scholarly journals Establishment of Routine Clinical Indicators-Based Nomograms for Predicting the Mortality in Patients with COVID-19

2020 ◽  
Author(s):  
Jialin He ◽  
Caiping Song ◽  
En Liu ◽  
Xi Liu ◽  
Hao Wu ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Clinical Manifestations ◽  
Vital Signs ◽  
Multivariate Logistic Regression Analysis ◽  
Hospital Death ◽  
Multivariate Logistic Regression ◽  
Clinical Indicators ◽  
Risk Of Death ◽  
Laboratory Test Results ◽  
Better Than

Abstract Background: The aim of the study was to establish and validate nomograms to predict the mortality risk of patients with COVID-19 using routine clinical indicators. Method: This retrospective study included a development cohort enrolled 2119 hospitalized COVID-19 patients and a validation cohort included 1504 COVID-19 patients. The demographics, clinical manifestations, vital signs and laboratory test results of the patients at admission and outcome of in-hospital death were recorded. The independent factors associated with death were identified by a forward stepwise multivariate logistic regression analysis and used to construct two prognostic nomograms. The models were then tested in an external dataset. Results: Nomogram 1 is a full model included nine factors identified in the multivariate logistic regression and nomogram 2 is built by selecting four factors from nine to perform as a reduced model. Nomogram 1 and nomogram 2 established showed better performance in discrimination and calibration than the MuLBSTA score in training. In validation, Nomogram 1 performed better than nomogram 2 for calibration. Conclusion: Nomograms we established performed better than the MuLBSTA score. We recommend the application of nomogram 1 in general hospital which provide robust prognostic performance but more cumbersome; nomogram 2 in mobile cabin hospitals which depend on less laboratory examinations and more convenient. Both nomograms can help clinicians in identifying patients at risk of death with routine clinical indicators at admission, which may reduce the overall mortality of COVID-19.

scholarly journals Establishment of Routine Clinical Indicators-Based Nomograms for Predicting the Mortality in Patients With COVID-19

2021 ◽  
Vol 8 ◽  
Author(s):  
Jialin He ◽  
Caiping Song ◽  
En Liu ◽  
Xi Liu ◽  
Hao Wu ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Clinical Manifestations ◽  
Vital Signs ◽  
Multivariate Logistic Regression Analysis ◽  
Smoking History ◽  
Hospital Death ◽  
Multivariate Logistic Regression ◽  
Clinical Indicators ◽  
Risk Of Death ◽  
Patients At Risk

This study aimed to establish and validate the nomograms to predict the mortality risk of patients with coronavirus disease 2019 (COVID-19) using routine clinical indicators. This retrospective study included a development cohort enrolled 2,119 hospitalized patients with COVID-19 and a validation cohort included 1,504 patients with COVID-19. The demographics, clinical manifestations, vital signs, and laboratory tests of the patients at admission and outcome of in-hospital death were recorded. The independent factors associated with death were identified by a forward stepwise multivariate logistic regression analysis and used to construct the two prognostic nomograms. The nomogram 1 was a full model to include nine factors identified in the multivariate logistic regression and nomogram 2 was built by selecting four factors from nine to perform as a reduced model. The nomogram 1 and nomogram 2 showed better performance in discrimination and calibration than the Multilobular infiltration, hypo-Lymphocytosis, Bacterial coinfection, Smoking history, hyper-Tension and Age (MuLBSTA) score in training. In validation, nomogram 1 performed better than nomogram 2 for calibration. We recommend the application of nomogram 1 in general hospitals which provide robust prognostic performance though more cumbersome; nomogram 2 in the out-patient, emergency department, and mobile cabin hospitals, which depend on less laboratory examinations to make the assessment more convenient. Both the nomograms can help the clinicians to identify the patients at risk of death with routine clinical indicators at admission, which may reduce the overall mortality of COVID-19.

scholarly journals Predictors of mortality for patients with COVID-19 pneumonia caused by SARS-CoV-2: a prospective cohort study

