Factors associated with laboratory confirmation of suspected hantavirus pulmonary syndrome in southern Argentina: a retrospective observational case–control study

ABSTRACT

Objective.

To identify demographic, occupational, exposure, clinical, and laboratory factors independently associated with diagnostic confirmation of hantavirus infection by RT-PCR or IgM among patients with suspected hantavirus pulmonary syndrome evaluated in Río Negro and Neuquén, Argentina.

Methods.

A retrospective case–control study using emergency department records and epidemiological notification forms from public hospitals in Río Negro and Neuquén, Argentina, during 1996–2025. Cases were patients with suspected hantavirus pulmonary syndrome confirmed by RT-PCR detection of hantavirus RNA and/or hantavirus-specific IgM ELISA through a standardized laboratory confirmation pathway verified by the reference laboratory. Controls were suspected cases in whom hantavirus infection was ruled out through the same pathway. Demographic, occupational, exposure, clinical, laboratory, and chest radiography variables were analyzed. Logistic regression models were adjusted for age and sex; symptoms were mutually adjusted in the clinical block.

Results.

We included 325 suspected cases: 113 confirmed and 212 ruled out. Compared with no evident risk, the activity-based exposure scale showed strong associations for high-risk activity (aOR 156; 95% CI [10, 2 448]) and moderate-risk activity (aOR 33; 95% CI [2.4, 456]). Confirmed cases more often had elevated hematocrit (aOR 7.40; 95% CI [3.96, 13.8]), elevated lactate dehydrogenase (aOR 10.67; 95% CI [4.85, 23.3]), thrombocytopenia (aOR 11.08; 95% CI [5.59, 21.9]), and elevated creatinine (aOR 2.91; 95% CI [1.59, 5.34]). Severe respiratory failure/criteria for mechanical ventilation (aOR 5.58; 95% CI [3.16, 9.85]) and neurological symptoms (aOR 5.17; 95% CI [1.16, 28.0]) were independently associated with confirmation.

Conclusions.

Among patients with suspected hantavirus pulmonary syndrome evaluated in southern Argentina, structured exposure assessment and selected laboratory abnormalities were associated with laboratory confirmation. Given the study limitations, these hypothesis-generating findings may inform future development and prospective validation of clinical prediction tools.

Hantavirus pulmonary syndrome (HPS) is an uncommon but severe zoonosis responsible for acute respiratory failure and shock, with high case-fatality rates in the Americas, including the Southern Cone of South America. The etiological agents are rodent-borne orthohantaviruses, enveloped negative-sense single-strand RNA viruses with a tripartite genome comprising S, M, and L segments (1). In humans, infection occurs mainly through inhalation of aerosols contaminated with excreta from reservoir rodents. Family and community clusters compatible with person-to-person transmission have been reported for Andes virus (ANDV), although distinguishing interpersonal transmission from shared rodent or environmental exposure remains challenging (2–5).

In Argentina, multiple orthohantaviruses circulate, including ANDV, classified within the family Hantaviridae, genus Orthohantavirus, species Orthohantavirus andesense, and other viruses within the same species, such as Orán, Lechiguanas, and Buenos Aires viruses, among others. This circulation defines four endemic regions: South, Central-East, Northeast, and Northwest. In the southern endemic region, comprising the Andean Patagonia of Argentina and Chile, ANDV predominates, and its main reservoir is Oligoryzomys longicaudatus.

In this setting, sporadic outbreaks and family or community clusters have been described, with the usual seasonality in spring and summer and reported case-fatality rates of around 30% to 50% (3, 6). These characteristics, together with the occurrence of family and community clusters and the difficulty of distinguishing interpersonal transmission from shared environmental exposure, make HPS a public health problem whose impact is disproportionate to its incidence. The central challenge in clinical practice is that HPS often begins with a nonspecific prodrome, including fever, myalgia, headache, and gastrointestinal symptoms, which may last only a few days and then progress abruptly to the cardiopulmonary phase, characterized by capillary leak, noncardiogenic pulmonary edema, and hemodynamic instability (7–9). In endemic areas, this dynamic requires diagnostic and referral decisions to be made within a narrow time window, often before etiologic confirmation is available. At the same time, emergency departments face a complex balance: a broad suspicion threshold may increase overreporting and strain laboratory capacity, including reverse transcription polymerase chain reaction (RT-PCR)/serology and referral logistics, whereas a restrictive suspicion threshold may lead to underreporting and, more importantly, missed opportunities for early intensive monitoring and timely supportive care in patients who will rapidly progress to severe disease.

