Serial Platelet Level Index Improves Prediction of Pulmonary Hemorrhage in Stenotrophomonas maltophilia Respiratory Infections

Serial Platelet Level Index Improves Prediction of Pulmonary Hemorrhage in Stenotrophomonas maltophilia Respiratory Infections | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Serial Platelet Level Index Improves Prediction of Pulmonary Hemorrhage in Stenotrophomonas maltophilia Respiratory Infections Huai-Chueh Gem Wu, Huai-Shing Wu, Chao-Neng Cheng, Jiann-Shiuh Chen, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1360630/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Thrombocytopenic patients who acquire Stenotrophomonas maltophilia (SM) respiratory infection often develop pulmonary hemorrhage (PH), resulting in a high respiratory failure rate and increased mortality. This study aimed to evaluate risk factors for PH and develop an index measuring serial platelet deficit to predict PH in patients with SM respiratory infection. Methods: Data of patients with both SM isolated from sputum/endotracheal suction culture and thrombocytopenia (platelet count < 150x10 3 /μL) who were treated at National Cheng Kung University Hospital during 2018-2020 were extracted from electronic medical records and analyzed retrospectively. SM respiratory infection was defined as positive bacterial isolates plus respiratory infection symptoms. Clinical parameters and laboratory findings were compared between PH and non-PH groups. The platelet dissimilarity index (d-index) was calculated by accumulating differences between the actual and the lowest normal level of platelet count in each patient at different time points. Results: Among 437 SM respiratory infection cases, 125 (28.6%) patients developed PH. Patients with PH had increased prothrombin time/international normalized ratio (PT/INR), lower platelet count, and higher platelet d-index. Multivariate analysis revealed that extreme thrombocytopenia (platelet count < 50x103 /μL) is a common independent risk factor for PH and mortality. The performance of platelet deficit and d-index varied between patients with different comorbidities. Performance of single time-point platelet deficit to predict PH is more reliable in patients with hematology/oncology and liver disease (area under curve 0.705-0.757), while performance of d-index is more reliable in patients with sepsis/treatment and various other groups (0.711-0.816). Conclusions: Prolonged and extreme thrombocytopenia is a determinant risk factor for PH in patients with SM respiratory infection. Given the complexity of causes of thrombocytopenia and associated comorbidities, different strategies should be applied to assess the degree of thrombocytopenia when evaluating the risk for PH. Stenotrophomonas maltophilia hemorrhagic pneumonia pulmonary hemorrhage platelet d-index thrombocytopenia Figures Figure 1 Background Stenotrophomonas maltophilia (SM) is a ubiquitous, globally emerging, multiple-drug resistant, non-fermenting gram-negative bacillus (NFGNB) that typically causes opportunistic infection in severely immunocompromised or debilitated patients. Respiratory infection, including ventilator associated pneumonia (VAP), is the most common clinical presentation of SM and potentially results in pulmonary hemorrhage (PH) [1]. The extracellular protease secreted by SM is reported to cause tissue destruction, vascular damage, and subsequent hemorrhage [2–4]. Although pulmonary hemorrhage (PH) is an uncommon complication of SM respiratory infection, previous studies have reported mortality as high as 85% within 30 days of infection onset [5–10]. Risk factors for PH have been identified in different clinical settings and in patients with various comorbidities. Hematologic malignancy and thrombocytopenia were found to be predictive factors of hemorrhagic pneumonia in SM bacteremia patients [6, 11]. Also, neutropenia, longer duration of neutropenia, high C-reactive protein (CRP) or procalcitonin (PCT) levels, and persistent fever despite using broad-spectrum antibiotics are independent predictors of PH in hemopoietic cell transplant (HCT) recipients or patients with other hematologic diseases [7, 8]. Although thrombocytopenia has been identified as an important risk factor for hemorrhagic complications in general practice, no comprehensive evaluation has yet addressed the degree of thrombocytopenia and its association with PH in SM infections. The cumulative d-index (c-d-index) is a scoring system that uses absolute neutrophil counts over the course of neutropenia to characterize the degree and durability of neutropenia; the index has been applied to febrile neutropenic patients to assess the risk of invasive mold infections [12–14]. The present study aimed to develop an index of serial platelet levels from different time windows to evaluate the degree of thrombocytopenia and explore associations between the platelet D-index and PH in respiratory SM infections. Materials And Methods Ethics statement The Institutional Review Board of National Cheng Kung University Hospital reviewed and approved the study protocol (IRB no. A-ER-110-079). The study was performed in accordance with the Declaration of Helsinki. Owing to the study's retrospective nature, signed informed consent from patients was waived. Patients The electronic medical records from National Cheng Kung University Hospital, Tainan, Taiwan, were searched using the criteria of hospitalized patients with positive SM isolated from sputum culture between January 2018 and December 2020. Only data of patients with SM respiratory infection and thrombocytopenia were extracted from the medical records database. Positive SM was defined as having both respiratory symptoms and thrombocytopenia (platelet count < 150 x10 3 /µL) 7 days before and after the date of sputum culture collection. Patients with duplicate culture results within the same hospitalization period were merged as a single event. Cases with (1) normal or high platelet count seven days before and after the date of sputum culture collection, (2) evidence of pulmonary invasive fungal infection, (3) only Stenotrophomonas colonization without respiratory symptoms, or (4) incomplete clinical data, were excluded. Clinical variables and data collection Demographic and clinical data, including age, sex, reason for admission, existence of hematological disease, alternation or disruptions in pulmonary structure (e.g., lung cancer, intrathoracic surgery, tuberculoma), existence of neutropenia ( 1.2 and INR > 1.2 was considered prolonged), platelet count on the day of sputum culture and use of mechanical ventilation, were extracted from the electronic medical records. Causes of thrombocytopenia were grouped as follows: sepsis-medication related (“Sepsis-Rx”) (e.g., disseminated intravascular coagulation due to severe infection, medication-related platelet destruction); hematological disease and chemotherapeutics use due to oncological disease(“Hem-Onc”); liver disease (“Liver”); and various other causes (“Others”) (e.g., mechanical destruction, transfusion consumption coagulopathy or major bleeding, unknown cause). PH was defined in patients with multiple episodes of hemoptysis and desaturation or evidence of deteriorating pulmonary function or anatomy (e.g., increased infiltrations in chest X-ray, increased oxygen demand). Platelet D-Index and Platelet Deficit Calculation D-index was applied in patients with prolonged neutropenia and opportunistic infections using an accumulated difference between neutrophil count and the threshold of neutropenia, as described previously [12–14]. The same rationale was applied to estimate the accumulated platelet deficit in thrombocytopenic patients. The Platelet D-index was calculated using this algorithm. $$Platelet {D}_{index}= {A}_{e}- {A}_{0}= {\sum }_{i=2}^{n}\left[150*\left({t}_{i}-{t}_{i-1}\right)\right]-{\sum }_{i=2}^{n}\left[\frac{{P}_{i-1}+{P}_{i}}{2}*\right({t}_{i}-{t}_{i-1}\left)\right]$$ Accumulated platelet deficit between estimated area under curve (Ae) and observed area under curve (Ao) 7 days before and after sputum culture result of SM was calculated. Time window of platelet d-index included 3 days before and after SM sputum test date (d-index-6), 5 days before and after (d-index-10), and 7 days before and after (d-index-14). The platelet deficit was calculated using the lowest level of normal platelet count (150 x10 3 /µL) minus the platelet count at test date. Statistical Analysis All statistical analyses were performed using SPSS 17 for Windows (IBM SPSS, Armonk, NY, USA). Patients with SM respiratory infections were grouped as “with PH” or “without PH”. The independent sample t-test was used for continuous variables, and the Chi-square test or Fisher’s exact test was used for dichotomous variables. P value < 0.05 was considered statistically significant. Cox’s proportional hazard analysis was used to determine risk factors for PH and 30-day mortality. One-way ANOVA was used to assess platelet levels and d-index of various causes of thrombocytopenia. To assess the ability of platelet d-index for different time windows and platelet deficits of a single day to predict pulmonary hemorrhage, sensitivity and specificity were analyzed using receiver operating characteristic (ROC) curves across the sputum sampling day showing SM positive. The optimal cut-off value was determined by the maximum sum of sensitivity and specificity. Results Study population Of the 437 patients with thrombocytopenic SM respiratory infection, 125 patients (28.6%) developed PH. Patients’ demographic and clinical characteristics are shown in Table 1 . No significant differences were found in age, sex, and cause of thrombocytopenia between patients with and without PH. The most common causes of thrombocytopenia were “Sepsis-Rx” (57.0%), followed by “Others” (15.1%), “Liver disease” (14.9%), and “Hem-Onc” (13.0%). Although hematological disease accounts for the majority (48/57, 84.2%) of cases in the “Hem-Onc” group, the proportion of hematological diseases was not significantly different between the “Hem-Onc and “Liver” groups. Platelet counts at the test date were lower, and the d-index of different time frames was higher in the PH group than in the non-PH group ( P value < 0.001). Also, prolonged PT/INR and mechanical ventilation use were significantly associated with PH (all P value < 0.05). The mortality of SM respiratory infection was higher in the PH group than in the non-PH group (87.2% vs. 57.7%, P value < 0.001), with the overall rate of 66.1%. Half of the patients with PH died within the first week after diagnosis, and the mortality rate declined in the second and third weeks. None of the neutropenic patients with PH (n = 15) survived. Table 1 Demographic and clinical characteristics of patients with SM respiratory infections Characteristics All Patients (N = 437) Patients without pulmonary hemorrhage (n = 312) Patients with Pulmonary Hemorrhage (n = 125) p value Sex, Male, no. (%) 273 (62.5%) 187 (59.9%) 86 (68.8%) 0.084 Age, years, median (IQR) 69 (59–79) 69 (59–80) 70 (59–78) 0.467 Comorbidities associated with thrombocytopenia, no. (%) 0.377 Hema-Onc 57 (13.0%) 35 (11.2%) 22 (17.6%) Liver disease 65 (14.9%) 46 (14.7%) 19 (15.2%) Sepsis-Rx 249 (57.0%) 185 (59.3%) 64 (51.2%) Others 66 (15.1%) 46 (14.7%) 20 (16.0%) Pulmonary structural abnormalities, no. (%) 160 (36.6%) 112 (35.9%) 48 (38.4%) 0.624 Mechanical ventilation, no. (%) 362 (82.8%) 250 (80.1%) 112 (89.6%) 0.018* Neutropenia, no. (%) 43 (9.8%) 28 (9.0%) 15 (12.0%) 0.337 APTT/MNAPTT ratio, median (IQR) 1.04 (0.93–1.25) 1.01 (0.91–1.18) 1.14 (0.99–1.34) 0.506 PT-INR, median (IQR) 1.31 (1.16–1.57) 1.28 (1.14–1.50) 1.36 (1.22–1.69) 0.007* Platelet count at test date, mean (range) (10 3 /µL) 85.17 (6-399) 92.30 (6-324) 67.90 (6-399) < 0.001* d-index per day, mean d-index-14 68.49 60.22 88.98 < 0.001* d-index-10 68.75 60.18 90.31 < 0.001* d-index-6 70.23 61.67 91.78 < 0.001* Mortality, no. (%) 289 (66.1%) 180 (57.7%) 109 (87.2%) < 0.001* within 7 days 132 (30.2%) 70 (22.4%) 62 (49.6%) < 0.001* within 14 days 190 (43.5%) 102 (32.7%) 88 (70.4%) < 0.001* within 30 days 229 (52.4%) 130 (41.7%) 99 (79.2%) < 0.001 APTT/MNAPTT, activated partial thromboplastin time/mean normal activated partial thromboplastin time; PT/INR, prothrombin time and international normalized ratio Risk factors associated with pulmonary hemorrhage and mortality Table 2 and Supplementary Table 2 list the results of Cox proportional hazard analysis of risk factors associated with PH in neutropenic SM respiratory infections and risk factors associated with 30-day mortality in the PH group, respectively. In univariate analysis, neutropenia, and extreme thrombocytopenia (platelet count at test date < 50 x10 3 /µL) were both risk factors for PH and 30-day mortality. However, multivariate analysis