2020 ◽  
Vol 55 (5) ◽  
pp. 2000524 ◽  
Author(s):  
Rong-Hui Du ◽  
Li-Rong Liang ◽  
Cheng-Qing Yang ◽  
Wen Wang ◽  
Tan-Ze Cao ◽  
...  
Keyword(s):  
T Cells ◽  
Logistic Regression ◽  
Cardiac Troponin ◽  
Troponin I ◽  
Multivariate Logistic Regression Analysis ◽  
Cerebrovascular Diseases ◽  
Cardiac Troponin I ◽  
Multivariate Logistic Regression ◽  
Risk Of Death ◽  
Novel Coronavirus

The aim of this study was to identify factors associated with the death of patients with COVID-19 pneumonia caused by the novel coronavirus SARS-CoV-2.All clinical and laboratory parameters were collected prospectively from a cohort of patients with COVID-19 pneumonia who were hospitalised to Wuhan Pulmonary Hospital (Wuhan City, Hubei Province, China) between 25 December 2019 and 7 February 2020. Univariate and multivariate logistic regression was performed to investigate the relationship between each variable and the risk of death of COVID-19 pneumonia patients.In total, 179 patients with COVID-19 pneumonia (97 male and 82 female) were included in the present prospective study, of whom 21 died. Univariate and multivariate logistic regression analysis revealed that age ≥65 years (OR 3.765, 95% CI 1.146‒17.394; p=0.023), pre-existing concurrent cardiovascular or cerebrovascular diseases (OR 2.464, 95% CI 0.755‒8.044; p=0.007), CD3+CD8+ T-cells ≤75 cells·μL−1 (OR 3.982, 95% CI 1.132‒14.006; p<0.001) and cardiac troponin I ≥0.05 ng·mL−1 (OR 4.077, 95% CI 1.166‒14.253; p<0.001) were associated with an increase in risk of mortality from COVID-19 pneumonia. In a sex-, age- and comorbid illness-matched case–control study, CD3+CD8+ T-cells ≤75 cells·μL−1 and cardiac troponin I ≥0.05 ng·mL−1 remained as predictors for high mortality from COVID-19 pneumonia.We identified four risk factors: age ≥65 years, pre-existing concurrent cardiovascular or cerebrovascular diseases, CD3+CD8+ T-cells ≤75 cells·μL−1 and cardiac troponin I ≥0.05 ng·mL−1. The latter two factors, especially, were predictors for mortality of COVID-19 pneumonia patients.

Prognostic factors, symptoms, and consequences of electrolyte imbalances in patients who suffered from cancer.

2017 ◽  
Vol 35 (31_suppl) ◽  
pp. 74-74
Author(s):  
Pawel Bryniarski
Keyword(s):  
Emergency Department ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Cancer Patients ◽  
Logistic Regression Analysis ◽  
Multivariate Logistic Regression Analysis ◽  
Terminal Cancer ◽  
Multivariate Logistic Regression ◽  
Risk Of Death ◽  
Ps Scale

74 Background: Dyselectrolytemia is a common problem in patients with terminal cancer. It worsens the quality of life and increases the amount of complications. The aim of our study was to determine factors connected with dyselectrolytemia in patients with terminal cancer. Methods: 310 terminal cancer patients admitted to Palliative Care Unit were retrospectively analyzed. Detailed physical examination, medical history and laboratory parameters were taken upon admission. Univariate and multivariate logistic regression analysis were used to determine possible predictors, symptoms and consequences of dyselectrolytemia. Results: On admission 67,74% of patients had dyselectrolytemia. They were more frequently admitted to hospital from Emergency Department (OR=Odds Ratio=2,879, p=probability value=0,00004), had higher PS scale note (OR=1,627, p=0,0001), were more often cachectic (OR=1,915, p=0,0083), had more often constipation (OR=1,728,p=0,0275), were more often dehydrated (OR=2,609 ,p=0,0007), had lower albumin level (OR=0,909, p=0,00001). They had 275% higher risk of death (OR=2,758, p=0,0001). Multivariate logistic regression analysis after adjustment for possible confounders reviled that admission to hospital from Emergency Department (OR=2,652, p=0,01), higher PS scale note (OR=1,445, p=0,001), opioids administration (OR=2,747, p=0,003), dehydration (OR=1,966 , p=0,038) and higher risk of death (OR=2,432, p=0,002) remained independently associated with dyselectrolytemia. Conclusions: Higher PS scale note, occurrence of dehydration, admission to hospital from Emergency Department and opioids administration are factors associated with dyselectrolytemia. Patients with electrolytes imbalances had 275% higher risk of death. Project "Extension of life and improvement of its quality and reduction of cancer patients' mortality due to proper control of water and electrolyte management and elimination of risk factors for dehydration and dyselectrolytemia." Co-financed by the European Social Fund under the project of the Ministry of Science and Higher Education of Poland entitled "Best of the best! 2.0 ".