In this context, identifying clinical, demographic, occupational, and laboratory predictors associated with confirmation by RT-PCR or IgM ELISA could refine the selection of patients for testing, prioritize care pathways, and align resource use with actual risk (7, 10, 11). Although clinical suspicion criteria and laboratory confirmation criteria have been proposed (12–14), their performance and applicability often depend on local epidemiological patterns, exposure profiles, and the clinical threshold used to request confirmation. In the southern endemic region, where environmental and occupational exposures coexist with reported family and community clusters, it is particularly relevant to identify which variables most consistently distinguish confirmed cases among patients with an initial clinical suspicion.

The primary objective was to identify demographic, occupational, clinical, and laboratory factors independently associated with diagnostic confirmation of hantavirus by RT-PCR or IgM among patients with suspected HPS evaluated in Río Negro and Neuquén, Argentina. Secondary objectives were to describe baseline characteristics of confirmed and ruled-out suspected cases and to explore how routinely available variables could inform future development of clinical prediction tools. Ultimately, identifying these factors could contribute to more timely diagnostic prioritization, referral, and monitoring, while informing the future development of prediction tools for use in the southern endemic region.

METHODS

We conducted a retrospective case–control study based on the records of patients with clinical suspicion of HPS from emergency departments of public hospitals in the provinces of Río Negro and Neuquén, Argentina, covering the period 1996–2025. Because the study covered a long period, calendar time was considered descriptively to account for potential changes in notification practices, diagnostic availability, and clinical management. We included only patients treated in these jurisdictions with verifiable epidemiological notification forms and clinical records routinely generated after notification of suspected cases. Although initial suspicion and notification could originate in public emergency departments across the participating jurisdictions, patients with suspected HPS requiring referral or specialized management were referred to the corresponding reference centers: Hospital Provincial Neuquén “Dr. Eduardo Castro Rendón” in Neuquén, and Hospital Zonal Bariloche “Dr. Ramón Carrillo” in Río Negro. The jurisdictional distribution of included patients and the corresponding reference centers are summarized in Supplementary Table S1. Notification forms provided demographic, residence, occupational, epidemiological, and exposure information, whereas clinical records provided symptoms, timing of presentation, laboratory findings, radiographic findings, and clinical course variables when available. The study was reported according to the STROBE recommendations for observational studies, with emphasis on participant selection, variable definition, handling of missing data, and analytical strategy (15).

Definition of cases and controls

The population was classified according to a standardized laboratory confirmation pathway. Cases were defined as patients with clinical suspicion of HPS and confirmation by RT-PCR and/or IgM serology by ELISA. Controls were patients with an initial clinical suspicion in whom hantavirus infection was ruled out using the same diagnostic algorithm. Patients of all ages who met suspected case criteria and had an epidemiological notification form were included. Individuals with confirmed hantavirus infection in the previous six months, patients receiving immunosuppressive therapy at the time of clinical evaluation, and those in whom the final diagnosis required for classification as case or control could not be established with certainty were excluded (6, 16–17). The six-month interval was selected to reduce diagnostic ambiguity related to recent infection, persistent serological reactivity, or difficulty distinguishing a new suspected episode from a previous confirmed event.

Population, suspicion criteria, and data sources

A suspected case was defined according to national and local surveillance criteria as any patient with a history of usual residence in or travel to an endemic area who presented with fever lasting more than 24 hours associated with general symptoms, such as headache, myalgia, arthralgia, or malaise, and/or gastrointestinal symptoms, such as abdominal pain, diarrhea, or vomiting, with or without respiratory involvement (16). The dependent variable was diagnostic confirmation of hantavirus infection, defined by detection of hantavirus RNA by RT-PCR and/or hantavirus-specific antibodies by ELISA, confirmed by the National Reference Laboratory for Hantavirus at the National Institute of Infectious Diseases, INEI–ANLIS “Dr. Carlos G. Malbrán.”

