Longitudinal changes of laboratory measurements after discharged from hospital in 268 COVID-19 pneumonia patients

3.2.1 Routine blood test indicators’ changes on whole patients

Figure 4 shows that CRP were 50% higher than upper bound of normal range at the time of hospitalization and mean of it resumed normal value at discharge. Both mean and variance of CRP kept decreasing through time series. As for T lymphocyte subset, four indicators were needed to be noticed which are CD45 + lymphocyte count, Absolute value of T lymphocytes (AVTL), T helper lymphocytes absolute count (THLA) and T suppress lymphocyte absolute count (TSLAC). CD45 + lymphocyte count was lower than lower bound of normal range at the time of on admission to hospital. Value of these four indicators kept near and even reached lower bound within 75 days after patients released from hospital. At the time instance of 75 days after released from hospital, they would probably drop below lower bound (95% confidence interval cross red dotted line). Additionally, AVTL, THLA and TSLAC changed in similar pattern and CD45 + lymphocyte count was closer to lower bound than another three. Being similar with CRP, IL-6 was nearly 33% higher than upper bound in admission day and resumed at discharge. The blood parameters stably resuming at discharge, such as CRP and IL-6, could be considered as marker to assist judging progression and treatment of COVID-19.

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Fig. 4

Six indicators were abnormal at time of in hospital and discharge.

It had been reported that WBC, neutrophils and lymphocytes were statistically significant between severe and non-severe groups in previous study [4, 19]. After patients being discharged, these three indicators all distributed in normal range. Furthermore, WBC and neutrophils had similar changes through time series shown in Fig. 5. It will be discussed in section 3.2.2 that whether there still existing statistical significance between severe and non-severe groups of these three indicators after discharge.

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Fig. 5

Three indicators fluctuate within normal range.

As for creatine kinase (CK), the mean increased sharply at duration of 100 days and showed high volatility in this time interval. The phenomenon was caused by that five patients’ CK dominated others which are 6997, 2379, 928, 539 and 412. Obviously, shown in Fig. 6, the 95% confidence interval (CI, blue shadow area) beyond upper bound of normal range implied that CK was probably larger than upper bound at 100 days after discharge. Coincidentally, at 25 days after discharge, T helper/suppressor lymphocytes (CD4 + /CD8+) was dominated by a male patient with value equaling 1046. In the remaining durations, the mean of this indicator fluctuated between 1.0 and 1.8 and its standard deviation ranged from 0.45 to 0.95.

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Fig. 6

Two indicators dominated by few patients.

A lot of previous works had been done by comparing routine blood indicators between severe and non-severe groups and had some findings with great value of clinic, e.g. [24, 25]. There is a wide variety in symptoms reported of patients with COVID-19, varying from mild symptoms to severe [26]. For this study, to continue previous works in hospital discharged patients, patients were divided by severity into three groups, mild, moderate and severe. There are 222 moderate patients, 28 severe patients and 18 mild patients, with average age of 44.7, 57.2 and 34.4 respectively. P-values of patients’ age between any two of these three groups are far smaller than 0.01 implying that differences of age are statistically significant. It is consistent with acknowledge that older patients are more likely to be severe. Association between severity and gender was tested by chi-square and statistically significant difference was observed with P value equaling 0.02.

Figure 7 shows dynamic changes of these three severity groups and corresponding P values are displayed in Table 3. Although majority of P values in Table 3 are larger than 0.05, statistically significant difference still exists. Neutrophils are the most abundant immune cells in human blood and activation of it is highly activated processes in SARS infection [27, 28]. Recruitment of neutrophils was found in immune response triggered by SARS-CoV-2 [29]. In previous bioinformatic study, an increasing trend of neutrophils was found in immune response triggered by SARS-CoV-2 and could be considered as an indicator of severe respiratory symptoms and a poor outcome in patients with COVID-19 [30–32]. For patients released from hospital, significant difference was observed in neutrophils between mild and moderate groups. It is probably that more efforts were put on severe patients and neutrophils of moderate patients were slightly neglected in hospital, leading to that severe patients were as good as mild patients in neutrophils but moderate patients were not. It suggests that moderate patients should be paid equal attention to with severe patients in neutrophils. However, for those four indicators shown in Fig. 7, there is not statistically significant between mild and severe groups.