Factors associated with lack of proper hydration in terminal cancer patients.

2017 ◽  
Vol 35 (31_suppl) ◽  
pp. 195-195
Author(s):  
Pawel Bryniarski
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Cancer Patients ◽  
Multivariate Logistic Regression Analysis ◽  
Nausea And Vomiting ◽  
Terminal Cancer ◽  
Multivariate Logistic Regression ◽  
Factors Associated ◽  
Risk Of Death ◽  
Terminal Cancer Patients

195 Background: Dehydration is a frequent problem in patients suffered from terminal cancer. It decreases the quality of life and increases the amount of complications. The aim of our study was to determine factors connected with dehydration in patients with terminal cancer. Methods: 310 terminal cancer patients admitted to Palliative Care Unit were retrospectively analyzed. Detailed physical examination, medical history including history taken from family and care givers was taken upon admission. Laboratory parameters including morphology, concentration of sodium, potassium, total and ionized calcium, LDH were taken on admission. Univariate and multivariate logistic regression analysis were used to determine possible predictors, symptoms and consequences of dehydration. Results: On admission 34,51% of patients were dehydrated. They had more frequently: metastases (OR = Odds Ratio = 2,77, p = probability value = 0,019), nausea and vomiting (OR = 2,234,p = 0,0176), dyselectrolytemia (OR = 2,609, p = 0,0007); had higher PS scale note (OR = 1,458, p = 0,0031); were more often cachectic (OR = 2,482, p = 0,0003); had lower albumin level (OR = 0,931 ,p = 0,0008). They had 235% higher risk of death (OR = 2,356, p = 0,0007). Multivariate logistic regression analysis after adjustment for possible confounders reviled that occurrence of: metastases (OR = 2,665, p = 0,045), cachexia (OR = 2,105; p = 0,01) and nausea and vomiting (OR = 2,727, p = 0,026) remained independently associated with dyselectrolytemia. Conclusions: Occurrence of metastases, occurrence of nausea and vomiting and occurrence of cachexia are factors associated with dehydration. Patients with lack of proper hydration had 235% higher risk of death. Project "Extension of life and improvement of its quality and reduction of cancer patients' mortality due to proper control of water and electrolytes management and elimination of risk factors for dehydration and dyselectrolytemia" co-financed by the European Social Fund under the project of the Ministry of Science and Higher Education of Poland entitled "Best of the best! 2.0".

scholarly journals Comparison of the Clinical Implications among Two Different Nutritional Indices in Hospitalized Patients with COVID-19

2020 ◽  
Author(s):  
Xuebei Du ◽  
Yuwei Liu ◽  
Jing Chen ◽  
Li Peng ◽  
Yalei Jin ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Odds Ratio ◽  
Multivariate Logistic Regression Analysis ◽  
Hospital Death ◽  
Nutritional Indices ◽  
Multivariate Logistic Regression ◽  
Severe Group ◽  
Conut Score