Independent variables included demographic and occupational characteristics; usual residence and workplace classified as urban, peri-urban, or rural according to the epidemiological notification form or, when missing, the clinical record; exposure through risk activities; and clinical, laboratory, and radiographic variables from the first emergency department or hospital assessment whenever available. Time since symptom onset was defined as the interval between patient-reported symptom onset and the first clinical assessment leading to notification or diagnostic evaluation, and was categorized as <2 days, 3–5 days, or >6 days. Clinical symptoms were analyzed as recorded in the source documents. Laboratory and chest radiography variables were preferentially taken from the same initial assessment window; when same-day data were not available, the earliest value recorded during the initial evaluation was used. Laboratory categorical variables were defined as follows: thrombocytopenia, platelet count <100 000/mm³ or a decrease >20% within

24 h; elevated lactate dehydrogenase (LDH), >1 000 U/L; elevated hematocrit, >42%; elevated creatinine, >1.2 mg/dL; and elevated aspartate aminotransferase (AST), >250 U/L. Abnormal chest radiography was defined as unilateral or bilateral pulmonary infiltrates. Severe respiratory involvement was defined as severe respiratory failure or criteria for mechanical ventilation. Exposure through risk activity was operationalized using a five-level ordinal scale developed by the authors for this study and reconstructed from exposure domains routinely collected by provincial epidemiology teams when completing hantavirus notification forms and epidemiological investigation records, supplemented by clinical records when necessary. Level 0 indicated no evident risk; level 1, low-risk occasional outdoor or rural exposure; level 2, moderate-risk frequent rural work or recurrent activities near potential rodent habitats without visible excreta; level 3, high-risk frequent or prolonged activities with direct or indirect evidence of rodent presence; and level 4, very high-risk activities involving confirmed direct exposure or high probability of contact with rodent excreta, carcasses, rodent handling, clearly infested places, or close contact with confirmed hantavirus cases. The operational definitions of each level and examples of activities are presented in Table 1.

TABLE 1. Proposed activity-based exposure risk scale.

Value	Risk level	Associated activities
0	No evident risk	Urban work without evident exposure, no rural activities, and no contact with rodents.
1	Low risk	Occasional outdoor activities, such as camping in authorized sites, picnics, occasional recreational fishing, or sporadic contact with rural environments without clear evidence of rodents.
2	Moderate risk	Frequent rural work and activities, including basic agriculture, light cleaning of sheds or rural homes, occasional firewood collection, frequent or prolonged camping, or recurrent activities near potential rodent habitats but without direct contact with visible excreta.
3	High risk	Frequent and prolonged activities with direct or indirect evidence of rodent presence, including deep cleaning of sheds, attics, or storage areas with likely rodent presence; frequent brush clearing in rural areas; frequent firewood collection; or regular observation of rodents or excreta in nearby areas.
4	Very high risk	Activities involving confirmed direct exposure or high probability of contact with excreta, carcasses, or rodent handling, including capture or direct handling of rodents, intensive cleaning of clearly infested places with visible droppings or nests, frequent tasks in sheds or storage areas inhabited by rodents, or close contact with confirmed hantavirus cases.

Source: Activity-based exposure risk scale developed by the authors for this study, reconstructed from exposure domains routinely collected by provincial epidemiology teams when completing hantavirus notification forms and epidemiological investigation records, supplemented by clinical records when necessary.

Statistical analysis

A descriptive analysis was performed for all variables included in the study. Continuous variables were expressed as mean ± standard deviation (SD) with 95% confidence intervals (95% CI). For laboratory variables with skewed distributions, medians and interquartile ranges were also reviewed to assess the influence of extreme values. Categorical variables were described as absolute frequencies, proportions, and 95% CIs.

For bivariate analysis, continuous variables were compared between confirmed and ruled-out patients using Student’s t test for independent samples. Categorical variables were analyzed using the chi-square test. When 2×2 contingency tables had expected frequencies below 5, Fisher’s exact test was used. The corresponding statistic and two-sided p value were reported, with a statistical significance level of α = 0.05.