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Fig. 7

Four indicators dynamic changes after discharge.

Hypertension, diabetes, cardiovascular disease (CVD) and chronic obstructive pulmonary disease (COPD) were four main underlying diseases among 268 patients, and 57 patients had at least one of them. Mean age of 57 patients is 57.9 and half of them are male. P values of each indicator were calculated between patients with and without the underlying disease, and part of them are shown in the Table 4. Few patients had COPD and CVD resulting in many missing values in the table. Four indicators, T helper lymphocyte% (THL%), CD3 + CD4 + CD8 + lymphocyte count, IL-6 and CD3 + CD4 + CD8 + /CD45 + did not show statistically significant difference for all four underlying diseases in majority of time intervals. Inversely, NLR showed statistically significant under both Hypertension and COPD, and is suggested to be added as an indicator in routine hematologic parameters for patients with underlying diseases.

According to N. Gadi et al. [33], with respect to infections and vaccinations, female is equipped with stronger immune responses and outlive male. Additionally, SARS-CoV-2 infection is more likely to trigger a sex-based differential immune response [34]. Therefore, in order to explore whether gender is an effecting factor, patients were divided into male and female groups for analysis. Figures in this section always have a gap of shadow at duration of 75 days on the “male line” (orange line) which is caused by the fact that only two male patients were included in that period and the 95% confidence interval could not be estimated. More importantly, to analyze the differences of hematologic parameters between males and females, effects of age should be eliminated first. Means of age in male and female groups both are equal to 45 and P value between their ages is 0.99. Nevertheless, statistically significant was observed in durations of “50”, “75”, “100” and “200”, so demonstrating the effect of gender requires further test to eliminate noisy effects of age first, which was carried out in following content.

Like Fig. 5, Fig. 8 shows that changes of WBC, neutrophils and lymphocytes still have the similar tendency in both male and female cases. For WBC, orange line dominated the blue line through all the time, and P values between males and females were smaller than 0.05 except duration equaling 25, 50, 175. Neutrophils were in same pattern, but lymphocytes were not. As shown in the sub-figure of lymphocytes below, orange line and bule line intersected three times and P values fluctuated across 0.05 four times. In general, males recovered better in WBC, neutrophils, monocytes and CK than females. Moreover, the tendency of both men and women in monocytes and CK indicators were nearly similar. Of note, the mean value of CK in the male group had high volatility in duration of both 100 days and 175 days. With respect to duration of 100 days, males’ mean increased to nearly 300, which was 50% higher than the upper bound of the normal value range and still had a large volatility at the same time. P values of these five indicators are displayed in Table 5.

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Fig. 8

Five indicators that male recovered better.

With the aim of eliminating effect of age in each duration, gender was chosen as control variable during analysis. Due to that number of females is larger than that of males in dataset, female patients were selected and divided into three subgroups, young (< 30 years), middle (30 years≤and < 60 years) and old (≥60 years). In Table 5, P values of blood test indicators between sex-specific groups as well as age-specific subgroups are displayed, e.g., “WBC(male/female)” represents P values of WBC between men and women, and “wbc_female(0–30/30–60)” represents P values of WBC between young and middle female patients. The age effect could be excluded in CK indicator, because almost all P values were larger than 0.05 between age-specific subgroups when CK in males are statistically different with those of females.

Inversely with what had been mentioned above, in Fig. 9, THL% and CD3 + CD4 + CD8 +lymphocyte count showed higher values in the female group than that in male group through all time periods. The values of THL% are very closed between male and female at duration of 75 and 200 due to only one male data including in these durations which were not considered in analysis. Similar with Table 5, relevant P values are listed in Table 6. THL% and CD3 + CD4 + CD8 + lymphocyte count are two important parameters in T lymphocyte subsets. Female recovered better than male in these two indicators implied that: The resuming ability of COVID-19 patients’ immune systems in female is better than that in male, being consistent with S. Jaillon et al. and N. Gadi et al. [18, 33].