SummaryBackgroundCoronavirus disease 2019 (COVID-19) is an emerging infectious disease.It was first reported in Wuhan, China, and then broke out on a large scale around the world.This study aimed to assess the clinical significance of two different nutritional indices in 245 patients with COVID-19.MethodsIn this retrospective single-center study, we finally included 245 consecutive patients who confirmed COVID-19 in Wuhan University Zhongnan Hospital from January 1 to February 29. Cases were classified as either discharged or dead. Demographic, clinical and laboratory datas were registered, two different nutritional indices were calculated: (i)the Controlling nutritional status (CONUT) score; (ii) prognostic nutritional index (PNI). We used univariate and multivariate logistic regression analysis to explore the relationship between nutritional indices and hospital death.Results212 of them were discharged and 33 of them died. In-hospital mortality was signifcantly higher in the severe group of PNI than in the moderate and normal groups. It was also significantly worse in the severe-CONUT group than in the moderate-, mild-, and normal-CONUT groups. Multivariate logistic regression analysis showed the CONUT score (odds ratio3.371,95%CI (1.124–10.106), p = 0.030) and PNI(odds ratio 0.721,95% CI (0.581–0.896), P=0.003) were independent predictors of all-cause death at an early stage; Multivariate logistic regression analysis also showed that the severe group of PNI was the independent risk predictor of in-hospital death(odds ratio 24.225, 95% CI(2.147–273.327), p=0.010).The CONUT score cutoff value was 5.5 (56.00 and 80.81%; AUC 0.753; 95% CI (0.644–0.862); respectively). The PNI cutoff value was 40.58 (81.80 and 66.20%; AUC 0.778; 95% CI (0.686–0.809); respectively). We use PNI and the COUNT score to assess malnutrition, which can have a prognosis effect of COVID-19patients.ConclusionThe CONUT score and PNI could be a reliable prognostic marker of all-cause deathin patients with COVID-19.

Epidemiology of pediatric hydrocephalus in Haiti: analysis of a surgical case series

2019 ◽  
Vol 23 (5) ◽  
pp. 568-576
Author(s):  
Michael Ragheb ◽  
Ashish H. Shah ◽  
Sarah Jernigan ◽  
Tulay Koru-Sengul ◽  
John Ragheb
Keyword(s):  
Public Health ◽  
Logistic Regression ◽  
Head Circumference ◽  
Rainy Season ◽  
Statistical Tests ◽  
Multivariate Logistic Regression Analysis ◽  
Case Series ◽  
Multivariate Logistic Regression ◽  
Surgical Case ◽  
Operative Notes

OBJECTIVEHydrocephalus is recognized as a common disabling pediatric disease afflicting infants and children disproportionately in the developing world, where access to neurosurgical care is limited and risk of perinatal infection is high. This surgical case series describes the Project Medishare Hydrocephalus Specialty Surgery (PMHSS) program experience treating hydrocephalus in Haiti between 2008 and 2015.METHODSThe authors conducted a retrospective review of all cases involving children treated for hydrocephalus within the PMHSS program in Port-au-Prince, Haiti, from 2008 through 2015. All relevant epidemiological information of children treated were prospectively collected including relevant demographics, birth history, hydrocephalus etiology, head circumference, and operative notes. All appropriate associations and statistical tests were performed using univariate and multivariate logistic regression analyses.RESULTSAmong the 401 children treated within PMHSS, postinfectious hydrocephalus (PIH) accounted for 39.4% (n = 158) of cases based on clinical, radiographic, and endoscopic findings. The majority of children with hydrocephalus in Haiti were male (54.8%, n = 197), born in the rainy season (59.7%, n = 233), and born in a coastal/inland location (43.3%, n = 61). The most common surgical intervention was endoscopic third ventriculostomy with choroid plexus cauterization (ETV/CPC) (45.7%, n = 175). Multivariate logistic regression analysis yielded coastal birth location (OR 3.76, 95% CI 1.16–12.18) as a statistically significant predictor of PIH. Increasing head circumference (adjusted OR 1.06, 95% CI 0.99–1.13) demonstrated a slight trend toward significance with the incidence of PIH.CONCLUSIONSThis information will provide the foundation for future clinical and public health studies to better understand hydrocephalus in Haiti. The 39.4% prevalence of PIH falls within observed rates in Africa as does the apparently higher prevalence for those born during the rainy season. Although PIH was the most frequent etiology seen in almost all birth locations, the potential relationship with geography noted in this series will be the focus of further research in an effort to understand the link between climate and PIH in Haiti. The ultimate goal will be to develop an appropriate public health strategy to reduce the burden of PIH on the children of Haiti.