Subsequently, multivariable analyses were performed using binomial logistic regression models, with diagnostic confirmation as the dependent variable (1 = confirmed; 0 = ruled out). For each independent variable, an adjusted model was built by forcibly including age as a continuous variable and sex as male/female as potential confounders. For clinical parameters, symptoms were also mutually adjusted by including them together in the model, given that the presence of one symptom may be associated with others. For the analysis of clinical, laboratory, and exposure variables, available data were used for each variable, meaning denominators varied according to information availability; no multiple imputation of missing data was performed. Missing data were summarized by variable and diagnostic group to assess whether missingness differed between confirmed and ruled-out suspected cases. In addition, the multivariable models included covariates defined a priori, and a sensitivity analysis was conducted to explore potential collinearity among predictors, including related clinical and laboratory variables, in order to avoid unstable estimates and overfitting. Results are expressed as adjusted odds ratios (aORs) with 95% CIs. For continuous laboratory variables, aORs represent the change in odds associated with a one-unit increase in the original measurement scale; therefore, these estimates were interpreted cautiously and alongside clinically defined categorical thresholds. All statistical analyses were performed using R software, version 4.3.3.

Ethical considerations

The protocol was evaluated and approved by the Research Ethics Committee of the Province of Río Negro [MSRN Nº 218455-S-2025]. For data from Neuquén, the protocol was submitted for review and approval to the corresponding ethics committee, and extraction and use of de-identified data were authorized by the Ministry of Health of Neuquén through its Directorate of Epidemiology. Because this was a retrospective study based on routinely collected clinical and epidemiological records, with no direct contact with participants and use of de-identified data, the requirement for individual informed consent was waived as part of the ethics approval and authorization process. Data handling complied with National Law 25 326 on Personal Data Protection, the Declaration of Helsinki, and the International Ethical Guidelines for Health-related Research Involving Humans of CIOMS/WHO.

RESULTS

A total of 325 patients with clinical suspicion were included, of whom 113 were confirmed and 212 were ruled out. Patients came predominantly from Neuquén (210/325, 64.6%) and Río Negro (79/325, 24.3%); among confirmed cases, 54/113 (47.8%) were from Neuquén and 44/113 (38.9%) from Río Negro, whereas among ruled-out suspected cases, 156/212 (73.6%) and 35/212 (16.5%), respectively, came from these provinces. The remaining records corresponded to a small number of patients from other jurisdictions, including Chubut, Buenos Aires, other provinces, and Chile. Additional details on the referral centers and jurisdictional distribution are provided in Supplementary Table S1. Analyses were performed using available data for each variable, and denominators therefore varied across covariates. Table 2 presents n/N (%), bivariate test results, and adjusted ORs with 95% CIs.

TABLE 2. Baseline characteristics and factors associated with confirmation of hantavirus pulmonary syndrome among patients with clinical suspicion: bivariate comparison and adjusted logistic regression models (total N = 325).

