Severe acute respiratory infection (SARI) was defined in 2011 for purposes of global surveillance. The 2011 definition harmonized heterogeneous definitions used by three WHO regions, thus facilitating comparisons. The revisions include one definition for all age groups to simplify implementation, dropping “shortness of breath” and “breathing difficulty,” adding “history of fever” and increasing the onset of symptoms to 10 days. SARI is now defined as an acute respiratory illness with a history of fever or measured fever of ≥38°C and cough, with onset within the past 10 days and requiring hospitalization.1

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has resulted in a significant global burden. Worldwide as on 7th November 2021, there have been about 249 million cases of SARS-CoV-2 infection with a case fatality rate of 2.0%.2 A few studies have evaluated the sensitivity and specificity of SARI criteria for influenza detection. Sensitivity and specificity range from 37% to 84% and 23% to 78%, respectively. 3,4

Severe acute respiratory infection and influenza-like illness (ILI) surveillance have been conducted at several hospitals and primary health centers. These studies reported that the proportion of influenza cases varied from 14% to 20% of all enrolled subjects. As the aims of these studies were to confirm influenza infections, other causes of respiratory infections or “systemic” viral or bacterial infections were not analyzed. Since bacterial, influenza, and non-influenza viral respiratory infections are prevalent in Indonesia, there is a need to evaluate strategies for respiratory pathogen surveillance in the region. Present study was aimed to study clinical and laboratory profile of SARI (Severe Acute Respiratory Infection) patients admitted at a tertiary care centre

Present study was single-center, prospective, observational study, conducted in department of General Medicine, at VDGMC LATUR, India. Study duration was of 18 months. (1 Aug 2022 to 29 Feb 2024). Study was approved by institutional ethical committee.

Inclusion criteria

• All patients > 18 years age, admitted in SARI ward, had regular patient follows up to our OPD, willing to participate in present study

Exclusion criteria

• Age of patients is below 18 years.
• Uncooperative patient.
• Patients who will not give written consent.

Study was explained to participants in local language & written informed consent was taken. Baseline demographic variables (age, weight, height, BMI, education, occupation, religion, income, address, type of family, socioeconomic status, and co-morbidities) were collected & entered in case proforma. All available previous reports including fasting, postprandial sugar level, and haemoglobin level were also collected. Radiological investigation (HRCT CHEST/CHEST X RAY), Hematological investigation (CBC, LFT, KFT, D DIMER, Sr ferritin, alkaline phosphatase, CRP, PCT propbnp & Rapid antigen), ECG, 2D ECHO, Spirometry, PFT were done in all patients. Blood pressure was measured by using a sphygmomanometer.

Subacute respiratory infections (SARI) arise from a variety of invaders, predominantly viruses and bacteria. Common culprits include respiratory syncytial virus (RSV), influenza virus, adenovirus, and rhinovirus. Bacteria like Streptococcus pneumoniae and Mycoplasma pneumoniae can also be responsible.

Data was collected and compiled using Microsoft Excel, analysed using SPSS 23.0 version. Frequency, percentage, means and standard deviations (SD) was calculated for the continuous variables, while ratios and proportions were calculated for the categorical variables. Difference of proportions between qualitative variables were tested using chi- square test or Fisher exact test as applicable. P value less than 0.5 was considered as statistically significant.

Out of a total of 250 participants, the largest group comprises those aged over 61 years (36 %), followed by 31-40 years (17%) 18-30 years and 41-50 years (16 % for each group). Out of 250 participants, 145 are male (58%), while 105 are female (42%). Among the 250 participants, the majority, 187 individuals (75%), fall within the normal weight range of a BMI between 18.5 and 24.9. Out of 250 participants, an equal number of 108 individuals (43%) each stayed in the hospital for less than one week and for one to two weeks.