showed that severe thrombocytopenia was the only independent risk factor for both PH and 30-day mortality in PH patients. Table 2 Univariate and multivariate analysis of risk factors associated with pulmonary hemorrhage in patients with SM respiratory infections Risk factors associated with pulmonary hemorrhage Characteristics Univariate analysis Multivariate analysis Hazard ratio (95% CI) p value Hazard ratio (95% CI) p value Age > 65 years 1.032 (0.790–1.621) 0.499 Male sex 1.176 (0.805–1.718) 0.402 Neutropenia 2.005 (1.145–3.511) 0.015* 1.399 (0.725–2.699) 0.316 Pulmonary structural abnormalities 1.013 (0.705–1.456) 0.943 Mechanical Ventilation 0.858 (0.480–1.533) 0.605 APTT/MNAPTT > 1.2 1.080 (0.720–1.621) 0.709 0.971 (0.615–1.532) 0.899 INR > 1.2 1.066 (0.661–1.721) 0.793 1.062 (0.590–1.912) 0.842 Platelet at test date < 50 x10 3 /µL 1.787 (1.230–2.596) 0.002* 2.310 (1.346–3.965) 0.002* APTT/MNAPTT, activated partial thromboplastin time/mean normal activated partial thromboplastin time; PT/INR, prothrombin time and international normalized ratio. Characteristics of SM respiratory infections by cause of thrombocytopenia Comparison of clinical characteristics and laboratory findings between patients with thrombocytopenic SM respiratory infection caused by thrombocytopenia is shown in Table 3 . The “Sepsis-Rx” group had more patients aged 65 years and older (67.9%), higher pulmonary structural abnormalities (41.8%), and greater need for mechanical ventilation (86.7%). Platelet counts at the test date were significantly lower in patients in “Hem-Onc” and “Liver” groups than those in the “Sepsis-Rx” and “Others” groups, with the most extreme thrombocytopenia (platelets < 50 x10 3 /µL) cases in the “Hem-Onc” group. The d-index-14 was inversely correlated with platelet counts at the test date and was significantly higher in patients in the “Hem-Onc” and “Liver” groups than those in the “Sepsis-Rx” and “Others” groups. However, the percentage of PH and the time to developing PH from diagnosis were not significantly different between these four groups. Mortality rates (66.1%) were significantly higher in the “Hem-Onc” (71.9%) and “Sepsis-Rx” (71.9%) groups than those in the “Liver” (52.3%) and “Others” groups (53%). Table 3 Comparison of clinical characteristics and laboratory findings between patients with SM respiratory infections by different comorbidities Overall (N = 437) Hema-Onc (n = 57) Liver (n = 65) Sepsis-Rx (n = 249) Others (n = 66) p value Age > 65-year-old, no. (%) 264 (60.4%) 28 (49.1%) 29 (44.6%) 169 (67.9%) 38 (57.6%) 0.001* Male sex, no. (%) 273 (62.5%) 34 (59.6%) 42 (64.6%) 156 (62.7%) 41 (62.1%) 0.955 Pulmonary structural abnormalities, no. (%) 160 (36.6%) 15 (26.3%) 13 (20%) 104 (41.8%) 28 (42.4%) 0.003* Mechanical ventilation, no. (%) 362 (82.8%) 37 (64.9%) 49 (75.4%) 216 (86.7%) 60 (90.9%) 1.2, no. (%) 92 (28.9%) 11 (26.8%) 20 (40%) 47 (26.6%) 14 (28.0%) 0.311 INR > 1.2, no. (%) 222 (66.3%) 31 (72.1%) 46 (79.3%) 116 (62.7%) 29 (59.2%) 0.065 Platelet count at test date (10 3 /µL), mean (CI 95%) 85.32 (80.33–90.31) 45.82 (34.99–56.66) 65.62 (56.55–74.68) 94.93 (88.46–101.40) 102.59 (88.12-117.07) < 0.001* Percentage of extreme thrombocytopenia ( < = 50 x10 3 /µL), no. (%) 9 (2.1%) 7 (12.3%) 0 (0%) 1 (0.4%) 1 (1.5%) < 0.001* d-index-14, mean (CI 95%) 68.33 (64.44–72.23) 104.08 (94.62-113.53) 83.04 (75.79–90.28) 59.79 (54.71–64.86) 55.21 (45.74–64.68) 0.008* Pulmonary hemorrhage (PH), no. (%) 125 (28.6%) 22 (38.6%) 19 (29.2%) 64 (25.7%) 20 (30.3%) 0.270 Time to development of PH; mean days (CI 95%) 5.94 (3.55–8.32) 2.96 (0.35–5.56) 3.00 (1.18–4.82) 7.83 (3.78–11.88) 5.95 (0.00-12.34) 0.148 Death, no. (%) 289 (66.1%) 41 (71.9%) 34 (52.3%) 179 (71.9%) 35 (53%) 0.002* APTT/MNAPTT, activated partial thromboplastin time/mean normal activated partial thromboplastin time; PT/INR, prothrombin time and international normalized ratio. (Available data of APTT n = 318, PT n = 335.) d-index-14, d-index 7 days before and after sputum test date. Platelet count-derived clinical parameters in predicting PH Various platelet count-derived clinical parameters were used to predict PH in patients with thrombocytopenia SM respiratory infection and the performance is shown in Fig. 1 and Table 4 . The predictability of these parameters varied across different causes of thrombocytopenia, and d-index-10 had the highest AUC (0.719) in all cases. Platelet deficit performed more reliably than d-index in the “Hem-Onc,” and “Liver” groups, and the two groups combined. In contrast, d-index performed more reliably in the “Sepsis-Rx” and “Others” groups. D-index-14 of the “Others” group showed the highest rate of predictability (AUC = 0.816) of PH across all groups. The cutoff values of platelet deficit and d-index-14 according to the maximum sums of sensitivity and specificity are listed in Table 4 . The optimal cutoff value of platelet deficit on the test date for all cases was 70.5 x10 3 /uL, corresponding to platelet levels of 79.5 x10 3 /uL with a sensitivity of 69.8% and a specificity of 57.7% in predicting PH. The optimal platelet cut-off value at the test date varied across the four groups, from 17.5 x10 3 /uL in the “Hem-Onc” group, to 67.5 x10 3 /uL in the “Liver” group, 86.5 x10 3 /uL in the “Sepsis-Rx” group, and 106 x10 3 /uL in the “Others” group. We subtracted the d-index-14 by days to calculate the average platelet deficit per day and the corresponding value had a similar pattern as the platelet deficit at the test date, but with more reliability in “Sepsis-Rx” and “Others” group. Table 4 Performance of various measurements in predicting pulmonary hemorrhage in patients with SM respiratory infection by different comorbidities AUC All Hema-Onc & Liver Sepsis-Rx & Others Hema-Onc Liver Sepsis-Rx Others Platelet deficit of test date 0.699 0.729 0.684 0.757 0.705 0.664 0.757 d-index-6 0.717 0.691 0.724 0.676 0.689 0.701 0.808 d-index-10 0.719 0.688 0.734 0.698 0.674 0.712 0.807 d-index-14 0.714 0.672 0.734 0.688 0.648 0.711 0.816 Platelet deficit at test date cutoff value, 10 3 /µL 70.5 118.5 48.5 132.5 82.5 63.5 44.0 Sensitivity 69.8% 53.7% 77.4% 50.0% 84.2% 68.8% 85.0% Specificity 57.7% 81.5% 48.9% 88.6% 52.2% 59.5% 54.3% Platelet deficit derived from d-index-14 cutoff value, 10 3 /µL 71.3 117.3 71.3 117.3 92.4 71.3 71.1 Sensitivity 70.6% 46.3% 63.1% 63.6% 63.2% 60.9% 70.0% Specificity 61.5% 87.7% 73.4% 77.1% 67.4% 73.5% 73.9% AUC, area under curve; cutoff value (/µL) indicates a value that could with the optimal sum of highest sensitivity and specificity. platelet deficit on the test date indicated the deficit of platelet count from lowest normal limit on the test date (150 x103/µL - platelet count). Discussion Although thrombocytopenia had been recognized as a significant risk factor for PH in SM respiratory infection, in the present study, the degree of thrombocytopenia by platelet deficit at a single time point and over a certain time period was evaluated to identify the optimal cut-off value in predicting PH. Also, results of the present study demonstrated the clinical heterogeneity of thrombocytopenia as the cause and its association with PH, which may explain the conflicting findings of previous observational studies and address the need for more precise and individualized risk classification based on comorbidities. Different measurement tools should be used in distinct subpopulations to predict PH; for example, platelet counts at the test date should be sufficient in patients with hematological and liver diseases, while d-index using serial platelet measurements performs more reliably for those with sepsis and other causes. Mortality associated with PH was overwhelmingly high in the present study, especially in patients with hematologic malignancy. Recently, increasing numbers of cases have been successfully treated, which may be due to refinement of preventive measures of transmission, rising awareness of SM infections, and timely use of empirical antimicrobial therapy [18,19]. The mortality rate in the present study was highest within the first week of diagnosis (50%), demonstrating the potential fulminant behavior of SM infections. Notably, only one patient with hematological disease survived through hemorrhagic SM respiratory infection, and none of the neutropenic patients survived. In a previous study conducted by Bao et al, patients with severe prolonged neutropenia and thrombopenia due to hematological disorders were shown to have 100% mortality when encountering SM bacteremia [20]. The present study echoes their findings, indicating that hematological abnormalities complicate the clinical course of SM respiratory infection and worsen the disease outcome. Although neutrophil counts may have been a decisive factor in infection control and hematopoiesis ability, it was also shown to be a significant risk factor for PH in previous studies [15]. After multivariate analysis, we found that neutropenia was not an independent risk factor for PH or associated mortality, implying that neutropenia is probably a collateral finding along with underlying disease and thrombocytopenia. Patients in the “Sepsis-Rx” and “Others” groups with SM-associated PH had higher proportions of pulmonary structural abnormalities and mechanical use. Because these patients are likely to receive mechanical ventilation due to pulmonary structure anomaly, they acquired SM infection through ventilator use. Until now, the attributable factors causing SM-related VAP remain unclear [1, 16]. A recent study found that exposure to ureido/carboxypenicillin or carbapenem during the week before VAP, and the severity of disease leading to respiratory and hematological failures, were independent risk factors for SM-VAP [1]. Moreover, SM-VAP mortality remains high even in patients receiving adequate treatment, either monotherapy or combinations of antimicrobials. Platelet counts at a single time point or over a given time period were significantly lower in patients with hematological and liver diseases than in those with sepsis or other diseases, but risk for PH did not differ significantly between these patients. Although thrombocytopenia is an independent determining factor for PH, patients experiencing long-term thrombocytopenia may develop a certain mechanism by which to compensate for the bleeding tendency. A previous study identified that an increased number of larger-sized platelets may compensate for the impaired platelet function in patients with chronic idiopathic thrombocytopenia [17]. In acute myeloid leukemia patients who have thrombocytopenia, platelet aggregation and platelet activation predicted bleeding better than the platelet count alone [18]. Overall, the bleeding risk is not only dependent on the platelet count but also on the platelet function, coagulopathy, and the underlying disease causing thrombocytopenia. Further mechanistic exploration of the cause of reduced platelet counts or function in different thrombocytopenic conditions is still needed to help develop and implement preventive strategies [19]. In the present study, thrombocytopenia due to hematological and liver diseases both had prolonged and profound low platelet levels and PH usually developed at the nadir of the platelet level. Meanwhile, the pattern of thrombocytopenia due to sepsis/medication or other causes were more alike and had higher average platelet count compared to those in hematological and liver disease. Traditionally, the pathophysiology of thrombocytopenia in chronic liver disease has long been attributed to hypersplenism, where pooling and sequestration of blood results in platelet consumption. Recently, other mechanisms, including bone marrow suppression by toxic substances such as alcohol or viral infection may also contribute to thrombocytopenia. In addition, the thrombopoietin, predominantly produced by the liver is markedly reduced in advanced-staged liver disease, which also contributes to reduced thrombopoiesis in the bone marrow [20]. All mechanisms mentioned above can explain the thrombocytopenia caused by liver disease that may be secondary to bone marrow suppression, similar to those in hematological disorders. The clinical consensus regarding the lowest platelet level needed to prevent bleeding in certain circumstances is that platelet counts must be above 20–50 x10 3 /uL for bronchoscopy exams and 50 x10 3 /µL for transbronchial lung biopsies [21]. Statistical results from the present study show that platelet levels above 60–100 x10 3 /µL may plausibly prevent PH in patients with sepsis, liver disease and other causes, while lower platelet counts (above 17.5 x10 3 /µL) may be tolerated in patients with hematological diseases. In addition to certain cut-off levels for platelet counts, the accumulative platelet deficit over a given time period was found to be more reliable in predicting