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Fig. 9

Two T subset indicators that female recovered better.

268 patients were assigned into old and non-old groups by age and 60 was chosen as cutoff. With 95% confidence level, six indicators shown in Fig. 10 are less volatility in non-old group than that in old group (green shadow narrower than blue shadow). As common sense, health condition of young patient is more stable than that of old patient and stronger to resist external infection. Be consistent with what have been mentioned in Section 3.2.1, AVTL, TSLAC and CD45 + lymphocyte count of old group changed in similar pattern. The curve of old group for all these three indicators dropped below lower bound at 75 days after hospital discharge. Besides, curve of CD45 + lymphocyte count for old group crossed lower dotted line four times within 100 days after hospital discharge. These phenomena above indicated that patients with age over 60 years would be more sensitive to COVID-19 which could still have effects on them after released from hospital for a period (more than 2 months). Basophils and LDH crossed upper and lower bound respectively in the time series. It may be sequela of COVID-19 or perhaps other external effects requiring further data to support analysis.

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Fig. 10

Six indicators show the difference between old and not old groups.

3.3.1 Tendency of lung lesions changing on overall patients

With the time going on, volumes of lesions kept decreasing on both left and right lungs indicating process of recovery and ratios of volumes were closed to zero at 100 days. Whereas significant differences were observed between right and left lungs. As indicated by Fig. 11 and Table 7, volumes of lung lesions on right side were bigger than that on left which is statistically significant at date of hospital discharged and first two periods.

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Fig. 11

Tendency of lesions changing on right and left lungs overall.

The 268 patients were also divided into male and female subgroups with purpose of exploring whether volumes of lung lesions caused by COVID-19 would be different between genders, and the results are shown in detail in Fig. 12 and Table 8. For both male and female, mean volumes of right lung lesions were always bigger than that of left lung and significant differences between them were observed at discharged date and first period. In addition, right lung of male recovered to the same health level with left lung faster than that of female, due to that statistical significance was observed in female but not in male after first period. However, differences between volumes of lung lesions for female and male were not significant not only in left lung, but also in right lung.

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Fig. 12

Tendency of lung lesions changing for gender-based subgroups.

Definitely, age is an unignorable factor in researching of infectious diseases including COVID-19. The whole patients were assigned into three subgroups age_30, age_60 and age_90 which represented ages of patients in the subgroups are smaller than or equal to 30, larger than 30 but smaller than or equal to 60 and larger than 60 but smaller than or equal to 90 respectively, and were named young group, middle group and old group in order. As the Fig. 13 showing, In the young group, differences of lesions volumes between right and left lungs were not significant through the whole time series since hospital discharged (P values > 0.05 for all time). When comparing across subgroups, a regular phenomenon was found. Comparing young and middle groups, there are significant differences in volumes of lesions for both left and right lungs at date of discharged (P_left lung value 0.001; P_right lung value: 0.003) and first period (P_left lung value 0.0004; P_right lung value: 0.0003). With respect to contrasting middle and old groups, except in the date of discharged and first period, statistical significance of lung lesions volumes was also observed in second period (P_left lung value 0.002; P_right lung value: 0.001). In addition, statistical difference of lung lesions volumes was also existing in fourth period (P values are 0.03), besides in date of discharged and first two periods (third period did not have P value due to lacking data), for young and old subgroups.

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Fig. 13

Tendency of lung lesions changing for age-based subgroups.

As mentioned in 3.2.3, 57 patients had at least one underlying disease of hypertension, diabetes, CVD and COPD before infected COVID-19. Only one and four of them suffered from COPD and CVD respectively and these two diseases were not considered during analyzing. In Fig. 14, hypertension was chosen as an instance, volumes of lung lesions for patients with underlying diseases were bigger than that for patients without underlying diseases and statistical significance was observed until the third period. Moreover, comparing volumes of lesions between left and right lungs, statistical significance was observed in patients with underlying diseases at date of discharged (P value: 0.001) and first two periods (P values: 0.002; 0.04) which is consistent with results in section 3.3.1.

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Fig. 14

Tendency of lung lesions changing for age-based subgroups.