Variable	Confirmed n/N (%)	Ruled out n/N (%)	Method	Statistic	Bivariate p value	aOR	95% CI	Adjusted model p value
Age, years	36.71 ± 16.20	38.64 ± 18.00	t	0.95	0.35	0.99	0.98, 1.00	0.35
Male	85/113 (75.2%)	143/212 (67.5%)	χ2	2.5	0.29	1.40	0.82, 2.39	0.21
Female	28/113 (24.8%)	68/212 (32.1%)				0.71	0.41, 1.21	0.21
Usual residence			χ2	3.04	0.219
Urban	50/113 (44.2%)	90/164 (54.9%)				0.69	0.40, 1.20	0.13
Rural	48/113 (42.5%)	57/164 (34.8%)				1.43	0.83, 2.46	0.19
Peri-urban	15/113 (13.3%)	17/164 (10.4%)				1.83	0.82, 4.00	0.19
Workplace setting			χ2	14.26	<0.001
Urban	40/101 (39.6%)	71/109 (65.1%)				0.67	0.39, 1.12	0.13
Rural	43/101 (42.6%)	24/109 (22.0%)				1.49	0.88, 2.50	0.13
Peri-urban	18/101 (17.8%)	14/109 (12.8%)				1.66	0.75, 3.65	0.20
Activity-based exposure			χ2	25.36	<0.001
High risk	48/87 (55.2%)	4/22 (18.2%)				156	10, 2 448	<0.001
Moderate risk	23/87 (26.4%)	6/22 (27.3%)				33	2.4, 456	<0.01
Very high risk	10/87 (11.5%)	5/22 (22.7%)				9.86	0.79, 122	0.07
Low risk	5/87 (5.7%)	1/22 (4.5%)				44.7	1.6, 1 244	0.02
No risk	1/87 (1.1%)	6/22 (27.3%)				0.01	0.001, 0.09	<0.01
Time since symptom onset			χ2	31.1	<0.001
<2 days	17/113 (15.0%)	97/212 (45.8%)				0.17	0.08, 0.30	<0.01
3–5 days	64/113 (56.6%)	82/212 (38.7%)				0.77	0.42, 1.42	0.41
>6 days	32/113 (28.3%)	33/212 (15.6%)				1.29	0.70, 2.36	0.41
Clinical parameters
Influenza-like syndrome	95/105 (90.5%)	180/212 (84.9%)	χ2	1.9	0.17	1.49	0.69, 3.19	0.30
Fever	94/99 (94.9%)	174/197 (88.3%)	χ2	3.38	0.066	2.16	0.78, 5.94	0.13
Headache	80/100 (80.0%)	170/196 (86.7%)	χ2	2.29	0.13	0.58	0.29, 1.14	0.11
Myalgia	78/100 (78.0%)	138/196 (70.4%)	χ2	1.94	0.15	1.50	0.83, 2.69	0.17
Upper respiratory tract symptoms	59/107 (55.1%)	69/174 (39.7%)	χ2	6.41	0.011	0.53	0.19, 1.45	0.22
Abdominal pain	24/108 (22.2%)	32/158 (20.3%)	χ2	0.15	0.69	1.95	0.31, 12.0	0.47
Neurological symptoms	12/57 (21.1%)	3/32 (9.4%)	χ2/Fisher	0.23	0.24	5.17	1.16, 28.0	0.03
Laboratory parameters, continuous
Hematocrit, %	46.7 ± 7.1	39.9 ± 7.2	t	–7.4	<0.001	1.001	1.001, 1.002	<0.01
Leukocytes, cells/mm3	15 325 ± 20 198	12 684 ± 14 661	t	–1.12	0.26	1.001	0.999, 1.002	0.37
Platelets, cells/mm3	81 009 ± 79 765	183 421 ± 94 113	t	9.21	<0.001	0.999	0.99, 1.000	<0.01
LDH, U/L	950.9 ± 559.6	594.4 ± 604.1	t	–3.83	<0.001	1.001	1.001, 1.002	<0.01
AST, U/L	196.9 ± 90.5	117.5 ± 95.1	t	–2.27	0.02	1.001	1.001, 1.002	<0.01
Creatinine, mg/dL	2.37 ± 3.12	1.26 ± 0.97	t	–3.03	0.003	1.401	1.147, 1.806	<0.01
Laboratory parameters, categorical
Thrombocytopenia	83/98 (84.7%)	53/151 (35.1%)	χ2	58.97	<0.001	11.08	5.59, 21.9	<0.01
Elevated LDH	73/86 (84.9%)	26/72 (36.1%)	χ2	50.09	<0.001	10.67	4.85, 23.3	<0.01
Elevated hematocrit	68/95 (71.6%)	41/159 (25.8%)	χ2	39.84	<0.001	7.40	3.96, 13.8	<0.01
Elevated creatinine	41/79 (51.9%)	39/135 (28.9%)	χ2	11.27	<0.001	2.91	1.59, 5.34	<0.01
Elevated AST	13/40 (32.5%)	49/146 (33.5%)	Fisher	1.00	0.86	0.93	0.42, 2.06	0.86
Chest radiography			χ2	2.40	0.30
Abnormal	65/78 (83.1%)	71/91 (78.0%)				1.68	0.78, 3.61	0.17
Normal	13/78 (15.7%)	20/91 (22.0%)				0.59	0.27, 1.26	0.17
Clinical course
Severe respiratory failure/criteria for mechanical ventilation	65/98 (66.3%)	50/178 (28.1%)	χ2	38.02	<0.001	5.58	3.16, 9.85	<0.01

AST, aspartate aminotransferase; LDH, lactate dehydrogenase; OR/aOR, odds ratio/adjusted odds ratio; 95% CI, 95% confidence interval.