PH in patients with sepsis, medication-related, or other causes of thrombocytopenia. Although these groups of patients did not have thrombocytopenia as profound as in those with hematological disorders, they are more susceptible to developing PH in prolonged thrombocytopenia. Therefore, regular prophylactic platelet transfusion to maintain platelet levels above certain thresholds over unstable periods may be a potential strategy to prevent PH in this group of patients. The present study used the largest database evaluating PH in patients with SM respiratory infections and is also the first study to extrapolate serial platelet measurements in predicting PH. Data in the present study provide clinicians with the optimal cutoff platelet level for transfusion therapy to prevent PH in thrombocytopenia of various causes. The concept of using d-index as a personalized measurement in evaluating the severity of thrombocytopenia can be implemented to prevent SM hemorrhagic pneumonia and bleeding disorders in various other diseases. Especially in the era of the COVID-19 pandemic, clinicians may also utilize the d-index to assess the risk of PH in sepsis due to COVID-19. Regardless of the above strengths, the present study has several limitations. First is that we did not evaluate associations between PH, antibiotic use and corresponding antimicrobial susceptibility. Although in both clinical and animal studies, timely appropriate antibiotic use could reduce the risk of mortality in SM hemorrhagic pneumonia, systematic review demonstrated that even patients treated with appropriate antibiotics, including trimethoprim/sulfamethoxazole, fluoroquinolones, or both combined, the mortality remained high, even reaching 100% [11, 15]. Also, no prior antimicrobial therapy for SM bacteremia had shown a preventive effect for PH [7]. Still, prompt administration of antibiotics is essential for control of infectious disease, but the use of antibiotics in preventing PH in SM respiratory infection does not appear to be an adequate measure. Conclusion Prolonged and extreme thrombocytopenia is a determinant risk factor for PH in patients with SM respiratory infections. The degree of platelet deficit varies significantly between different causes of thrombocytopenia and types of underlying comorbidities. Single time-point measurement of platelet counts may most reliably predict PH in patients with hematological and liver diseases, while serial measurement over a given time period may reliably predict PH in those with sepsis and other causes of thrombocytopenia. Abbreviations APTT/MNAPTT, activated partial thromboplastin time/mean normal activated partial thromboplastin time; CRP, C-reactive protein; NFGNB, non-fermenting gram-negative bacillus; VAP, ventilator associated pneumonia; HCT, hemopoietic cell transplant; PCT, procalcitonin; PT/INR, prothrombin time and international normalized ratio; PH, Pulmonary hemorrhage; SM, Stenotrophomonas maltophilia; ROC, receiver operating characteristic; AUC, area under curve. Declarations Acknowledgements The authors would like to thank Chief, Shih Min Wang, in the Department of Pediatrics giving his full support to this study, and Ms Shih-Wei Wang, Ms Hui-Feng Lee for the assistance of data collection. Special thanks to George Kuo from Chang-Geng Medical Foundation, Linkou Chang-Geng Memorial Hospital for his advice on statistical analyses. Funding This work was supported by grants from the Clinical Medical Research Center, National Cheng Kung University Hospital, Taiwan (NCKUH-11002017) and Ministry of Science and Technology, Taiwan (110-2923-B-006-001-MY4). Availability of data and materials Datasets used and analyzed during the present study are available the Corresponding Author upon reasonable request. Ethics approval and consent to participate The Institutional Review Board of National Cheng Kung University Hospital reviewed and approved the study protocol (IRB no. A-ER-110-079). The study was performed in accordance with the Declaration of Helsinki. Owing to the study's retrospective nature, signed informed consent from patients was waived. Competing interests The authors declare that they have no competing interests. Consent for publication Not applicable. Authors’ contributions HCGW and CFS conceived the original study. CFS oversaw data collection. HCGW acquired all data. HSW wrote the d-index algorithm. Statistical analysis was overseen by CIL and CFS. HCGW analyzed the data, wrote the original manuscript, and prepared the final figures. CNC, CHC, and TSC had provided some insights regarding clinical association. CFS oversaw the analysis, writings, and figures. All authors have seen and approved the final version of the manuscript. Authors’ information Corresponding author: Ching-Fen Shen, MD, MSc. Address: Department of Pediatrics, National Cheng Kung University Hospital. No.138, Sheng-Li Road, North District, Tainan City, 704, Taiwan. E-mail: [email protected] ; Tel.: +886-6-2353535*4184; Fax: +886-6-275308. Author details 1 Department of Internal medicine, Chang Gung Memorial Hospital, Taoyuan, Taiwan. 2 Education Center, National Cheng Kung University Hospital, Tainan, Taiwan. 3 Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan. 4 Department of Pediatrics, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan. 5 Department of Internal Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan. 6 Department of Statistics, College of Management, National Cheng Kung University, Tainan, Taiwan. References Ibn Saied, W., et al., Ventilator-associated pneumonia due to Stenotrophomonas maltophilia: Risk factors and outcome. J Infect, 2020. 80(3): p. 279–285. Windhorst, S., et al., The major extracellular protease of the nosocomial pathogen Stenotrophomonas maltophilia: characterization of the protein and molecular cloning of the gene. J Biol Chem, 2002. 277(13): p. 11042-9. Guzoglu, N., F.N. Demirkol, and D. Aliefendioglu, Haemorrhagic pneumonia caused by Stenotrophomonas maltophilia in two newborns. J Infect Dev Ctries, 2015. 9(5): p. 533-5. Trifonova, A. and T. Strateva, Stenotrophomonas maltophilia - a low-grade pathogen with numerous virulence factors. Infect Dis (Lond), 2019. 51(3): p. 168–178. Gutierrez, C., et al., Fatal hemorrhagic pneumonia: Don't forget Stenotrophomonas maltophilia. Respir Med Case Rep, 2016. 19: p. 12 − 4. Imoto, W., et al., Clinical Characteristics of Rapidly Progressive Fatal Hemorrhagic Pneumonia Caused by Stenotrophomonas maltophilia. Intern Med, 2020. 59(2): p. 193–198. Zhu, L., et al., Fatal hemorrhagic pneumonia in patients with hematologic diseases and Stenotrophomonas maltophilia bacteremia: a retrospective study. BMC Infect Dis, 2021. 21(1): p. 723. Tada, K., et al., Stenotrophomonas maltophilia infection in hematopoietic SCT recipients: high mortality due to pulmonary hemorrhage. Bone Marrow Transplant, 2013. 48(1): p. 74 − 9. Mori, M., et al., Life-threatening hemorrhagic pneumonia caused by Stenotrophomonas maltophilia in the treatment of hematologic diseases. Ann Hematol, 2014. 93(6): p. 901 − 11. Araoka, H., et al., Rapidly progressive fatal hemorrhagic pneumonia caused by Stenotrophomonas maltophilia in hematologic malignancy. Transpl Infect Dis, 2012. 14(4): p. 355 − 63. Kim, S.H., et al., Pathogenic significance of hemorrhagic pneumonia in hematologic malignancy patients with Stenotrophomonas maltophilia bacteremia: clinical and microbiological analysis. Eur J Clin Microbiol Infect Dis, 2019. 38(2): p. 285–295. Portugal, R.D., M. Garnica, and M. Nucci, Index to predict invasive mold infection in high-risk neutropenic patients based on the area over the neutrophil curve. J Clin Oncol, 2009. 27(23): p. 3849-54. Yilmaz, G., et al., D-index: A New Scoring System in Febrile Neutropenic Patients for Predicting Invasive Fungal Infections. Turk J Haematol, 2016. 33(2): p. 102-6. Kimura, S., et al., Retrospective evaluation of the area over the neutrophil curve index to predict early infection in hematopoietic stem cell transplantation recipients. Biol Blood Marrow Transplant, 2010. 16(10): p. 1355-61. Penagos, S.C., et al., First report of survival in two patients with hematologic malignancy and Stenotrophomonas maltophilia hemorrhagic pneumonia treated with trimethoprim-sulfamethoxazole-based combination antibiotic therapy. J Infect Chemother, 2020. 26(4): p. 397–399. Scholte, J.B., et al., Stenotrophomonas maltophilia ventilator-associated pneumonia. A retrospective matched case-control study. Infect Dis (Lond), 2016. 48(10): p. 738 − 43. Nishiura, N., et al., Reevaluation of platelet function in chronic immune thrombocytopenia: impacts of platelet size, platelet-associated anti-alphaIIbbeta3 antibodies and thrombopoietin receptor agonists. Br J Haematol, 2020. 189(4): p. 760–771. Just Vinholt, P., et al., Platelet function tests predict bleeding in patients with acute myeloid leukemia and thrombocytopenia. Am J Hematol, 2019. 94(8): p. 891–901. Vinholt, P.J., The role of platelets in bleeding in patients with thrombocytopenia and hematological disease. Clin Chem Lab Med, 2019. 57(12): p. 1808–1817. Peck-Radosavljevic, M., Thrombocytopenia in chronic liver disease. Liver Int, 2017. 37(6): p. 778–793. Radchenko, C., A.H. Alraiyes, and S. Shojaee, A systematic approach to the management of massive hemoptysis. J Thorac Dis, 2017. 9(Suppl 10): p. S1069-S1086. Additional Declarations No competing interests reported. Supplementary Files Additionalfile1ROCCurveacrossdifferentgroupscomparingdindexandplateletdeficit.jpg Additional file 1 included: Figure 1a: Comparisons between all groups; Figure 1b: ROC curve of hematological and liver diseases related thrombocytopenia; Figure 1c: ROC curve of sepsis and others related thrombocytopenia; Figure 1d: ROC curve of hematological diseases related thrombocytopenia; 1e: ROC curve of liver diseases related thrombocytopenia; 1f: ROC curve of sepsis-medication related thrombocytopenia; 1g: ROC curve of other cause of thrombocytopenia; Additionalfile2Boxplotofsingledayandserialplateletdeficitbetweendifferentgroups.png Additional file 2 – Boxplot of single day and serial platelet deficit between different groupsAdditional file 2 included: Figure 2a: Boxplot of single day platelet deficit; Figure 2b: Boxplot of serial platelet deficit (d-index-14-days). Data are presented as box plot with a line at the median with platelet counts (/μL). Additionalfile3Univariateandmultivariateanalysisofriskfactorsassociatedwith30dayriskofpulmonaryhemorrhage.xlsx Additional file 3 – Univariate and multivariate analysis of risk factors associated with 30-day risk of pulmonary hemorrhage Additionalfile4Univariateandmultivariateanalysisofriskfactorsassociatedwith30daymortalityinpatientswithSMpulmonaryinfectioncomplicatedbypulmonaryhemorrhage.xlsx Additional file 4 – Univariate and multivariate analysis of risk factors associated with 30-day mortality in patients with SM pulmonary infection complicated by pulmonary hemorrhageAdditional file 4 Abbreviations: APTT/MNAPTT, activated partial thromboplastin time/mean normal activated partial thromboplastin time; PH, Pulmonary hemorrhage (patients with multiple episodes of hemoptysis with desaturation, evidence of deteriorating pulmonary function or anatomy (e.g., increased infiltrations in chest X-ray, increased oxygen demand). PT/INR, prothrombin time and international normalized ratio. Additionalfile5PosthocanalysiswithScheffesmethodoncharacteristicsofgroupswithdifferentcausesofthrombocytopeniainSMrespiratoryinfections.xlsx Additional file 5 – Post hoc analysis with Scheffe’s method on characteristics of groups with different causes of thrombocytopenia in SM respiratory infections. *. Mean difference is significant at p <0.05 level. