We aimed to develop and validate a predictive model to evaluate in-hospital mortality risk in HIV/AIDS patients with PCP in China. 1001 HIV/AIDS patients with PCP admitted in the Beijing Ditan hospital from August 2009 to January 2018 were included in this study. Multivariate Cox proportional hazard model was used to identify independent risk factors of death, and a predictive model was devised based on risk factors. The overall in-hospital mortality was 17.3%. The patients were randomly assigned into derivation cohort (801cases) and validation cohort (200 cases) in 8:2 ratio, respectively, in which in derivation cohort we found that 7 predictors, including LDH >350U/L, HR>130 times/min, room air PaO2 <70mmHg, later admission to ICU, Anemia (HGB≤90g/L), CD4<50cells/ul, and development of a pneumothorax, were associated with poor prognosis in HIV/AIDS patients with PCP and were included in the predictive model. The model had excellent discrimination with AUC of 0.904 and 0.921 in derivation and validation cohort, respectively. The predicted scores were divided into two groups to assess the in-hospital mortality risk: low-risk group (0-11 points with mortality with 2.15-12.77%) and high-risk group (12-21 points with mortality with 38.78%-81.63%). The cumulative mortality rate also indicated significant difference between two groups with Kaplan-Meier curve (
With the advent of era of antiretroviral therapy and widespread use of pneumocystis pneumonia (PCP) prophylaxis, the incidence of PCP has declined substantially in HIV/AIDS population. Buchacz et al. [
PCP was still a life-threatening opportunistic infection in HIV/AIDS patients with severe immunosuppression, which often needed mechanical ventilation, especially in patients with severe PCP. Although different guidelines [
Prior studies [
This retrospective study was carried out in Beijing Ditan Hospital, Capital Medical University, and the study protocol was approved by the research ethics committee of hospital, which complied with principles of Declaration of Helsinki. All of clinical and laboratory data were used anonymously and written informed consent was not required due to retrospective study using deidentified clinical information.
1025 AIDS patients with PCP who were admitted to Beijing Ditan Hospital, the national referral hospital for HIV/AIDS patients in China, were identified from August 2009 to January 2018 for retrospective analysis. Exclusion criteria were (1) aged < 18 years old; (2) overseas patients; (3) the patients who had baseline data missing (Figure
Flowchart of study population and random assignment with ratio of 8:2.
Diagnosis of PCP in HIV/AIDS patients was based on treatment guidelines of opportunistic infections (OIs) recommended by the National Institute of Health (NIH) of America [
Some other serum markers such as elevated (1,3)-ß-D-Glucan had a higher predictive value for diagnosis of PCP in HIV/AIDS patients [
90% of the patients were ARV-naïve, and these patients were not aware of HIV infection until OIs became the first indicator of their disease. HIV infection was diagnosed when these patients sought medical attention. They were referred from other hospitals to Ditan hospital, the national referral hospital for HIV/AIDS patients in China. Patients with compatible clinical symptoms after admission were required to receive laboratory tests and perform computerized tomography (CT) scan and bronchoalveolar lavage (BAL) as early as possible, the time interval between presentation to the hospital and the clinical diagnosis of PCP was 1-2 days based on results of laboratory tests and CT scan, and time interval for definite diagnosis was 5-7 days based on cytopathologic demonstration of pathogen in BALF samples.
Diagnosis of OIs in HIV/AIDS patients was based on treatment guidelines of OIs recommended by the US National Institute of Health (NIH) [
PCP treatment was based on guidelines of OIs recommended by NIH [
Highly active antiretroviral therapy (HAART) was recommended to HIV/AIDS patients with PCP based on National Free Antiretroviral Treatment Program (NFATP) in China [
The social-demographic data included gender, age, and status of marriage, while clinical data included HIV transmission routes, breath and heart rates, duration of receiving ART, delayed admission to intensive care units (ICU), coinfected OIs with PCP patients, and documented comorbidities and complications. Laboratory data included baseline hemoglobin (HGB), albumin (ALB), CD4 cell counts, lactate dehydrogenase (LDH), and room air partial pressure of oxygen (PaO2) levels.
The prognosis recorded either survival or death when patients were discharged from hospital.