Table 1: General characteristics

Fever is the most common symptom, reported by 248 participants (99.2%). Headache and cough are also prevalent, affecting 179 (71.6%) and 178 (71.2%) participants, respectively. Tachypnea and sore throat each occur in 108 participants (43.2%), while nausea/vomiting is noted in 110 participants (44%). Other symptoms include diarrhea (19.2%), shortness of breath (15.2%), and myalgia (11.2%). Less common symptoms are haemoptysis (7.2%), arthralgia (3.6%), seizure (3.2%), chills (4.4%), lethargy (2%), and coryza (1.2%). Among the 250 participants, bronchitis is the most prevalent clinical sign, observed in 118 individuals (47.2%). Bronchiolitis is present in 66 participants, accounting for 26.4% of the sample. Asthma is noted in 48 participants, making up 19.2%.

Table 2: Clinical profile of the patients

Out of 250 participants, the majority, 198 individuals (80%), have an SpO2 level greater than 95%, indicating normal oxygen saturation. A smaller portion of 22 participants (8.5%) have SpO2 levels between 90-95%, while 20 participants (8%) fall within the 85-90% range, suggesting mild hypoxemia. The remaining 10 participants (3.5%) have SpO2 levels below 85%, indicating more severe hypoxemia.

Table 3: Oxygen saturation (SPO₂)

Out of 250 participants, 138 individuals (55%) are classified as having SARI, while the remaining 112 participants (45%) are identified as non-SARI. Out of the total 250 participants, 30 individuals (12%) tested positive for COVID-19, while the majority, 230 individuals (88%), tested negative.

Table 4: SARI & COVID status

Based on their white blood cell (WBC) count status categorized by SARI and non-SARI conditions, p-value indicates statistical significance (P<0.05) for the difference in WBC count distribution between SARI and non-SARI groups, suggesting that WBC count variation is likely associated with the severity or type of respiratory illness observed in the study participants.

Based on their Haemoglobin levels categorized by SARI and non-SARI conditions, p-value indicates no statistical significance (P>0.05) for the difference in Haemoglobin level distribution between SARI and non-SARI groups, suggesting that Haemoglobin levels do not significantly differ based on the severity or type of respiratory illness observed in the study participants.

Based on their hematocrit status, with distinctions between those diagnosed with Severe Acute Respiratory Infection (SARI) and those without (non-SARI), p-value indicates statistical significance (P<0.05), implying a notable difference in hematocrit status distribution between SARI and non-SARI groups. This suggests that hematocrit status may be a significant indicator or factor associated with the severity or presence of severe respiratory infections within the study population.

Based on their platelet levels categorized by SARI and non-SARI conditions, p-value indicates no statistical significance (P>0.05) for the difference in platelet level distribution between SARI and non-SARI groups, suggesting that platelet levels do not significantly differ based on the severity or type of respiratory illness observed in the study participants.

Table 5: Hematological profile of the patients

Based on their sodium, potassium & chloride levels categorized by SARI and non-SARI conditions, p-value indicates no statistical significance (P>0.05) for the difference in electrolyte level distribution between SARI and non-SARI groups, suggesting that electrolyte levels do not significantly differ based on the severity or type of respiratory illness observed in the study participants.

Table 6: Electrolyte profile of the patients

There was a significant difference in blood urea, serum creatinine levels, CRP levels & D-dimer levels between SARI and non-SARI groups. Elevated CRP levels often indicate inflammation or infection, which aligns with the symptomatic severity of SARI cases observed in the study participants. This data underscores the potential utility of CRP levels as a biomarker for distinguishing between SARI and non-SARI conditions within this study cohort.

Elevated D-dimer levels often indicate increased fibrinolytic activity, which can be associated with conditions like thrombosis or acute inflammation, potentially reflecting the severity and thrombotic risk in SARI cases observed in the study participants

Table 7: Laboratory profile of the patients

In India, the initial COVID-19 testing strategy included people who had international travel history with symptoms, symptomatic contacts of laboratory-confirmed COVID-19 patients and symptomatic healthcare workers managing Influenza like illness (ILI)/severe acute respiratory illness (SARI) patients.5

While most people with COVID-19 infection develop only mild or uncomplicated illness, approximately 14% develop severe disease that requires hospitalization and oxygen support, and 5% require admission to an intensive care unit.8 at present, there are no effective therapies or vaccines for COVID-19.