Notes: Data are presented as mean ± SD for continuous variables and n/N (%) for categorical variables, using the available denominator for each variable. In the bivariate analysis, Student’s t test was used for continuous variables and the χ2 test for categorical variables; Fisher’s exact test was used when appropriate because of low expected frequencies. Adjusted models estimate aORs with 95% CIs, adjusting for age as a continuous variable and sex as male/female. For clinical parameters, the adjustment also included mutual adjustment among symptoms in addition to age and sex. For multi-category variables, adjusted estimates are category-specific comparisons of each category versus the remaining categories. Time since symptom onset was categorized as <2 days, 3–5 days, or >6 days. The activity-based exposure scale ranged from 0 to 4: 0, no evident risk; 1, low risk; 2, moderate risk; 3, high risk; and 4, very high risk, according to the type and intensity of potential exposure to rodents, rodent excreta, or environments with probable rodent presence. Thrombocytopenia was defined as platelet count <100 000/mm3 or a decrease >20% within 24 h; elevated LDH as >1 000 U/L; elevated hematocrit as >42%; elevated creatinine as >1.2 mg/dL; and elevated AST as >250 U/L. Abnormal chest radiography was defined as unilateral or bilateral pulmonary infiltrates. Severe respiratory involvement was defined as severe respiratory failure or criteria for mechanical ventilation. For continuous laboratory variables, aORs represent the change in odds associated with a one-unit increase in the original measurement scale. Therefore, for variables measured on large scales, such as platelet count, ORs and 95% CIs may appear very close to 1 after rounding. These continuous estimates should be interpreted cautiously and together with the corresponding clinically defined categorical variables. For AST, the marked dispersion of values, particularly among ruled-out suspected cases, supported interpreting the predefined categorical threshold rather than the continuous per-unit estimate as the clinically meaningful analysis.

Source: Prepared by the authors based on the study data.

Baseline characteristics

Age and sex were similar between confirmed and ruled-out suspected cases, with no clear association in adjusted models. Detailed n/N values, bivariate tests, and adjusted estimates for all variables are shown in Table 2.

Usual residence

Usual residence data were available for 113 confirmed and 164 ruled-out suspected cases. Urban, rural, and peri-urban residence showed broadly similar distributions between groups, with no clear association after adjustment (Table 2).

Workplace setting

Workplace setting was available for 101 confirmed and 109 ruled-out suspected cases. Rural and peri-urban workplaces were more frequent among confirmed cases in the descriptive analysis, whereas urban workplace was more frequent among ruled-out suspected cases; however, none of the workplace categories showed a clear association in the adjusted models (Table 2).

Activity-based exposure

The activity-based exposure scale was available for 87 confirmed and 22 ruled-out suspected cases. Compared with no evident risk, high-risk activity (48/87 [55.2%] vs. 4/22 [18.2%]; aOR 156; 95% CI [10, 2 448]; p < 0.001) and moderate-risk activity (23/87 [26.4%] vs. 6/22 [27.3%]; aOR 33; 95% CI [2.4, 456]; p < 0.01) showed the strongest associations with laboratory confirmation. Low-risk activity also showed an association, but with very wide uncertainty (aOR 44.7; 95% CI [1.6, 1 244]; p = 0.02). These estimates should be interpreted cautiously because exposure data were less frequently available among ruled-out suspected cases and some categories had small cell counts.

Time since symptom onset

Time since symptom onset differed between groups. Presentation within <2 days of symptom onset was less frequent among confirmed cases than among ruled-out suspected cases (17/113 [15.0%] vs. 97/212 [45.8%]) and was negatively associated with laboratory confirmation in the adjusted analysis (aOR 0.17; 95% CI [0.08, 0.30]; p < 0.01). This finding suggests that very early presentations may overlap with other nonspecific febrile illnesses in endemic areas.

Clinical presentation

Most nonspecific prodromal symptoms, including influenza-like syndrome, fever, headache, myalgia, upper respiratory tract symptoms, and abdominal pain, had limited discriminatory value after adjustment (Table 2). Neurological symptoms were recorded in 12/57 (21.1%) confirmed cases and 3/32 (9.4%) ruled-out suspected cases and were associated with laboratory confirmation in the adjusted model (aOR 5.17; 95% CI [1.16, 28.0]; p = 0.03).