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1360630","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":84170399,"identity":"edcaf286-2f69-4550-ba78-b00219c3be16","order_by":0,"name":"Huai-Chueh Gem Wu","email":"","orcid":"","institution":"Chang Gung Memorial Hospital","correspondingAuthor":false,"prefix":"","firstName":"Huai-Chueh","middleName":"Gem","lastName":"Wu","suffix":""},{"id":84170400,"identity":"c016c5b7-0621-408c-a4bb-04b49ef774bd","order_by":1,"name":"Huai-Shing Wu","email":"","orcid":"","institution":"National Taiwan University","correspondingAuthor":false,"prefix":"","firstName":"Huai-Shing","middleName":"","lastName":"Wu","suffix":""},{"id":84170402,"identity":"36dbf696-1111-483b-816d-0c1ee42aea8f","order_by":2,"name":"Chao-Neng Cheng","email":"","orcid":"","institution":"National Cheng Kung University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chao-Neng","middleName":"","lastName":"Cheng","suffix":""},{"id":84170403,"identity":"42bfb273-560a-41d6-a676-aa92e1457e24","order_by":3,"name":"Jiann-Shiuh Chen","email":"","orcid":"","institution":"National Cheng Kung University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jiann-Shiuh","middleName":"","lastName":"Chen","suffix":""},{"id":84170404,"identity":"75c50f0a-a0d1-41fb-9d96-bbcf7f444d9a","order_by":4,"name":"Tsai-Yun Chen","email":"","orcid":"","institution":"National Cheng Kung University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Tsai-Yun","middleName":"","lastName":"Chen","suffix":""},{"id":84170406,"identity":"0df9d6b2-657d-4ffc-b29c-b4fc70f9b951","order_by":5,"name":"Chung-I Li","email":"","orcid":"","institution":"National Cheng Kung University","correspondingAuthor":false,"prefix":"","firstName":"Chung-I","middleName":"","lastName":"Li","suffix":""},{"id":84170407,"identity":"a8895af9-c33d-4639-a227-3afc2c012778","order_by":6,"name":"Ching-Fen Shen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2klEQVRIiWNgGAWjYDCCAwxsQFKCh429+QCIIUOsFgsZPp5jCWC9xGqpsJGTyDEA8Qlr4bt9/NmDjzuADmPI+fzqRo0FDwP74aMb8GmRPJdjbjjzDEjL2W3WOceADuNJS7uBT4vBGR42ad42oBbG3m3GOWxALRI8ZgS0sD+T/gvSwszzzDjnH1FaGMykGUFa2HiYH+e2EaFF8gyPmWQvSAsPmxlzbh+IQcAvfECHSfxsq7OXn//48eecb3Vy/OyHj+HVggzYJMAkscpBgPkDKapHwSgYBaNg5AAAocg/dKSacCsAAAAASUVORK5CYII=","orcid":"","institution":"National Cheng Kung University Hospital","correspondingAuthor":true,"prefix":"","firstName":"Ching-Fen","middleName":"","lastName":"Shen","suffix":""}],"badges":[],"createdAt":"2022-02-15 06:29:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1360630/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1360630/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":18341675,"identity":"5cbe5d94-2710-4377-b40f-b3dcb98b47f3","added_by":"auto","created_at":"2022-02-17 21:37:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":61215,"visible":true,"origin":"","legend":"\u003cp\u003eReceiver Operating Curve (ROC) of various measurements in predicting pulmonary hemorrhage in patient with SM infection\u0026nbsp;\u003c/p\u003e\u003cp\u003eAbbreviations: Platelet deficit of test date, the deficit of platelet count from lowest normal limit on the test date (150 x10\u003csup\u003e3\u003c/sup\u003e/uL - platelet count). d_6, daily average of d-index 3 days before and after sputum test date, d_10, daily average of d-index 5 days before and after sputum test date, d_14, daily average of d-index 7 days before and after sputum test date.\u003c/p\u003e","description":"","filename":"fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-1360630/v1/39cbf283ba8a672ac7b8f4d0.png"},{"id":18941820,"identity":"c21b2743-1a11-432a-91b2-581a7bdfe076","added_by":"auto","created_at":"2022-03-07 17:14:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":386049,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1360630/v1/512edb14-f46d-41d7-9374-48d0d87bb4df.pdf"},{"id":18341874,"identity":"c7ea4ead-91da-4bf7-b6b9-8765772fd783","added_by":"auto","created_at":"2022-02-17 21:40:02","extension":"jpg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1841322,"visible":true,"origin":"","legend":"\u003cp\u003eAdditional file 1 included: Figure 1a: Comparisons between all groups; Figure 1b: ROC curve of hematological and liver diseases related thrombocytopenia; Figure 1c: ROC curve of sepsis and others related thrombocytopenia; Figure 1d: ROC curve of hematological diseases related thrombocytopenia; 1e: ROC curve of liver diseases related thrombocytopenia; 1f: ROC curve of sepsis-medication related thrombocytopenia; 1g: ROC curve of other cause of thrombocytopenia;\u0026nbsp;\u003c/p\u003e","description":"","filename":"Additionalfile1ROCCurveacrossdifferentgroupscomparingdindexandplateletdeficit.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1360630/v1/eb4c2d8a2b2d188d8dccf07d.jpg"},{"id":18341680,"identity":"c0ffd1ae-11aa-482c-9e6f-fd72507eb80e","added_by":"auto","created_at":"2022-02-17 21:37:02","extension":"png","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":579450,"visible":true,"origin":"","legend":"\u003cp\u003eAdditional file 2 – Boxplot of single day and serial platelet deficit between different groups\u003c/p\u003e\u003cp\u003eAdditional file 2 included: Figure 2a: Boxplot of single day platelet deficit; Figure 2b: Boxplot of serial platelet deficit (d-index-14-days). Data are presented as box plot with a line at the median with platelet counts (/μL).\u003c/p\u003e","description":"","filename":"Additionalfile2Boxplotofsingledayandserialplateletdeficitbetweendifferentgroups.png","url":"https://assets-eu.researchsquare.com/files/rs-1360630/v1/1f95bfb7b836f33f88e6c8b6.png"},{"id":18341677,"identity":"67f03ece-420f-4320-be16-ed74afb19ce9","added_by":"auto","created_at":"2022-02-17 21:37:01","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":16739,"visible":true,"origin":"","legend":"\u003cp\u003eAdditional file 3 – Univariate and multivariate analysis of risk factors associated with 30-day risk of pulmonary hemorrhage\u003c/p\u003e","description":"","filename":"Additionalfile3Univariateandmultivariateanalysisofriskfactorsassociatedwith30dayriskofpulmonaryhemorrhage.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1360630/v1/32dd781b1f263286c27792d1.xlsx"},{"id":18341676,"identity":"ab98cfe8-33b1-4e44-9fd9-ad0b0e27fab1","added_by":"auto","created_at":"2022-02-17 21:37:01","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":10833,"visible":true,"origin":"","legend":"\u003cp\u003eAdditional file 4 – Univariate and multivariate analysis of risk factors associated with 30-day mortality in patients with SM pulmonary infection complicated by pulmonary hemorrhage\u003c/p\u003e\u003cp\u003eAdditional file 4 Abbreviations: APTT/MNAPTT, activated partial thromboplastin time/mean normal activated partial thromboplastin time; PH, Pulmonary hemorrhage (patients with multiple episodes of hemoptysis with desaturation, evidence of deteriorating pulmonary function or anatomy (e.g., increased infiltrations in chest X-ray, increased oxygen demand). PT/INR, prothrombin time and international normalized ratio.\u003c/p\u003e","description":"","filename":"Additionalfile4Univariateandmultivariateanalysisofriskfactorsassociatedwith30daymortalityinpatientswithSMpulmonaryinfectioncomplicatedbypulmonaryhemorrhage.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1360630/v1/83811a205b34cab165d49551.xlsx"},{"id":18341678,"identity":"c730b6e8-c8a3-44d0-8290-19dcd5fbbbe4","added_by":"auto","created_at":"2022-02-17 21:37:01","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":16713,"visible":true,"origin":"","legend":"\u003cp\u003eAdditional file 5 – Post hoc analysis with Scheffe’s method on characteristics of groups with different causes of thrombocytopenia in SM respiratory infections. *. Mean difference is significant at p \u0026lt;0.05 level.\u003c/p\u003e","description":"","filename":"Additionalfile5PosthocanalysiswithScheffesmethodoncharacteristicsofgroupswithdifferentcausesofthrombocytopeniainSMrespiratoryinfections.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1360630/v1/a2afe544f04437a34dac7b9b.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eSerial Platelet Level Index Improves Prediction of Pulmonary Hemorrhage in \u003cem\u003eStenotrophomonas maltophilia\u003c/em\u003e Respiratory Infections\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003e \u003cem\u003eStenotrophomonas maltophilia\u003c/em\u003e (SM) is a ubiquitous, globally emerging, multiple-drug resistant, non-fermenting gram-negative bacillus (NFGNB) that typically causes opportunistic infection in severely immunocompromised or debilitated patients. Respiratory infection, including ventilator associated pneumonia (VAP), is the most common clinical presentation of SM and potentially results in pulmonary hemorrhage (PH) [1]. The extracellular protease secreted by SM is reported to cause tissue destruction, vascular damage, and subsequent hemorrhage [2\u0026ndash;4]. Although pulmonary hemorrhage (PH) is an uncommon complication of SM respiratory infection, previous studies have reported mortality as high as 85% within 30 days of infection onset [5\u0026ndash;10].\u003c/p\u003e \u003cp\u003eRisk factors for PH have been identified in different clinical settings and in patients with various comorbidities. Hematologic malignancy and thrombocytopenia were found to be predictive factors of hemorrhagic pneumonia in SM bacteremia patients [6, 11]. Also, neutropenia, longer duration of neutropenia, high C-reactive protein (CRP) or procalcitonin (PCT) levels, and persistent fever despite using broad-spectrum antibiotics are independent predictors of PH in hemopoietic cell transplant (HCT) recipients or patients with other hematologic diseases [7, 8]. Although thrombocytopenia has been identified as an important risk factor for hemorrhagic complications in general practice, no comprehensive evaluation has yet addressed the degree of thrombocytopenia and its association with PH in SM infections. The cumulative d-index (c-d-index) is a scoring system that uses absolute neutrophil counts over the course of neutropenia to characterize the degree and durability of neutropenia; the index has been applied to febrile neutropenic patients to assess the risk of invasive mold infections [12\u0026ndash;14]. The present study aimed to develop an index of serial platelet levels from different time windows to evaluate the degree of thrombocytopenia and explore associations between the platelet D-index and PH in respiratory SM infections.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cp\u003eEthics statement\u003c/p\u003e\n\u003cp\u003eThe Institutional Review Board of National Cheng Kung University Hospital reviewed and approved the study protocol (IRB no. A-ER-110-079). The study was performed in accordance with the Declaration of Helsinki. Owing to the study\u0026apos;s retrospective nature, signed informed consent from patients was waived.\u003c/p\u003e\n\u003cp\u003ePatients\u003c/p\u003e\n\u003cp\u003eThe electronic medical records from National Cheng Kung University Hospital, Tainan, Taiwan, were searched using the criteria of hospitalized patients with positive SM isolated from sputum culture between January 2018 and December 2020. Only data of patients with SM respiratory infection and thrombocytopenia were extracted from the medical records database. Positive SM was defined as having both respiratory symptoms and thrombocytopenia (platelet count\u0026thinsp;\u0026lt;\u0026thinsp;150 x10\u003csup\u003e3\u003c/sup\u003e/\u0026micro;L) 7 days before and after the date of sputum culture collection. Patients with duplicate culture results within the same hospitalization period were merged as a single event. Cases with (1) normal or high platelet count seven days before and after the date of sputum culture collection, (2) evidence of pulmonary invasive fungal infection, (3) only Stenotrophomonas colonization without respiratory symptoms, or (4) incomplete clinical data, were excluded.\u003c/p\u003e\n\u003cp\u003eClinical variables and data collection\u003c/p\u003e\n\u003cp\u003eDemographic and clinical data, including age, sex, reason for admission, existence of hematological disease, alternation or disruptions in pulmonary structure (e.g., lung cancer, intrathoracic surgery, tuberculoma), existence of neutropenia (\u0026lt;\u0026thinsp;500/\u0026micro;L), PT/APTT ratio within a week (APTT/MNAPTT\u0026thinsp;\u0026gt;\u0026thinsp;1.2 and INR\u0026thinsp;\u0026gt;\u0026thinsp;1.2 was considered prolonged), platelet count on the day of sputum culture and use of mechanical ventilation, were extracted from the electronic medical records. Causes of thrombocytopenia were grouped as follows: sepsis-medication related (\u0026ldquo;Sepsis-Rx\u0026rdquo;) (e.g., disseminated intravascular coagulation due to severe infection, medication-related platelet destruction); hematological disease and chemotherapeutics use due to oncological disease(\u0026ldquo;Hem-Onc\u0026rdquo;); liver disease (\u0026ldquo;Liver\u0026rdquo;); and various other causes (\u0026ldquo;Others\u0026rdquo;) (e.g., mechanical destruction, transfusion consumption coagulopathy or major bleeding, unknown cause). PH was defined in patients with multiple episodes of hemoptysis and desaturation or evidence of deteriorating pulmonary function or anatomy (e.g., increased infiltrations in chest X-ray, increased oxygen demand).\u003c/p\u003e\n\u003cp\u003ePlatelet D-Index and Platelet Deficit Calculation\u003c/p\u003e\n\u003cp\u003eD-index was applied in patients with prolonged neutropenia and opportunistic infections using an accumulated difference between neutrophil count and the threshold of neutropenia, as described previously [12\u0026ndash;14]. The same rationale was applied to estimate the accumulated platelet deficit in thrombocytopenic patients. The Platelet D-index was calculated using this algorithm.