Severe pneumonia represented severe opportunistic infections in respiratory system with severe acute respiratory failure and/or septic shock due to immunosuppression in HIV/AIDS patient [
Delayed admission-to-ICU meant a hospital-to-ICU interval was more than 24 hours [
All data were analyzed using SPSS 20.0(SPSS Institute, Chicago IL, USA). The study population was randomly assigned as derivation and validation cohort, and clinical data were evaluated with percentages and chi-square test or Fisher exact test was used for statistical comparisons of these categorical variables between two cohorts.
Radom sampling was conducted using R software (3.3.3 version). 80% patients in alive and dead groups were randomly selected separately with random sampling procedure and were combined with derivation cohort, while other 20% in two groups were combined with validation cohort. Algorithm of randomization for the derivation and validation cohort we used was widely used in development of predictive score models [
Cox proportional hazard models were used to evaluate the risk factors associated with mortality in HIV/AIDS patients with PCP in the derivation cohort. The integer scores were converted by rounding the hazard ratios (HRs) of the risk factors. For example, the HR of 1.860 associated with heart rate >130 times/min was equal to 2 points and the final score was the sum of these values. The prediction model was validated using the area under the receiver operating curve (ROC) curves in derivation and validation cohort. The maximum Youden index was determined based on ROC analysis. The correlation between prediction scoring model and mortality was plotted according to scores, and Kaplan-Meier survival curves were computed to compare difference in cumulative mortality between different groups.
In this study,
From August 2009 to January 2018, PCP was etiologically diagnosed in 1025 HIV/AIDS patients and 1001 patients were enrolled in this study based on exclusion criteria, in which 828 patients survived to discharge from hospital while 173 in-hospital death (17.3%) were found in the cohort. Random assignment in 8:2 ratio was conducted in survival group (663 &165 patients) and dead group (138 & 35 patients), respectively, to form derivation cohort (n=801) and validation cohort (n=200) in 8:2 ratio (Figure
Baseline characteristics of HIV/AIDS patient with PCP in the study cohort.
Variables | Total | Derivation cohort | Validation cohort | |
---|---|---|---|---|
| ||||
| 188 (18.8%) | 156 (19.5%) | 32 (16.0%) | 0.260 |
<50 | 813 (81.2%) | 645 (80.5%) | 168 (84.0%) | |
| ||||
Female | 77 (7.7%) | 61 (7.6%) | 16 (8.0%) | 0.855 |
Male | 924 (92.3%) | 740 (92.4%) | 184 (92.0%) | |
| ||||
Homosexual | 94 (9.4%) | 71 (8.9%) | 23 (11.5%) | 0.484 |
Heterosexual | 272 (27.2%) | 218 (27.2%) | 54 (27.0%) | |
Blood transfusion | 11 (1.1%) | 7 (0.9%) | 4 (2.0%) | |
Intravenous drug | 7 (0.7%) | 6 (0.7%) | 1 (0.5%) | |
Unknown | 617 (61.6%) | 499 (62.3%) | 118 (59.0%) | |
| ||||
Married | 542 (54.1%) | 439 (54.8%) | 103 (51.5%) | 0.401 |
Unmarried | 459 (45.9%) | 362 (45.3%) | 97 (48.5%) | |
| ||||
HGB (g/L) | ||||
Median (Q1, Q3) | 120 (107, 133) | 120 (107, 134) | 119.7(107.3, 131) | 0.403 |
>90g/L | 918 (91.7%) | 737 (92.0%) | 181 (90.5%) | 0.488 |
≦90g/L | 83 (8.3%) | 64 (8.0%) | 19 (9.5%) | |
ALB) (g/L) | ||||
Median (Q1, Q3 | 31.8(28.3, 34.8) | 31.7(28.3, 34.9) | 32.1(28.5, 34.6) | 0.539 |
>30g/L | 646 (64.5%) | 519 (64.8%) | 127 (63.5%) | 0.732 |
⩽30g/L | 355 (35.5%) | 282 (35.2%) | 73 (36.5%) | |
CD4 (cells/ul) | ||||