Laboratory parameters, continuous

Confirmed cases had higher hematocrit and LDH values and lower platelet counts than ruled-out suspected cases. In adjusted models using the original continuous scales, ORs were close to 1 for hematocrit, LDH, and platelet count because they represent one-unit changes in the original measurement units; therefore, these continuous estimates were interpreted together with the corresponding clinically defined categorical variables. The distributions of LDH, AST, and creatinine were also reviewed using medians and interquartile ranges to assess the influence of extreme values. The marked dispersion of AST values, particularly among ruled-out suspected cases, supported interpreting AST mainly through the predefined categorical threshold rather than through the continuous estimate.

Laboratory parameters, categorical

Confirmed cases more frequently had thrombocytopenia (83/98 [84.7%] vs. 53/151 [35.1%]; aOR 11.08; 95% CI [5.59, 21.9]; p < 0.01), elevated LDH (73/86 [84.9%] vs. 26/72 [36.1%]; aOR 10.67; 95% CI [4.85, 23.3]; p < 0.01), elevated hematocrit (68/95 [71.6%] vs. 41/159 [25.8%]; aOR 7.40; 95% CI [3.96, 13.8]; p < 0.01), and elevated creatinine (41/79 [51.9%] vs. 39/135 [28.9%]; aOR 2.91; 95% CI [1.59, 5.34]; p < 0.01). In contrast, elevated AST showed no clear association with diagnostic confirmation (13/40 [32.5%] vs. 49/146 [33.5%]; aOR 0.93; 95% CI [0.42, 2.06]; p = 0.86).

Chest radiography

Abnormal chest radiography, defined as unilateral or bilateral pulmonary infiltrates, was common in both groups (65/78 [83.1%] vs. 71/91 [78.0%]) and was not clearly associated with laboratory confirmation when classified dichotomously as normal versus abnormal (aOR 1.68; 95% CI [0.78, 3.61]; p = 0.17).

Clinical course

Severe respiratory failure/criteria for mechanical ventilation was recorded in 65/98 (66.3%) confirmed cases and 50/178 (28.1%) ruled-out cases (χ² = 38.02; p < 0.001), with an adjusted OR of 5.58 (95% CI [3.16, 9.85]; p < 0.01). This variable was interpreted as a marker of early clinical severity; in some records, it could reflect early in-hospital deterioration rather than a finding strictly present at first assessment.

DISCUSSION

In this case–control study of patients with clinical suspicion of HPS evaluated in emergency departments, laboratory confirmation was mainly associated with a structured characterization of exposure and with an early biological profile compatible with HPS pathophysiology. Activity-based exposure risk showed the strongest association with confirmation, suggesting that information on the activity-based exposure and likelihood of contact with rodents or their excreta may be more informative than broader categories such as usual residence or workplace setting. Confirmed cases also more frequently presented hemoconcentration, thrombocytopenia, elevated LDH, elevated creatinine, severe respiratory involvement, and neurological symptoms.

These findings are consistent with previous evidence identifying rural, forest, and peri-domestic exposures as relevant determinants of HPS risk in the Andean-Patagonian region and other endemic areas (18, 19). However, our results suggest that, among patients already classified as suspected cases, operationalizing exposure through specific activities may add discriminatory value. This is also consistent with evidence indicating that risk is not determined only by rural residence but also by practices and environmental conditions that favor aerosolization in enclosed or poorly ventilated settings (20, 21).

The laboratory findings observed in confirmed cases are biologically plausible and align with the known pathophysiology of HPS, characterized by endothelial dysfunction, capillary leak, hemoconcentration, and thrombocytopenia. Previous reports have highlighted thrombocytopenia as one of the most useful laboratory findings for guiding diagnostic suspicion, including settings where its absence has been associated with a high negative predictive value (13, 14). In our cohort, thrombocytopenia remained strongly associated with confirmation and was complemented by elevated hematocrit and LDH, converging with prior strategies that proposed simple laboratory combinations to improve early diagnostic assessment (14). The association with elevated creatinine may also reflect early systemic involvement in patients with clinical presentations compatible with HPS (12).