\u003c/p\u003e\n\u003cdiv class=\"Equation\" id=\"Equa\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e$$Platelet {D}_{index}= {A}_{e}- {A}_{0}= {\\sum }_{i=2}^{n}\\left[150*\\left({t}_{i}-{t}_{i-1}\\right)\\right]-{\\sum }_{i=2}^{n}\\left[\\frac{{P}_{i-1}+{P}_{i}}{2}*\\right({t}_{i}-{t}_{i-1}\\left)\\right]$$\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003eAccumulated platelet deficit between estimated area under curve (Ae) and observed area under curve (Ao) 7 days before and after sputum culture result of SM was calculated. Time window of platelet d-index included 3 days before and after SM sputum test date (d-index-6), 5 days before and after (d-index-10), and 7 days before and after (d-index-14). The platelet deficit was calculated using the lowest level of normal platelet count (150 x10\u003csup\u003e3\u003c/sup\u003e/\u0026micro;L) minus the platelet count at test date.\u003c/p\u003e\n\u003cdiv class=\"Section2\" id=\"Sec3\"\u003e\n \u003ch2\u003eStatistical Analysis\u003c/h2\u003e\n \u003cp\u003eAll statistical analyses were performed using SPSS 17 for Windows (IBM SPSS, Armonk, NY, USA). Patients with SM respiratory infections were grouped as \u0026ldquo;with PH\u0026rdquo; or \u0026ldquo;without PH\u0026rdquo;. The independent sample t-test was used for continuous variables, and the Chi-square test or Fisher\u0026rsquo;s exact test was used for dichotomous variables. P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. Cox\u0026rsquo;s proportional hazard analysis was used to determine risk factors for PH and 30-day mortality. One-way ANOVA was used to assess platelet levels and d-index of various causes of thrombocytopenia. To assess the ability of platelet d-index for different time windows and platelet deficits of a single day to predict pulmonary hemorrhage, sensitivity and specificity were analyzed using receiver operating characteristic (ROC) curves across the sputum sampling day showing SM positive. The optimal cut-off value was determined by the maximum sum of sensitivity and specificity.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eStudy population\u003c/p\u003e\n\u003cp\u003eOf the 437 patients with thrombocytopenic SM respiratory infection, 125 patients (28.6%) developed PH. Patients\u0026rsquo; demographic and clinical characteristics are shown in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. No significant differences were found in age, sex, and cause of thrombocytopenia between patients with and without PH. The most common causes of thrombocytopenia were \u0026ldquo;Sepsis-Rx\u0026rdquo; (57.0%), followed by \u0026ldquo;Others\u0026rdquo; (15.1%), \u0026ldquo;Liver disease\u0026rdquo; (14.9%), and \u0026ldquo;Hem-Onc\u0026rdquo; (13.0%). Although hematological disease accounts for the majority (48/57, 84.2%) of cases in the \u0026ldquo;Hem-Onc\u0026rdquo; group, the proportion of hematological diseases was not significantly different between the \u0026ldquo;Hem-Onc and \u0026ldquo;Liver\u0026rdquo; groups. Platelet counts at the test date were lower, and the d-index of different time frames was higher in the PH group than in the non-PH group (\u003cem\u003eP\u003c/em\u003e value\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Also, prolonged PT/INR and mechanical ventilation use were significantly associated with PH (all \u003cem\u003eP\u003c/em\u003e value\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The mortality of SM respiratory infection was higher in the PH group than in the non-PH group (87.2% vs. 57.7%, \u003cem\u003eP\u003c/em\u003e value\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with the overall rate of 66.1%. Half of the patients with PH died within the first week after diagnosis, and the mortality rate declined in the second and third weeks. None of the neutropenic patients with PH (n\u0026thinsp;=\u0026thinsp;15) survived.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u003ctable border=\"1\" id=\"Tab1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDemographic and clinical characteristics of patients with SM respiratory infections\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAll Patients\u003c/p\u003e\n \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;437)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePatients without pulmonary hemorrhage\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;312)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePatients with Pulmonary Hemorrhage\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;125)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex, Male, no. (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e273 (62.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e187 (59.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86 (68.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.084\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge, years, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69 (59\u0026ndash;79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69 (59\u0026ndash;80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70 (59\u0026ndash;78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.467\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eComorbidities associated with thrombocytopenia, no. (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.377\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHema-Onc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57 (13.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35 (11.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22 (17.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLiver disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65 (14.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46 (14.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (15.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSepsis-Rx\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e249 (57.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e185 (59.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64 (51.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66 (15.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46 (14.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (16.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePulmonary structural abnormalities, no. (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e160 (36.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e112 (35.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48 (38.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.624\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMechanical ventilation, no. (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e362 (82.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e250 (80.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e112 (89.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.018*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeutropenia, no. (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43 (9.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 (9.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (12.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.337\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAPTT/MNAPTT ratio, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.04 (0.93\u0026ndash;1.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.01 (0.91\u0026ndash;1.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.14 (0.99\u0026ndash;1.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.506\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePT-INR, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.31 (1.16\u0026ndash;1.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.28 (1.14\u0026ndash;1.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.36 (1.22\u0026ndash;1.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.007*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePlatelet count at test date, mean (range) (10\u003csup\u003e3\u003c/sup\u003e/\u0026micro;L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85.17 (6-399)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e92.30 (6-324)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67.90 (6-399)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ed-index per day, mean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ed-index-14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e88.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ed-index-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e90.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ed-index-6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e91.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMortality, no. (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e289 (66.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e180 (57.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e109 (87.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ewithin 7 days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e132 (30.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70 (22.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62 (49.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ewithin 14 days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e190 (43.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e102 (32.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e88 (70.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ewithin 30 days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e229 (52.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e130 (41.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99 (79.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eAPTT/MNAPTT, activated partial thromboplastin time/mean normal activated partial thromboplastin time; PT/INR, prothrombin time and international normalized ratio\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eRisk factors associated with pulmonary hemorrhage and mortality\u003c/p\u003e\n\u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and Supplementary Table 2 list the results of Cox proportional hazard analysis of risk factors associated with PH in neutropenic SM respiratory infections and risk factors associated with 30-day mortality in the PH group, respectively. In univariate analysis, neutropenia, and extreme thrombocytopenia (platelet count at test date\u0026thinsp;\u0026lt;\u0026thinsp;50 x10\u003csup\u003e3\u003c/sup\u003e/\u0026micro;L) were both risk factors for PH and 30-day mortality. However, multivariate analysis showed that severe thrombocytopenia was the only independent risk factor for both PH and 30-day mortality in PH patients.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u003ctable border=\"1\" id=\"Tab2\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eUnivariate and multivariate analysis of risk factors associated with pulmonary hemorrhage in patients with SM respiratory infections\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eRisk factors associated with pulmonary hemorrhage\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariate analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariate analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHazard ratio (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHazard ratio (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u0026thinsp;\u0026gt;\u0026thinsp;65 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.032 (0.790\u0026ndash;1.621)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale sex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.176 (0.805\u0026ndash;1.718)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.402\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeutropenia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.005 (1.145\u0026ndash;3.511)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.015*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.399 (0.725\u0026ndash;2.699)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.316\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePulmonary structural abnormalities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.013 (0.705\u0026ndash;1.456)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.943\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMechanical Ventilation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.858 (0.480\u0026ndash;1.533)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.605\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAPTT/MNAPTT\u0026thinsp;\u0026gt;\u0026thinsp;1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.080 (0.720\u0026ndash;1.621)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.709\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.971 (0.615\u0026ndash;1.532)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.899\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eINR\u0026thinsp;\u0026gt;\u0026thinsp;1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.066 (0.661\u0026ndash;1.721)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.793\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.062 (0.590\u0026ndash;1.912)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.842\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePlatelet at test date\u0026thinsp;\u0026lt;\u0026thinsp;50 x10\u003csup\u003e3\u003c/sup\u003e/\u0026micro;L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.787 (1.230\u0026ndash;2.596)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.002*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.310 (1.346\u0026ndash;3.965)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.002*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eAPTT/MNAPTT, activated partial thromboplastin time/mean normal activated partial thromboplastin time; PT/INR, prothrombin time and international normalized ratio.