Median (Q1, Q3) | 21 (10, 47) | 35.2 (10, 46) | 41.6 (9, 53.8) | 0.082 |
>50cells/ul | 236 (23.6%) | 183 (22.8%) | 53 (26.5%) | 0.276 |
≦50cells/ul | 765 (76.4%) | 618 (77.2%) | 147 (73.5%) | |
LDH (IU/L) | ||||
Median (Q1, Q3) | 334.1(252.8, 456.5) | 336.8(251.4, 457.1) | 321.8(259.2, 449.2) | 0.198 |
| 456 (45.6%) | 372 (46.4%) | 84 (42.0%) | 0.259 |
<350 IU/L | 545 (54.4%) | 429 (53.6%) | 116 (58.0%) | |
Partial pressure of oxygen | ||||
>70mmHg | 541 (54.0%) | 434 (54.2%) | 107 (53.5%) | 0.863 |
⩽70mmHg | 460 (46.0%) | 367 (45.8%) | 93 (46.5%) | |
| ||||
Respiratory rate | ||||
| 142 (14.2%) | 115 (14.4%) | 27 (13.5%) | 0.756 |
<30 times/min | 859 (85.8%) | 686 (85.6%) | 173 (86.5%) | |
Heart rate | ||||
| 58 (5.8%) | 42 (5.2%) | 16 (8.0%) | 0.136 |
<130 times/min | 943 (94.2%) | 759 (94.8%) | 184 (92.0%) | |
| ||||
ART-naive | 898 (89.7%) | 720 (89.9%) | 178 (89.0%) | 0.618 |
<6 months | 86 (8.6%) | 69 (8.6%) | 17 (8.5%) | |
>6 months | 17 (1.7%) | 12 (1.5%) | 5 (2.5%) | |
| ||||
Yes | 183 (18.3%) | 147 (18.4%) | 36 (18.0%) | 0.908 |
NO | 818 (81.7%) | 654 (81.6%) | 164 (82.0%) | |
| ||||
Bacterial pneumonitis | ||||
Yes | 832 (83.1%) | 663 (82.8%) | 169 (84.5%) | 0.559 |
NO | 169 (16.9%) | 138 (17.2%) | 31 (15.5%) | |
CMV pneumonitis | ||||
Yes | 385 (38.5%) | 304 (38%) | 81 (40.5%) | 0.508 |
NO | 616 (61.5%) | 497 (62%) | 119 (59.5%) | |
Cryptococcal pneumonitis | ||||
Yes | 19 (1.9%) | 17 (2.1%) | 2 (1.0%) | 0.298 |
NO | 982 (98.1%) | 784 (97.9%) | 198 (99.0%) | |
Fungal pneumonia | ||||
Yes | 209 (20.9%) | 163 (20.3%) | 46 (23.0%) | 0.409 |
NO | 792 (79.1%) | 638 (79.7%) | 154 (77.0%) | |
Pulmonary tuberculosis | ||||
Yes | 148 (14.8%) | 110 (13.7%) | 38 (19.0%) | 0.060 |
NO | 853 (85.2%) | 691 (86.3%) | 162 (81.0%) | |
Severe pneumonia | ||||
Yes | 148 (14.8%) | 115 (14.4%) | 33 (16.5%) | 0.445 |
NO | 853 (85.2%) | 686 (85.6%) | 167 (83.5%) | |
Pneumothorax | ||||
Yes | 41 (4.0%) | 34 (4.2%) | 7 (3.5%) | 0.635 |
NO | 960 (96.0%) | 767 (95.8%) | 193 (96.5%) | |
CNS infection | ||||
Yes | 54 (5.4%) | 43 (5.4%) | 11 (5.5%) | 0.941 |
NO | 947 (94.6%) | 758 (94.6%) | 189 (94.5%) | |
Cardiovascular disease | ||||
Yes | 64 (6.4%) | 46 (5.7%) | 18 (9.0%) | 0.092 |
NO | 937 (93.6%) | 755 (94.3%) | 182 (91.0%) | |
Malignancies | ||||
Yes | 27 (2.7%) | 23 (2.9%) | 4 (2.0%) | 0.496 |
NO | 974 (97.3%) | 778 (97.1%) | 196 (98.0%) |
Univariate Cox proportional hazard models were used to find risk factors of mortality in HIV/AIDS patients with PCP in derivation cohort; the results indicated significant difference in following variables: age>50years, CD4<50cells/ul, HGB≤90g/L, LDH≤350U/L, hypoalbuminemia, room air PaO2 <70mmHg, breathing rate ≥30 times/min, heart rate ≥130 times/min, later admission to ICU, and some comorbidities, including bacterial pneumonia, CMV pneumonitis, fungal pneumonia, severe pneumonia, and pneumothorax. Multivariate Cox proportional hazard model using above variables indicated that CD4<50cells/ul (HR 1.844, 95%CI 1.022, 3.326, and p=0.042), HGB≤90g/L (HR 2.063, 95%CI 1.220, 3.490, and p=0.007), LDH≤350U/L (HR 2.128, 95%CI 1.382, 3.279, and p=0.001), room air PaO2 <70mmHg (HR 7.328, 95%CI 3.621,14.830, and p<0.001), heart rate ≥130 times/min (HR 1.860, 95%CI 1.131, 3.060, and p=0.015), later admission to ICU (HR 6.418, 95%CI 4.212,9.781, and p<0.001), and pneumothorax (HR 1.630, 95%CI 1.027,2.588, and p=0.038) were independent predictors of mortality in HIV/AIDS patients with PCP (see Table
Risk factors for mortality rate by Cox proportional hazard regression in HIV/AIDS patients with PCP and hazard rate and integer risk scores.