Severe acute respiratory illness (SARI) is among the leading cause of hospitalization and deaths worldwide. SARI is associated with a large number of different viral and bacterial agents, notably influenza A and B viruses, parainfluenza viruses, coronaviruses, respiratory syncytial viruses (RSV), adenoviruses (AV), and rhinoviruses. 6

In the present study, 108 (43%) had hospital stays of less than one week, in comparison, the study by AA El Kholy et al. reports the median duration of hospital stay as 7 days, with a range of 2 to 120 days. Notably, 22% of patients diagnosed with viral lower respiratory tract infections had a length of stay (LOS) exceeding 10 days, which is beyond the 75th percentile of the median hospital stay duration.

The present study's findings that the majority of participants have relatively shorter hospital stays (<2 weeks) suggest a generally less severe patient population or effective medical interventions leading to quicker recoveries. In contrast, the AA El Kholy et al.,7 study's focus on a specific patient group with potentially more severe conditions results in a wider range of hospital stay durations and a notable proportion of extended stays.

The study participants exhibited a range of clinical symptoms, with fever being the most common (99.2%) followed by Headache and cough (71.6% and 71.2% respectively). Other notable symptoms included nausea/vomiting (44%), sore throat (43.2%), and tachypnea (43.2%). In comparison, the study by Amit Aggarwal et al.,8 focuses on a different set of common symptoms among their study participants. The most frequent symptom reported is dyspnea (90.6%), followed by cough (84.4%) and fever (68%). Body aches and myalgia are reported by 43.75% of participants.

This comparison highlights the importance of context in interpreting clinical symptom data, as the prevalence and type of symptoms can vary significantly depending on the patient population and the specific health conditions being studied. The present study's broader symptom distribution suggests a general assessment of common clinical symptoms, while the Amit Aggarwal et al.,8 study's detailed focus on respiratory and hematological symptoms indicates a more targeted investigation into severe respiratory conditions.

Out of 250 participants, 138 (55%) were classified under the SARI category, indicating they presented with severe respiratory symptoms requiring hospitalization or intensive medical care.

In contrast, the study by Jin-Zhu Wang et al.,9 encompasses a broader cohort of 1266 patients, focusing on respiratory symptoms and medical outcomes. In their study, the majority of patients were males (61.6%) and farmers (61.4%), with a high proportion seeking medical treatment in 2020 (88.8%). Most patients (80.3%) were admitted to general wards, reflecting the distribution of patients across different hospital settings. Common respiratory symptoms included fever (86.8%) and cough (77.8%), with a significant number of patients (62.6%) showing anomalies on chest imaging. Moreover, respiratory pathogens were detected in 58.1% of cases, with a notable subset (28.5%) presenting with multiple infections.

Out of 250 participants, 30 (12%) tested positive for COVID-19, while 230 (88%) tested negative. Comparatively, findings from the study by Reena Jain et al.,10 underscore significant differences between COVID-19 positive and negative patients in terms of clinical outcomes. Despite similarities in demographic characteristics and initial symptoms between COVID-19 and non-COVID-19 patients, COVID-19 patients exhibited lower absolute lymphocyte counts and higher serum alanine transaminase levels. Moreover, COVID-19 patients with Severe Acute Respiratory Infection (SARI) were more likely to experience acute respiratory distress syndrome, shock, and required intensive care unit admission at higher rates compared to non-COVID-19 SARI patients. The study also noted a trend towards higher mortality among COVID-19 patients, with death occurring in 18% of COVID-19 patients compared to 9% among non-COVID-19 patients.