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eCharacteristics of SM respiratory infections by cause of thrombocytopenia\u003c/p\u003e\n\u003cp\u003eComparison of clinical characteristics and laboratory findings between patients with thrombocytopenic SM respiratory infection caused by thrombocytopenia is shown in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. The \u0026ldquo;Sepsis-Rx\u0026rdquo; group had more patients aged 65 years and older (67.9%), higher pulmonary structural abnormalities (41.8%), and greater need for mechanical ventilation (86.7%). Platelet counts at the test date were significantly lower in patients in \u0026ldquo;Hem-Onc\u0026rdquo; and \u0026ldquo;Liver\u0026rdquo; groups than those in the \u0026ldquo;Sepsis-Rx\u0026rdquo; and \u0026ldquo;Others\u0026rdquo; groups, with the most extreme thrombocytopenia (platelets\u0026thinsp;\u0026lt;\u0026thinsp;50 x10\u003csup\u003e3\u003c/sup\u003e/\u0026micro;L) cases in the \u0026ldquo;Hem-Onc\u0026rdquo; group. The d-index-14 was inversely correlated with platelet counts at the test date and was significantly higher in patients in the \u0026ldquo;Hem-Onc\u0026rdquo; and \u0026ldquo;Liver\u0026rdquo; groups than those in the \u0026ldquo;Sepsis-Rx\u0026rdquo; and \u0026ldquo;Others\u0026rdquo; groups. However, the percentage of PH and the time to developing PH from diagnosis were not significantly different between these four groups. Mortality rates (66.1%) were significantly higher in the \u0026ldquo;Hem-Onc\u0026rdquo; (71.9%) and \u0026ldquo;Sepsis-Rx\u0026rdquo; (71.9%) groups than those in the \u0026ldquo;Liver\u0026rdquo; (52.3%) and \u0026ldquo;Others\u0026rdquo; groups (53%).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u003ctable border=\"1\" id=\"Tab3\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparison of clinical characteristics and laboratory findings between patients with SM respiratory infections by different comorbidities\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOverall (N\u0026thinsp;=\u0026thinsp;437)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHema-Onc (n\u0026thinsp;=\u0026thinsp;57)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLiver (n\u0026thinsp;=\u0026thinsp;65)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSepsis-Rx (n\u0026thinsp;=\u0026thinsp;249)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOthers (n\u0026thinsp;=\u0026thinsp;66)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u0026thinsp;\u0026gt;\u0026thinsp;65-year-old, no. (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e264 (60.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e28 (49.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29 (44.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e169 (67.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38 (57.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale sex, no. (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e273 (62.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34 (59.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42 (64.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e156 (62.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41 (62.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.955\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePulmonary structural abnormalities, no. (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e160 (36.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15 (26.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e104 (41.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 (42.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.003*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMechanical ventilation, no. (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e362 (82.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37 (64.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49 (75.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e216 (86.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60 (90.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAPTT/MNAPTT\u0026thinsp;\u0026gt;\u0026thinsp;1.2, no. (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e92 (28.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11 (26.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47 (26.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (28.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.311\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eINR\u0026thinsp;\u0026gt;\u0026thinsp;1.2, no. (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e222 (66.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e31 (72.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46 (79.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e116 (62.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29 (59.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePlatelet count at test date (10\u003csup\u003e3\u003c/sup\u003e/\u0026micro;L), mean (CI 95%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e85.32 (80.33\u0026ndash;90.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45.82 (34.99\u0026ndash;56.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65.62 (56.55\u0026ndash;74.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e94.93 (88.46\u0026ndash;101.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e102.59 (88.12-117.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePercentage of extreme thrombocytopenia (\u0026thinsp;\u0026lt;\u0026thinsp;=\u0026thinsp;50 x10\u003csup\u003e3\u003c/sup\u003e/\u0026micro;L), no. (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9 (2.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7 (12.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1 (0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (1.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ed-index-14, mean (CI 95%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e68.33 (64.44\u0026ndash;72.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e104.08 (94.62-113.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83.04 (75.79\u0026ndash;90.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e59.79 (54.71\u0026ndash;64.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55.21 (45.74\u0026ndash;64.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.008*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePulmonary hemorrhage (PH), no. (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e125 (28.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22 (38.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (29.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e64 (25.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (30.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.270\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTime to development of PH; mean days (CI 95%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.94 (3.55\u0026ndash;8.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.96 (0.35\u0026ndash;5.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.00 (1.18\u0026ndash;4.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.83 (3.78\u0026ndash;11.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.95 (0.00-12.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.148\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDeath, no. (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e289 (66.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e41 (71.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34 (52.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e179 (71.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35 (53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.002*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003eAPTT/MNAPTT, activated partial thromboplastin time/mean normal activated partial thromboplastin time; PT/INR, prothrombin time and international normalized ratio. (Available data of APTT n\u0026thinsp;=\u0026thinsp;318, PT n\u0026thinsp;=\u0026thinsp;335.) d-index-14, d-index 7 days before and after sputum test date.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003ePlatelet count-derived clinical parameters in predicting PH\u003c/p\u003e\n\u003cp\u003eVarious platelet count-derived clinical parameters were used to predict PH in patients with thrombocytopenia SM respiratory infection and the performance is shown in Fig. 1 and Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e. The predictability of these parameters varied across different causes of thrombocytopenia, and d-index-10 had the highest AUC (0.719) in all cases. Platelet deficit performed more reliably than d-index in the \u0026ldquo;Hem-Onc,\u0026rdquo; and \u0026ldquo;Liver\u0026rdquo; groups, and the two groups combined. In contrast, d-index performed more reliably in the \u0026ldquo;Sepsis-Rx\u0026rdquo; and \u0026ldquo;Others\u0026rdquo; groups. D-index-14 of the \u0026ldquo;Others\u0026rdquo; group showed the highest rate of predictability (AUC\u0026thinsp;=\u0026thinsp;0.816) of PH across all groups. The cutoff values of platelet deficit and d-index-14 according to the maximum sums of sensitivity and specificity are listed in Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e. The optimal cutoff value of platelet deficit on the test date for all cases was 70.5 x10\u003csup\u003e3\u003c/sup\u003e /uL, corresponding to platelet levels of 79.5 x10\u003csup\u003e3\u003c/sup\u003e /uL with a sensitivity of 69.8% and a specificity of 57.7% in predicting PH. The optimal platelet cut-off value at the test date varied across the four groups, from 17.5 x10\u003csup\u003e3\u003c/sup\u003e /uL in the \u0026ldquo;Hem-Onc\u0026rdquo; group, to 67.5 x10\u003csup\u003e3\u003c/sup\u003e /uL in the \u0026ldquo;Liver\u0026rdquo; group, 86.5 x10\u003csup\u003e3\u003c/sup\u003e /uL in the \u0026ldquo;Sepsis-Rx\u0026rdquo; group, and 106 x10\u003csup\u003e3\u003c/sup\u003e /uL in the \u0026ldquo;Others\u0026rdquo; group. We subtracted the d-index-14 by days to calculate the average platelet deficit per day and the corresponding value had a similar pattern as the platelet deficit at the test date, but with more reliability in \u0026ldquo;Sepsis-Rx\u0026rdquo; and \u0026ldquo;Others\u0026rdquo; group.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u003ctable border=\"1\" id=\"Tab4\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePerformance of various measurements in predicting pulmonary hemorrhage in patients with SM respiratory infection by different comorbidities\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"8\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAUC\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAll\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHema-Onc\u003c/p\u003e\n \u003cp\u003e\u0026amp; Liver\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSepsis-Rx \u0026amp; Others\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHema-Onc\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLiver\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSepsis-Rx\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePlatelet deficit of test date\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.699\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.729\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.684\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.757\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.705\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.664\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.757\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ed-index-6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.717\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.691\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.724\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.676\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.689\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.701\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.808\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ed-index-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.719\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.688\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.734\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.698\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.674\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.712\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.807\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ed-index-14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.714\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.672\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.734\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.688\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.648\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.711\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.816\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePlatelet deficit at test date\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecutoff value, 10\u003csup\u003e3\u003c/sup\u003e/\u0026micro;L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e70.