From a clinical perspective, most nonspecific prodromal symptoms contributed little to discriminating confirmed from ruled-out cases, as expected given their overlap with other febrile syndromes in endemic areas. In contrast, neurological symptoms showed an independent association with confirmation. Previous studies have described neurological involvement or neurocognitive manifestations in hantavirus infection (22–25),

and studies in Andes virus contexts emphasize the need to integrate epidemiological, environmental, and contact-related

components into surveillance and control strategies, particularly because shared rodent exposure can be difficult to distinguish from interpersonal transmission in family or community clusters (6, 26–27). Therefore, this finding may suggest a subgroup of patients with more pronounced systemic involvement, although it should be interpreted cautiously.

This study has limitations. Its retrospective design and reliance on notification forms and clinical records introduce potential information bias, heterogeneity in measurement, and nonrandom missing data, reflected in variable denominators across covariates. This is particularly relevant for the activity-based exposure scale, which was less frequently available among ruled-out cases and may have produced unstable estimates because of small cell counts or near-complete separation. In addition, although the scale was predefined before this analysis, it was reconstructed retrospectively from notification forms and clinical records, and formal blinded duplicate coding or inter-rater reliability assessment was not performed. Some large adjusted ORs, including those for exposure categories and categorical laboratory markers, should therefore be interpreted as indicators of association rather than as precise effect estimates or components of a ready-to-use prediction rule. The long study period might also have introduced heterogeneity related to changes in surveillance practices, diagnostic access, clinical awareness, and supportive care over time. Finally, broadly categorized variables such as normal versus abnormal chest radiography may have failed to capture specific radiological patterns and could have been affected by indication bias. Severe respiratory failure/criteria for mechanical ventilation should also be interpreted as a marker of early clinical severity, because in some records it might have reflected early in-hospital deterioration rather than a predictor strictly present at first assessment.

The study also has strengths. To our knowledge, it represents one of the largest case–control analyses evaluating factors associated with HPS confirmation among suspected cases in this endemic region. The outcome was defined using a standardized laboratory confirmation pathway, with verification by a reference laboratory, reducing the risk of outcome misclassification. In addition, the analysis integrated exposure, clinical variables, and routinely available laboratory findings, and adjusted the estimates for relevant covariates to improve comparability between confirmed and ruled-out suspected cases. The proposed activity-based exposure scale provides a standardized approach to classifying exposure intensity, translating heterogeneous exposure histories into operational categories. This approach should be considered exploratory, but it may contribute to a broader body of evidence for the future development of clinical prediction tools and could be incorporated as a candidate framework in subsequent systematic review and prospective validation efforts.

Conclusion

In this case–control study of patients with suspected HPS evaluated in emergency departments, activity-based exposure risk, selected laboratory abnormalities at admission (including hemoconcentration, thrombocytopenia, elevated LDH, and elevated creatinine) severe respiratory involvement, and neurological symptoms were associated with laboratory confirmation of HPS. These findings suggest that, among patients who already meet clinical suspicion criteria, structured exposure assessment together with a minimal laboratory panel may

inform diagnostic prioritization. Given the retrospective design, variable completeness of records, and potential instability of some estimates, these results should be interpreted cautiously. Rather than supporting immediate implementation as a prediction rule or risk score, they may contribute to the future development and prospective validation of clinical prediction tools for HPS in endemic settings.

Funding Statement

This study received no specific funding. No sponsor had any role in the study design, data collection, analysis, interpretation, manuscript preparation, or decision to submit the article for publication.

Data availability.

The data are not openly available because they contain sensitive individual-level clinical and epidemiological information. De-identified data underlying the results may be made available upon reasonable request to the corresponding author, subject to approval by the study investigators and applicable ethical and legal requirements.

Declaration of artificial intelligence (AI) use.

During preparation of the revised manuscript, the authors used ChatGPT (OpenAI) to support English-language editing. The tool was not used to generate data, conduct statistical analyses, interpret results, or draw scientific conclusions. All AI-assisted outputs were reviewed, edited, and approved by the authors, who take full responsibility for the content of the manuscript.

Disclaimer.

Authors hold sole responsibility for the views expressed in the manuscript, which may not necessarily reflect the opinion or policy of the RPSP/PAJPH or the Pan American Health Organization (PAHO).