High Risk of One-year Stroke Recurrence in Patients with Younger Age and Prior History of Ischemic Stroke

2019 ◽  
Vol 16 (3) ◽  
pp. 250-257 ◽  
Author(s):  
Jiann-Der Lee ◽  
Ya-Han Hu ◽  
Meng Lee ◽  
Yen-Chu Huang ◽  
Ya-Wen Kuo ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Ischemic Stroke ◽  
Multivariate Logistic Regression Analysis ◽  
Stroke Recurrence ◽  
Prior History ◽  
Multivariate Logistic Regression ◽  
Cart Analysis ◽  
Younger Age ◽  
History Of ◽  
One Year

Background and Purpose: Recurrent ischemic strokes increase the risk of disability and mortality. The role of conventional risk factors in recurrent strokes may change due to increased awareness of prevention strategies. The aim of this study was to explore the potential risk factors besides conventional ones which may help to affect the advances in future preventive concepts associated with one-year stroke recurrence (OSR). Methods: We analyzed 6,632 adult patients with ischemic stroke. Differences in clinical characteristics between patients with and without OSR were analyzed using multivariate logistic regression and classification and regression tree (CART) analyses. Results: Among the study population, 525 patients (7.9%) had OSR. Multivariate logistic regression analysis revealed that male sex (OR 1.243, 95% CI 1.025 – 1.506), age (OR 1.015, 95% CI 1.007 - 1.023), and a prior history of ischemic stroke (OR 1.331, 95% CI 1.096 – 1.615) were major factors associated with OSR. CART analysis further identified age and a prior history of ischemic stroke were important factors for OSR when classified the patients into three subgroups (with risks of OSR of 8.8%, 3.8%, and 12.5% for patients aged > 57.5 years, ≤ 57.5 years/with no prior history of ischemic stroke, and ≤ 57.5 years/with a prior history of ischemic stroke, respectively). Conclusions: Male sex, age, and a prior history of ischemic stroke could increase the risk of OSR by multivariate logistic regression analysis, and CART analysis further demonstrated that patients with a younger age (≤ 57.5 years) and a prior history of ischemic stroke had the highest risk of OSR.

scholarly journals Efficacy of flurbiprofen axetil for preventing postanesthetic shivering in patients undergoing gynecologic laparotomy surgeries

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Atsushi Kotera
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Postoperative Pain ◽  
Logistic Regression Analysis ◽  
Pain Control ◽  
Multivariate Logistic Regression Analysis ◽  
Multivariate Logistic Regression ◽  
Postoperative Pain Control ◽  
Flurbiprofen Axetil ◽  
Postanesthetic Shivering

Abstract Background Postanesthetic shivering is an unpleasant adverse event in surgical patients. A nonsteroidal anti-inflammatory drug has been reported to be useful in preventing postanesthetic shivering in several previous studies. The aim of this study was to evaluate the efficacy of flurbiprofen axetil being a prodrug of a nonsteroidal anti-inflammatory drug for preventing postanesthetic shivering in patients undergoing gynecologic laparotomy surgeries. Method This study is a retrospective observational study. I collected data from patients undergoing gynecologic laparotomy surgeries performed between October 1, 2019, and September 30, 2020, at Kumamoto City Hospital. All the patients were managed with general anesthesia with or without epidural analgesia. The administration of intravenous 50 mg flurbiprofen axetil for postoperative pain control at the end of the surgery was left to the individual anesthesiologist. The patients were divided into two groups: those who had received intravenous flurbiprofen axetil (flurbiprofen group) and those who had not received intravenous flurbiprofen axetil (non-flurbiprofen group), and I compared the frequency of postanesthetic shivering between the two groups. Additionally, the factors presumably associated with postanesthetic shivering were collected from the medical charts. Intergroup differences were assessed with the χ2 test with Yates’ correlation for continuity category variables. The Student’s t test was used to test for differences in continuous variables. Furthermore, a multivariate logistic regression analysis was performed to elucidate the relationship between the administration of flurbiprofen axetil and the incidence of PAS. Results I retrospectively examined the cases of 141 patients aged 49 ± 13 (range 21-84) years old. The overall postanesthetic shivering rate was 21.3% (30 of the 141 patients). The frequency of postanesthetic shivering in the flurbiprofen group (n = 31) was 6.5%, which was significantly lower than that in the non-flurbiprofen group (n = 110), 25.5% (p value = 0.022). A multivariate logistic regression analysis showed that administration of flurbiprofen axetil was independently associated with a reduced incidence of postanesthetic shivering (odds ratio 0.12; 95% confidence interval, 0.02-0.66, p value = 0.015). Conclusions My result suggests that intraoperative 50 mg flurbiprofen axetil administration for postoperative pain control is useful to prevent postanesthetic shivering in patients undergoing gynecologic laparotomy surgeries.