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e118.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e48.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e132.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e82.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e63.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e44.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSensitivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e69.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e53.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e77.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e84.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e68.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e85.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSpecificity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e57.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e81.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e48.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e88.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e52.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e59.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e54.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePlatelet deficit derived from d-index-14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ecutoff value, 10\u003csup\u003e3\u003c/sup\u003e/\u0026micro;L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e71.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e117.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e71.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e117.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e92.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e71.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e71.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSensitivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e70.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e46.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e63.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e63.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e63.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e60.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e70.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSpecificity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e61.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e87.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e73.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e77.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e67.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e73.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e73.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\"\u003eAUC, area under curve; cutoff value (/\u0026micro;L) indicates a value that could with the optimal sum of highest sensitivity and specificity. platelet deficit on the test date indicated the deficit of platelet count from lowest normal limit on the test date (150 x103/\u0026micro;L - platelet count).\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eAlthough thrombocytopenia had been recognized as a significant risk factor for PH in SM respiratory infection, in the present study, the degree of thrombocytopenia by platelet deficit at a single time point and over a certain time period was evaluated to identify the optimal cut-off value in predicting PH. Also, results of the present study demonstrated the clinical heterogeneity of thrombocytopenia as the cause and its association with PH, which may explain the conflicting findings of previous observational studies and address the need for more precise and individualized risk classification based on comorbidities. Different measurement tools should be used in distinct subpopulations to predict PH; for example, platelet counts at the test date should be sufficient in patients with hematological and liver diseases, while d-index using serial platelet measurements performs more reliably for those with sepsis and other causes.\u003c/p\u003e \u003cp\u003eMortality associated with PH was overwhelmingly high in the present study, especially in patients with hematologic malignancy. Recently, increasing numbers of cases have been successfully treated, which may be due to refinement of preventive measures of transmission, rising awareness of SM infections, and timely use of empirical antimicrobial therapy [18,19]. The mortality rate in the present study was highest within the first week of diagnosis (50%), demonstrating the potential fulminant behavior of SM infections. Notably, only one patient with hematological disease survived through hemorrhagic SM respiratory infection, and none of the neutropenic patients survived. In a previous study conducted by Bao et al, patients with severe prolonged neutropenia and thrombopenia due to hematological disorders were shown to have 100% mortality when encountering SM bacteremia [20]. The present study echoes their findings, indicating that hematological abnormalities complicate the clinical course of SM respiratory infection and worsen the disease outcome. Although neutrophil counts may have been a decisive factor in infection control and hematopoiesis ability, it was also shown to be a significant risk factor for PH in previous studies [15]. After multivariate analysis, we found that neutropenia was not an independent risk factor for PH or associated mortality, implying that neutropenia is probably a collateral finding along with underlying disease and thrombocytopenia.\u003c/p\u003e \u003cp\u003ePatients in the \u0026ldquo;Sepsis-Rx\u0026rdquo; and \u0026ldquo;Others\u0026rdquo; groups with SM-associated PH had higher proportions of pulmonary structural abnormalities and mechanical use. Because these patients are likely to receive mechanical ventilation due to pulmonary structure anomaly, they acquired SM infection through ventilator use. Until now, the attributable factors causing SM-related VAP remain unclear [1, 16]. A recent study found that exposure to ureido/carboxypenicillin or carbapenem during the week before VAP, and the severity of disease leading to respiratory and hematological failures, were independent risk factors for SM-VAP [1]. Moreover, SM-VAP mortality remains high even in patients receiving adequate treatment, either monotherapy or combinations of antimicrobials.\u003c/p\u003e \u003cp\u003ePlatelet counts at a single time point or over a given time period were significantly lower in patients with hematological and liver diseases than in those with sepsis or other diseases, but risk for PH did not differ significantly between these patients. Although thrombocytopenia is an independent determining factor for PH, patients experiencing long-term thrombocytopenia may develop a certain mechanism by which to compensate for the bleeding tendency. A previous study identified that an increased number of larger-sized platelets may compensate for the impaired platelet function in patients with chronic idiopathic thrombocytopenia [17]. In acute myeloid leukemia patients who have thrombocytopenia, platelet aggregation and platelet activation predicted bleeding better than the platelet count alone [18]. Overall, the bleeding risk is not only dependent on the platelet count but also on the platelet function, coagulopathy, and the underlying disease causing thrombocytopenia. Further mechanistic exploration of the cause of reduced platelet counts or function in different thrombocytopenic conditions is still needed to help develop and implement preventive strategies [19].\u003c/p\u003e \u003cp\u003eIn the present study, thrombocytopenia due to hematological and liver diseases both had prolonged and profound low platelet levels and PH usually developed at the nadir of the platelet level. Meanwhile, the pattern of thrombocytopenia due to sepsis/medication or other causes were more alike and had higher average platelet count compared to those in hematological and liver disease. Traditionally, the pathophysiology of thrombocytopenia in chronic liver disease has long been attributed to hypersplenism, where pooling and sequestration of blood results in platelet consumption. Recently, other mechanisms, including bone marrow suppression by toxic substances such as alcohol or viral infection may also contribute to thrombocytopenia. In addition, the thrombopoietin, predominantly produced by the liver is markedly reduced in advanced-staged liver disease, which also contributes to reduced thrombopoiesis in the bone marrow [20]. All mechanisms mentioned above can explain the thrombocytopenia caused by liver disease that may be secondary to bone marrow suppression, similar to those in hematological disorders.\u003c/p\u003e \u003cp\u003eThe clinical consensus regarding the lowest platelet level needed to prevent bleeding in certain circumstances is that platelet counts must be above 20\u0026ndash;50 x10\u003csup\u003e3\u003c/sup\u003e /uL for bronchoscopy exams and 50 x10\u003csup\u003e3\u003c/sup\u003e /\u0026micro;L for transbronchial lung biopsies [21]. Statistical results from the present study show that platelet levels above 60\u0026ndash;100 x10\u003csup\u003e3\u003c/sup\u003e /\u0026micro;L may plausibly prevent PH in patients with sepsis, liver disease and other causes, while lower platelet counts (above 17.5 x10\u003csup\u003e3\u003c/sup\u003e /\u0026micro;L) may be tolerated in patients with hematological diseases. In addition to certain cut-off levels for platelet counts, the accumulative platelet deficit over a given time period was found to be more reliable in predicting PH in patients with sepsis, medication-related, or other causes of thrombocytopenia. Although these groups of patients did not have thrombocytopenia as profound as in those with hematological disorders, they are more susceptible to developing PH in prolonged thrombocytopenia. Therefore, regular prophylactic platelet transfusion to maintain platelet levels above certain thresholds over unstable periods may be a potential strategy to prevent PH in this group of patients.\u003c/p\u003e \u003cp\u003eThe present study used the largest database evaluating PH in patients with SM respiratory infections and is also the first study to extrapolate serial platelet measurements in predicting PH. Data in the present study provide clinicians with the optimal cutoff platelet level for transfusion therapy to prevent PH in thrombocytopenia of various causes. The concept of using d-index as a personalized measurement in evaluating the severity of thrombocytopenia can be implemented to prevent SM hemorrhagic pneumonia and bleeding disorders in various other diseases. Especially in the era of the COVID-19 pandemic, clinicians may also utilize the d-index to assess the risk of PH in sepsis due to COVID-19.\u003c/p\u003e \u003cp\u003eRegardless of the above strengths, the present study has several limitations. First is that we did not evaluate associations between PH, antibiotic use and corresponding antimicrobial susceptibility. Although in both clinical and animal studies, timely appropriate antibiotic use could reduce the risk of mortality in SM hemorrhagic pneumonia, systematic review demonstrated that even patients treated with appropriate antibiotics, including trimethoprim/sulfamethoxazole, fluoroquinolones, or both combined, the mortality remained high, even reaching 100% [11, 15]. Also, no prior antimicrobial therapy for SM bacteremia had shown a preventive effect for PH [7]. Still, prompt administration of antibiotics is essential for control of infectious disease, but the use of antibiotics in preventing PH in SM respiratory infection does not appear to be an adequate measure.