Unadjusted | | Adjusted | | Predictive Score | |
---|---|---|---|---|---|
CD4≤50cells/ul | 2.860(1.612,5.072) | <0.001 | 1.844(1.022,3.326) | 0.042 | 2 |
Anemia( HGB≤90g/L) | 1.861 (1.118, 3.100) | 0.017 | 2.063(1.220,3.490) | 0.007 | 2 |
LDH≥350 IU/L | 4.706(3.097,7.151) | <0.001 | 2.128(1.382,3.279) | 0.001 | 2 |
Heart rate≥130 times/min | 4.335(2.663,7.058) | <0.001 | 1.860(1.131,3.060) | 0.015 | 2 |
PaO2≤70mmHg | 19.193(9.748,37.789) | <0.001 | 7.328(3.621,14.830) | <0.001 | 7 |
Delayed admission to ICU | 16.610(11.310,24.394) | <0.001 | 6.418(4.212,9.781) | <0.001 | 6 |
Pneumothorax | 8.328 (5.397,12.850 ) | <0.001 | 1.630(1.027,2.588) | 0.038 | 2 |
| | ||||
Low risk 2.15-12.77% | 0-11 | ||||
High risk 38.78%-81.63% | 12-21 |
The total scores from above 7 risk factors in each patients in derivation cohort ranged from 0 to 21 (Table
Predictive scores were assigned to above 7 risk factors based on rounding the HRs (Table
The area under the ROC curves in the validation cohort was used to evaluate the potency of predictive model of mortality in HIV/AIDS patients with PCP, and results indicated that area under the ROC curves (AUC) was 0.921 (95% CI: 0.882–0.961) in validation cohort, and AUC was 0.904 (95% CI: 0.875–0.934) in derivation cohort, which was more than 0.7, suggesting the predictive model to be effective to predict in-hospital mortality in HIV/AIDS patients with PCP (Figure
The correlations between the predictive model and the in-hospital mortality in HIV/AIDS patients with PCP were further evaluated in this study, and results indicated that patients with higher scores showed poorer prognosis in our cohort. In-hospital mortality was 2.15% in patients with score of 0-6, 12.77% in patients with score of 7-11, 38.78% in patients with score of 12-15, and 81.63% in patients with score of 17-21, respectively (Figure
Percentage of mortality of HIV/AIDS patients with PCP according to the scores.
Kaplan-Meier survival curve of HIV/AIDS patients with PCP between groups of low-level and high-level scores.
TMP/SMX was the treatment of best choice for HIV/AIDS patients with PCP in China, recommended duration of therapy was 21 days, and PCP secondary prophylaxis was initiated immediately upon completion of therapy. HAART was recommended to HIV/AIDS patients with PCP once clinical symptoms were alleviated and temperature was normal. In this study, recurrent PCP was found in 20 patients based on second bronchoscopic detection and cytopathologic demonstration due to immune reconstitutional inflammatory syndromes after initiating antiretroviral therapy.
In this study, 173 patients were dead in the hospital. Figure
Trend of in-hospital mortality rates in study period.