scholarly journals The association between hypoglycemia and glycemic variability in elderly patients with type 2 diabetes: a prospective observational study

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Takahisa Handa ◽  
Akinobu Nakamura ◽  
Aika Miya ◽  
Hiroshi Nomoto ◽  
Hiraku Kameda ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Observational Study ◽  
Elderly Patients ◽  
Prospective Observational Study ◽  
Multivariate Logistic Regression Analysis ◽  
Glycemic Variability ◽  
Multivariate Logistic Regression

Abstract Background This study aimed to explore predictive factors of time below target glucose range (TBR) ≥ 1% among patients’ characteristics and glycemic variability (GV) indices using continuous glucose monitoring data in elderly patients with type 2 diabetes. Methods We conducted a prospective observational study on 179 (71 female) Japanese outpatients with type 2 diabetes aged ≥ 65 years. The characteristics of the participants with TBR ≥ 1% were evaluated by multivariate logistic regression analysis. Receiver-operating characteristic (ROC) curve analyses of GV indices, comprising coefficient of variation (CV), standard deviation, and mean amplitude of glycemic excursions, were performed to identify the optimal index for the identification of patients with TBR ≥ 1%. Results In the multivariate logistic regression analysis, none of the clinical characteristics, including HbA1c and C-peptide index, were independent markers for TBR ≥ 1%, while all three GV indices showed significant associations with TBR ≥ 1%. Among the three GV indices, CV showed the best performance based on the area under the curve in the ROC curve analyses. Conclusions Among elderly patients with type 2 diabetes, CV reflected TBR ≥ 1% most appropriately among the GV indices examined. Trial registration UMIN-CTR: UMIN000029993. Registered 16 November 2017

scholarly journals Risk factors for tissue expander infection in scar reconstruction: a retrospective cohort study of 2374 consecutive cases

2020 ◽  
Vol 8 ◽  
Author(s):  
Chen Dong ◽  
Minhui Zhu ◽  
Luguang Huang ◽  
Wei Liu ◽  
Hengxin Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Treatment Failure ◽  
Logistic Regression Analysis ◽  
Disease Duration ◽  
Multivariate Logistic Regression Analysis ◽  
Tissue Expansion ◽  
Multivariate Logistic Regression ◽  
Hematoma Evacuation

Abstract Background Tissue expansion is used for scar reconstruction owing to its excellent clinical outcomes; however, the complications that emerge from tissue expansion hinder repair. Infection is considered a major complication of tissue expansion. This study aimed to analyze the perioperative risk factors for expander infection. Methods A large, retrospective, single-institution observational study was carried out over a 10-year period. The study enrolled consecutive patients who had undergone tissue expansion for scar reconstruction. Demographics, etiological data, expander-related characteristics and postoperative infection were assessed. Univariate and multivariate logistic regression analysis were performed to identify risk factors for expander infection. In addition, we conducted a sensitivity analysis for treatment failure caused by infection as an outcome. Results A total of 2374 expanders and 148 cases of expander infection were assessed. Treatment failure caused by infection occurred in 14 expanders. Multivariate logistic regression analysis identified that disease duration of ≤1 year (odds ratio (OR), 2.07; p &lt; 0.001), larger volume of expander (200–400 ml vs &lt;200 ml; OR, 1.74; p = 0.032; &gt;400 ml vs &lt;200 ml; OR, 1.76; p = 0.049), limb location (OR, 2.22; p = 0.023) and hematoma evacuation (OR, 2.17; p = 0.049) were associated with a high likelihood of expander infection. Disease duration of ≤1 year (OR, 3.88; p = 0.015) and hematoma evacuation (OR, 10.35; p = 0.001) were so related to high risk of treatment failure. Conclusions The rate of expander infection in patients undergoing scar reconstruction was 6.2%. Disease duration of &lt;1 year, expander volume of &gt;200 ml, limb location and postoperative hematoma evacuation were independent risk factors for expander infection.

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