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eProlonged and extreme thrombocytopenia is a determinant risk factor for PH in patients with SM respiratory infections. The degree of platelet deficit varies significantly between different causes of thrombocytopenia and types of underlying comorbidities. Single time-point measurement of platelet counts may most reliably predict PH in patients with hematological and liver diseases, while serial measurement over a given time period may reliably predict PH in those with sepsis and other causes of thrombocytopenia.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAPTT/MNAPTT, activated partial thromboplastin time/mean normal activated partial thromboplastin time; CRP, C-reactive protein; NFGNB, non-fermenting gram-negative bacillus; VAP, ventilator associated pneumonia; HCT, hemopoietic cell transplant; PCT, procalcitonin; PT/INR, prothrombin time and international normalized ratio; PH, Pulmonary hemorrhage; SM, Stenotrophomonas maltophilia; ROC, receiver operating characteristic; AUC, area under curve.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank Chief, Shih Min Wang, in the Department of Pediatrics giving his full support to this study, and Ms Shih-Wei Wang, Ms Hui-Feng Lee for the assistance of data collection. Special thanks to George Kuo from Chang-Geng Medical Foundation, Linkou Chang-Geng Memorial Hospital for his advice on statistical analyses.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis work was supported by grants from the Clinical Medical Research Center, National Cheng Kung University Hospital, Taiwan (NCKUH-11002017) and Ministry of Science and Technology, Taiwan (110-2923-B-006-001-MY4).\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eDatasets used and analyzed during the present study are available the Corresponding Author upon reasonable request.\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThe Institutional Review Board of National Cheng Kung University Hospital reviewed and approved the study protocol (IRB no. A-ER-110-079). The study was performed in accordance with the Declaration of Helsinki. Owing to the study\u0026apos;s retrospective nature, signed informed consent from patients was waived.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eAuthors\u0026rsquo; contributions\u003c/p\u003e\n\u003cp\u003eHCGW and CFS conceived the original study. CFS oversaw data collection. HCGW acquired all data. HSW wrote the d-index algorithm. Statistical analysis was overseen by CIL and CFS. HCGW analyzed the data, wrote the original manuscript, and prepared the final figures. CNC, CHC, and TSC had provided some insights regarding clinical association. CFS oversaw the analysis, writings, and figures. All authors have seen and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003eAuthors\u0026rsquo; information\u003c/p\u003e\n\u003cp\u003eCorresponding author: Ching-Fen Shen, MD, MSc. Address: Department of Pediatrics, National Cheng Kung University Hospital. No.138, Sheng-Li Road, North District, Tainan City, 704, Taiwan. E-mail: [email protected]; Tel.: +886-6-2353535*4184; Fax: +886-6-275308.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAuthor details\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u0026nbsp;\u003c/sup\u003eDepartment of Internal medicine, Chang Gung Memorial Hospital, Taoyuan, Taiwan. \u003csup\u003e2\u003c/sup\u003e Education Center, National Cheng Kung University Hospital, Tainan, Taiwan. \u003csup\u003e3\u003c/sup\u003e Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan. \u0026nbsp;\u003csup\u003e4\u003c/sup\u003e Department of Pediatrics, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan. \u003csup\u003e5\u003c/sup\u003e Department of Internal Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan. \u003csup\u003e6\u003c/sup\u003e Department of Statistics, College of Management, National Cheng Kung University, Tainan, Taiwan.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003e\u003cspan\u003eIbn Saied, W., et al., Ventilator-associated pneumonia due to Stenotrophomonas maltophilia: Risk factors and outcome. J Infect, 2020. 80(3): p. 279\u0026ndash;285.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eWindhorst, S., et al., The major extracellular protease of the nosocomial pathogen Stenotrophomonas maltophilia: characterization of the protein and molecular cloning of the gene. J Biol Chem, 2002. 277(13): p. 11042-9.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eGuzoglu, N., F.N. Demirkol, and D. Aliefendioglu, Haemorrhagic pneumonia caused by Stenotrophomonas maltophilia in two newborns. J Infect Dev Ctries, 2015. 9(5): p. 533-5.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eTrifonova, A. and T. Strateva, Stenotrophomonas maltophilia - a low-grade pathogen with numerous virulence factors. Infect Dis (Lond), 2019. 51(3): p. 168\u0026ndash;178.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eGutierrez, C., et al., Fatal hemorrhagic pneumonia: Don\u0026apos;t forget Stenotrophomonas maltophilia. Respir Med Case Rep, 2016. 19: p. 12\u0026thinsp;\u0026minus;\u0026thinsp;4.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eImoto, W., et al., Clinical Characteristics of Rapidly Progressive Fatal Hemorrhagic Pneumonia Caused by Stenotrophomonas maltophilia. Intern Med, 2020. 59(2): p. 193\u0026ndash;198.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eZhu, L., et al., Fatal hemorrhagic pneumonia in patients with hematologic diseases and Stenotrophomonas maltophilia bacteremia: a retrospective study. BMC Infect Dis, 2021. 21(1): p. 723.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eTada, K., et al., Stenotrophomonas maltophilia infection in hematopoietic SCT recipients: high mortality due to pulmonary hemorrhage. Bone Marrow Transplant, 2013. 48(1): p. 74\u0026thinsp;\u0026minus;\u0026thinsp;9.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eMori, M., et al., Life-threatening hemorrhagic pneumonia caused by Stenotrophomonas maltophilia in the treatment of hematologic diseases. Ann Hematol, 2014. 93(6): p. 901\u0026thinsp;\u0026minus;\u0026thinsp;11.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eAraoka, H., et al., Rapidly progressive fatal hemorrhagic pneumonia caused by Stenotrophomonas maltophilia in hematologic malignancy. Transpl Infect Dis, 2012. 14(4): p. 355\u0026thinsp;\u0026minus;\u0026thinsp;63.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eKim, S.H., et al., Pathogenic significance of hemorrhagic pneumonia in hematologic malignancy patients with Stenotrophomonas maltophilia bacteremia: clinical and microbiological analysis. Eur J Clin Microbiol Infect Dis, 2019. 38(2): p. 285\u0026ndash;295.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003ePortugal, R.D., M. Garnica, and M. Nucci, Index to predict invasive mold infection in high-risk neutropenic patients based on the area over the neutrophil curve. J Clin Oncol, 2009. 27(23): p. 3849-54.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eYilmaz, G., et al., D-index: A New Scoring System in Febrile Neutropenic Patients for Predicting Invasive Fungal Infections. Turk J Haematol, 2016. 33(2): p. 102-6.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eKimura, S., et al., Retrospective evaluation of the area over the neutrophil curve index to predict early infection in hematopoietic stem cell transplantation recipients. Biol Blood Marrow Transplant, 2010. 16(10): p. 1355-61.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003ePenagos, S.C., et al., First report of survival in two patients with hematologic malignancy and Stenotrophomonas maltophilia hemorrhagic pneumonia treated with trimethoprim-sulfamethoxazole-based combination antibiotic therapy. J Infect Chemother, 2020. 26(4): p. 397\u0026ndash;399.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eScholte, J.B., et al., Stenotrophomonas maltophilia ventilator-associated pneumonia. A retrospective matched case-control study. Infect Dis (Lond), 2016. 48(10): p. 738\u0026thinsp;\u0026minus;\u0026thinsp;43.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eNishiura, N., et al., Reevaluation of platelet function in chronic immune thrombocytopenia: impacts of platelet size, platelet-associated anti-alphaIIbbeta3 antibodies and thrombopoietin receptor agonists. Br J Haematol, 2020. 189(4): p. 760\u0026ndash;771.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eJust Vinholt, P., et al., Platelet function tests predict bleeding in patients with acute myeloid leukemia and thrombocytopenia. Am J Hematol, 2019. 94(8): p. 891\u0026ndash;901.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eVinholt, P.J., The role of platelets in bleeding in patients with thrombocytopenia and hematological disease. Clin Chem Lab Med, 2019. 57(12): p. 1808\u0026ndash;1817.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003ePeck-Radosavljevic, M., Thrombocytopenia in chronic liver disease. Liver Int, 2017. 37(6): p. 778\u0026ndash;793.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eRadchenko, C., A.H. Alraiyes, and S. Shojaee, A systematic approach to the management of massive hemoptysis. J Thorac Dis, 2017. 9(Suppl 10): p. S1069-S1086.\u003c/span\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Stenotrophomonas maltophilia, hemorrhagic pneumonia, pulmonary hemorrhage, platelet d-index, thrombocytopenia","lastPublishedDoi":"10.21203/rs.3.rs-1360630/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1360630/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Thrombocytopenic patients who acquire \u003cem\u003eStenotrophomonas maltophilia\u003c/em\u003e (SM) respiratory infection often develop pulmonary hemorrhage (PH), resulting in a high respiratory failure rate and increased mortality. This study aimed to evaluate risk factors for PH and develop an index measuring serial platelet deficit to predict PH in patients with SM respiratory infection.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Data of patients with both SM isolated from sputum/endotracheal suction culture and thrombocytopenia (platelet count \u0026lt; 150x10\u003csup\u003e3\u003c/sup\u003e /μL) who were treated at National Cheng Kung University Hospital during 2018-2020 were extracted from electronic medical records and analyzed retrospectively. SM respiratory infection was defined as positive bacterial isolates plus respiratory infection symptoms. Clinical parameters and laboratory findings were compared between PH and non-PH groups. The platelet dissimilarity index (d-index) was calculated by accumulating differences between the actual and the lowest normal level of platelet count in each patient at different time points.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Among 437 SM respiratory infection cases, 125 (28.6%) patients developed PH. Patients with PH had increased prothrombin time/international normalized ratio (PT/INR), lower platelet count, and higher platelet d-index. Multivariate analysis revealed that extreme thrombocytopenia (platelet count \u0026lt; 50x103 /μL) is a common independent risk factor for PH and mortality. The performance of platelet deficit and d-index varied between patients with different comorbidities. Performance of single time-point platelet deficit to predict PH is more reliable in patients with hematology/oncology and liver disease (area under curve 0.705-0.757), while performance of d-index is more reliable in patients with sepsis/treatment and various other groups (0.711-0.816).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e Prolonged and extreme thrombocytopenia is a determinant risk factor for PH in patients with SM respiratory infection. Given the complexity of causes of thrombocytopenia and associated comorbidities, different strategies should be applied to assess the degree of thrombocytopenia when\u0026nbsp;evaluating the risk for PH.\u003c/p\u003e","manuscriptTitle":"Serial Platelet Level Index Improves Prediction of Pulmonary Hemorrhage in Stenotrophomonas maltophilia Respiratory Infections","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-02-17 21:36:59","doi":"10.21203/rs.3.rs-1360630/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"279fd7c3-c5f1-48f6-baac-9ff1941f2356","owner":[],"postedDate":"February 17th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2022-03-07T17:14:21+00:00","versionOfRecord":[],"versionCreatedAt":"2022-02-17 21:36:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1360630","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1360630","identity":"rs-1360630","version":["v1"]},"buildId":"J0_U0BvcaRcwD8yVFaRlm","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}