Together, these findings highlight the distinct clinical characteristics and outcomes associated with COVID-19 within the study population, emphasizing the virus's impact on severe respiratory illness and healthcare utilization. The categorization of COVID-19 status in the present study provides a foundational understanding of how COVID-19 influences the epidemiology and clinical management of respiratory conditions in hospitalized adults, complementing broader insights from comparative studies like that of Reena Jain et al.,10

In the present study, white blood cell counts differed significantly between the SARI and Non-SARI groups. The SARI group had a lower proportion of participants with counts <5000 (18) compared to the non-SARI group (24), with a significant P value <0.05. However, the non-SARI group had more participants in the 5000-15000 range (70 vs. 50), and the SARI group had a notably higher proportion of participants with counts >15000 (70 vs. 18). In contrast, the Amit Agarwal et al.,8 study reported leucopenia (WBC count <4000) in 31.2% of COVID-19 patients, with no significant difference between severe and non-severe cases, indicating different trends in WBC distribution between SARI and COVID-19.

The present study observed no significant differences in haemoglobin levels <6 gm/dl between SARI (8) and non-SARI (9) groups. However, more SARI participants had levels >12 gm/dl (38 vs. 11). In the Amit Agarwal et al.,8 study, anaemia was present in 43.8% of participants, with no significant difference between severe and non-severe cases. The present study's higher haemoglobin levels in SARI participants contrast with the moderate haemoglobin levels reported in COVID-19 patients.

The present study found significantly higher positive haematocrit levels in the SARI group (128 vs. 60, P<0.05). Negative haematocrit levels were more prevalent in the non-SARI group (72 vs. 10). The Amit Agarwal et al.,8 study did not specifically report haematocrit levels, making direct comparison difficult.

Platelet counts showed no significant differences between groups in the present study. Platelet counts <2 lakhs/mm³ were slightly lower in SARI participants (4 vs. 7), and counts >5 lakhs/mm³ were observed in 6 SARI participants vs. 3 non-SARI participants. In the Amit Agarwal et al.,8 study, thrombocytopenia was observed in 43.8% of patients, with no significant differences between severe and non-severe cases, aligning with the present study's findings of no significant differences in platelet counts.

The present study found significantly higher blood urea levels >40 mg/dl in the SARI group (28 vs. 4, P<0.05). The Amit Agarwal et al.,8 study reported raised urea levels in severe COVID-19 cases, consistent with the present study's findings. The present study observed significantly higher serum creatinine levels >1 mg/dl in the SARI group (17 vs. 2, P<0.05). The Amit Agarwal et al.,8 study also reported higher creatinine levels in severe COVID-19 cases, aligning with the present study's findings.

CRP levels were significantly higher in the SARI group in the present study (128 vs. 62, P<0.001). The Amit Agarwal et al.,8 study also reported raised CRP levels in severe cases, highlighting the inflammatory response, consistent with the present study. D-Dimer levels were significantly elevated in the SARI group (127 vs. 14, P<0.05) in the present study. The Amit Agarwal et al.,8 study similarly reported raised D-Dimer levels in severe COVID-19 cases, indicating a common marker of severity in both SARI and COVID-19.

In summary, both studies observed significant differences in white blood cell counts, haemoglobin levels, and inflammatory markers like CRP and D-Dimer between severe and non-severe cases. While the present study focused on SARI and the Amit Agarwal et al.,8 study on COVID-19, the findings align in terms of elevated inflammatory markers and indicators of severity. Differences in specific markers like haematocrit and electrolyte levels highlight the need for context-specific analysis, but the overall trends suggest common pathways of severe respiratory infections and their systemic impacts.

In present study, majority patients were older adults, with significant representation over 61 years old, male participants, had normal BMI. Elevated CRP levels were significantly more common in SARI patients compared to non-SARI patients, reflecting higher levels of systemic inflammation. D-Dimer levels were significantly elevated in SARI patients compared to non-SARI patients, suggesting increased risk of thrombotic complications in severe cases.

Conflict of Interest: None to declare

Source of funding: Nil

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