In this study, 173 patients were dead in the hospital and the duration from admission to death was 14 days (6, 26.5) (mean value based on
The clinical management of AIDS-related opportunistic illnesses and ART for HIV infection had evolved significantly during study period. First, the time when to initiate ART was updated. Although antiretroviral regimens were freely provided to HIV/AIDS patients in China based on NFATP, the time when to initiate ART was updated from CD4 <200cells/ul to any CD4 cells levels, which reduced the incidence of OIs in China. Second, HIV testing and counseling were updated, which was changed from voluntary counseling and testing (VCT) to provider initiated testing and counseling (PITC) [
In this study, 90% of the patients were ART-naïve and HAART was recommended to HIV/AIDS patients with PCP as soon as possible once clinical symptoms were alleviated and temperature was normal based on National Free Antiretroviral Treatment Program (NFATP) in China [
In this retrospective study of 1001 HIV-infected patients diagnosed as PCP in China, we found overall in-hospital mortality was 17.3%. The high mortality indicated importance of rapidly identifying patients with higher risk of death and earlier providing clinical intervention. In this study, we developed a clinically predictive model to assess prognosis in HIV/AIDS patients with PCP in China. In a multivariate Cox proportional hazard model, we found 7 predictors including LDH >350U/L, HR>130 times/min, room air PaO2 <70mmHg, later admission to ICU, Anemia (HGB≤90g/L), CD4<50cells/ul, and development of a pneumothorax were associated with poor prognosis in HIV/AIDS patients with PCP. A clinically predictive model to assess mortality was then developed based on above 7 predictors, which demonstrated that 38.78-81.63% of patients died in higher risk group and 2.15-12.77% in lower risk group.
Several studies [
Despite China’s free ART program initiated in 2002 to save the lives and reduce the mortality of HIV/AIDS patients [
Chen et al. [
Prior studies [
Previous studies [
Anemia can result in abnormal physiological functions in ordinary population. It was also reported [
Serum LDH level was an unspecific marker for cell damage or death in path-physiological status, and in HIV/AIDS patients with PCP, elevated serum LDH level was associated with the degree of lung tissue damage [
It was reported that [
Development of pneumothorax was previously reported as a risk factor of mortality in HIV/AIDS patients with PCP [
In this study, we found some risk factors that were amenable to interventions to affect the prognosis, which can be treated as a simple tool for physicians to assess the prognosis in HIV/AIDS patients with PCP. Besides risk factors we found, some other modifiable factors may also affect the prognosis of HIV/AIDS patients with PCP. Sun et al
This predictive model had some strength. First, the clinical data collected were obtained from a large retrospective cohort over 9-year time period, which increased reliability of the conclusion. Second, the model was validated in a sizable validation cohort, which indicated high accuracy. Third, 7 predictors used in the model were routinely collected in clinical work, and simple calculation of scores was also conducive to implement clinical use of the model, which helped healthcare workers determine the prognosis and outcome of HIV/AIDS-associated PCP, especially in resource limited regions in China.
Besides these advantages, our study had some limitations. First, it was a retrospective study with inherent bias nature. Second, the study was conducted in a single center, and conclusion made in this study should be further validated in a prospective cohort. Third, the model was only used to evaluate the prognosis of patients who had confirmed diagnosis of PCP after admission; some patients who were too severe to confirm the diagnosis might be excluded in the study.
In conclusion, a predictive model to evaluate mortality in HIV/AIDS patients with PCP was constructed based on routine laboratory and clinical parameters, which may be a simple tool for physicians to assess the prognosis in HIV/AIDS patients with PCP in China.
Lamivudine
Albumin
Antiretroviral therapy
Area under the ROC curves
Bronchoalveolar lavage
Bronchoalveolar lavage fluid
Confidence Interval
Cytomegalovirus
Central nervous system
Computerized tomography
Efavirenz
Highly active antiretroviral therapy
Hemoglobin
Hazard ratios
Intensive care unit
Lactate dehydrogenase
Median based on 25th and 75th percentiles
National Free Antiretroviral Treatment Program
National Institute of Health
Opportunistic infection
Partial pressure of oxygen
Provider initiated testing and counseling
Pneumocystis pneumonia
Pulmonary tuberculosis
Receiver operating curve
Tenofovir
Trimethoprim/sulfamethoxazole
Voluntary counseling and testing.
The data used to support the findings of this study are available from the corresponding author upon request.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
All authors declared that there are no conflicts of interest.
Jiang Xiao and Hongxin Zhao conceived and designed the experiments; Liang Wu and Zhe Zhan performed experiment. Liang Wu wrote the manuscript. Liang Wu, Zhe Zhan, Yu Wang, Yiwei Hao, Fang Wang, Guiju Gao, and Di Yang collected and analysed the data.
The authors acknowledge the work of HIV healthcare providers for their diagnosis, nursing, and treatment of HIV/AIDS patients in Ditan Hospital. Support for this work was provided by (1) Healthcare Talent Training Program in Beijing Health System (grant 2015-3-105); (2) the National natural Science Fund