fernández, Buenos Aires 7 2.08 55.19
Sanatorio del Sur, Bahia Blanca,
Provincia de Buenos Aires
6 1.78 56.97
Sanatorio Julio Corzo, Rosario 4 1.19 58.16
Hospital Interzonal San Martin La
Plata, Provincia de Buenos Aires
16 4.75 62.91
Hospital de la Universidad Abierta
Interamericana, Buenos Aires
6 1.78 64.69
Sanatorio Trinidad San Isidro,
Provincia de Buenos Aires
10 2.97 67.66
Page 44 of 55
Hospital Italiano Garibaldi,
10 2.97 70.62
Clínica Cuyo, Mendoza 1 0.30 70.92
Sanatorio Trinidad Palermo, Buenos
5 1.48 72.40
Hospital Francisco Lopez Lima,
General Roca, Río Negro.
23 6.82 79.23
Hospital San Juan de Dios. La Plata,
Provincia de Buenos Aires
7 2.08 81.31
Clinica San Camilo, Buenos Aires 4 1.19 82.49
Sanatorio Franchin, Buenos Aires 11 3.26 85.76
Sanatorio San Carlos, Bariloche 8 2.37 88.13
Sanatorio Trinidad Mitre, Buenos
10 2.97 91.10
Sanatorio Mendez, Buenos Aires 14 4.15 95.25
Hospital Transito Caceres, Córdoba 16 4.75 100.00
Total 337 100.00
Page 45 of 55
TABLE E3. CHARACTERISTICS OF PATIENTS WITH REFRACTORY HYPOXEMIA
(PaO2FIO2 ≤ ≤ ≤ ≤100)
PaO2FIO2 ≤ ≤ ≤ ≤ 100 PaO2FIO2 > 100 P value
N, (%) 151 (45) 186 (55)
Use of recruitment
107 (71) 27 (15) <.001
Use of prone position 40 (26) 3 (2) <.001
Use of tracheal gas
14 (9) 2 (1) <.001
Use of pressure-
74 (49) 63 (35) .009
Hospital mortality 101 (67) 55 (30) <.001
In Patients with deep hypoxemia, as exemplified by PaO2FIO2 ≤ 100, the use of extraordinary
measures to reverse it was significantly more frequent. Mortality in this subgroup and mortality
was accordingly higher.
Page 46 of 55
TABLE E4: COMPARISON OF EPIDEMIOLOGICAL DATA, CLINICAL CHARACTERISTICS AND OUTCOMES BETWEEN THE
ARGENTINIAN STUDY AND OTHER REPORTS
ARDS Shock AKI
N/A 52/48 1)Asthma/COPD
1) Chronic lung
2) Ever smoker
2) Obesity (29%)
9% 31.7% 48.8% Overall 103/608
103/456 on MV
29/136 on MV
at 60 days
Kumar et al*
168 136 32.3*
Cherit et al
Jain et al (4)
58 54 44*
67 42 29
7% 27% Overall 19/273
19/42 on MV
within 2 days
Louie et al
340 30<18 yr
N/A 51/49 1) Obesity (48%)
2) Chronic lung
10% 32% Overall 11%
95/193 adults on
8/24 on MV
Rello et al
32 24 36
27./73 1) Obesity(
1) Obesity (45%)
2) Obesity (24%)
6.3% 50% 62.5%
Ugarte et al
75 56 45
14 (1-35) 41/59
9.3% 44% 9.3 Overall 26%
44/56 7% 36% 88% 72% 17%
Only patients on
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MV: Mechnical ventilation
BMI: Body-mass index
ARDS: Acute respiratory distress syndrome
AKI: Acute kidney injury
Data are presented as mean ± standard deviation, median (range), or median IQR [.25-.75]
π Obesity was defined as a BMI > 30, unless specified
* Includes pediatric patients
** Mortality data are displayed as presented in each study. Mortality of patients on MV is calculated whenever the study authors provide the
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TABLE E5. COMPARISON OF THE PERIOD BETWEEN SYMPTOM ONSET AND
ADMISSION TO THE HOSPITAL, AND RELATION TO MORTALITY.
between symptom onset
and hospital amission
(Australia and New Zealand)
4 [2-7] 14.3%
Kumar et al* (2)
4 [2-7] 14.3%
Ugarte et al (7)
5 [1-15] 26%
Dominguez Cherit et al (3)
6 [4-8] 41.3%
6 [3-8] 46%
MV: mechanical ventilation
Data are presented as median [IQR], or median (range).
* The Argentinian study includes patients only on MV. The remaining studies are mixed cohorts
of ventilated and non -ventilated patients. As this period increases, mortality increases.
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