Procalcitonin as a Tool to Antimicrobial Stewardship in COVID-19 Patients with Superimposed Bacterial Infections: A Systematic Review

Figures & data

Figure 1 PRISMA flow diagram.

Table 1 Characteristics of the Included Studies

Authors	Country of Origin	Study Design	Sample Size
Moreno-García et al^Citation5	Barcelona, Spain	Observational cohort (retrospective)	1125
Atallah et al^Citation2	Boston, Massachusetts, USA	Retrospective observational study	324
Richards et al^Citation3	Wales, United Kingdom	Retrospective observational study	65
Basnet et al^Citation12	Gwarko, Lalitpur, Nepal	Descriptive cross-sectional study	49
He et al^Citation6	Changsha, China	Retrospective observational study	905
Vanhomwegen et al^Citation1	Brussels, Belgium	Retrospective observational study	66
Ming et al^Citation7	North-West London, UK	Retrospective observational study	237
Cheng et al^Citation13	Huangshi, China	Retrospective study	212
Heesom et al^Citation14	Southampton, United Kingdom	Prospective, single center, cohort study	52
Waris et al^Citation14	Islamabad, Pakistan	Prospective cohort study	430
Hughes et al^Citation15	London, United Kingdom	Retrospective observational study	730
Pink et al^Citation8	Hannover, Germany	Retrospective single-center study	99
Peters et al^Citation16	Chesterfield, United Kingdom	Retrospective single-center study	118
May et al^Citation4	New York, United States	Retrospective cohort study	2443
Heer et al^Citation17	Slough, United Kingdom	Retrospective cohort study	60
Tang et al^Citation19	Zhuzhou, China	Retrospective cohort study	78
Garrido et al^Citation20	Reus, Spain	Retrospective observational study	56
Roy et al^Citation18	Jacksonville, Florida, USA	Retrospective observational study	147

Table 2 Summary of Statistics

Country	n (%)
UK	6 (33.33)
USA	3 (16.67)
China	3 (16.67)
Spain	2 (11.11)
Pakistan	1 (5.56)
Belgium	1 (5.56)
Germany	1 (5.56)
Nepal	1 (5.56)
Study Type	n (%)
Retrospective Observational	11 (61.11)
Retrospective Cohort	4 (22.22)
Prospective Cohort	2 (11.11)
Descriptive Cross-Sectional	1 (5.56)
Gold Standard	n (%)
Blood Culture	9 (50)
Sputum / LRT Culture	9 (50)
Urine Culture	4 (22.22)
Urine Antigen	4 (22.22)
Unspecified Culture	2 (11.11)
Other Markers (no culture)	7 (38.89)
Procalcitonin Cut-Off value	n (%)
2/2.5 ng/mL	2 (11.11)
1 ng/mL	2 (11.11)
0.5/0.55 ng/mL	10 (55.56)
0.3 ng/mL	1 (5.56)
0.2/0.25 ng/mL	6 (33.33)
0.1 ng/mL	2 (11.11)
No Cut-Off Values	3 (16.67)

Table 3 Studies’ Overall Conclusion(s)

Citation	Procalcitonin Cut-Off Value	Overall Conclusion
Moreno-García et al^Citation5	4 cut-off levels were used: 0.2 0.5 1 2	1- Procalcitonin (>0.2) is an indicator of bacterial coinfection in COVID-19 patients. 2- Procalcitonin can be used as an antibiotic stewardship tool to de-escalate the use of antibiotics.
Atallah et al^Citation2	2 cut-off levels were used: 0.25 0.5	Procalcitonin (>0.25) is an indicator of bacterial coinfection in COVID-19 patients.
Richards et al^Citation3	None	Procalcitonin (>50% of baseline) is an indicator of bacterial coinfection in COVID-19 patients.
Basnet et al^Citation12	None	Procalcitonin is an indicator of bacterial coinfection in COVID-19 patients.
He et al^Citation6	None	Increased procalcitonin levels does not rule in bacterial co-infection; however, low procalcitonin levels can rule out bacterial co-infection and limit antibiotic use. (Sensitive but not specific)
Vanhomwegen et al^Citation1	2 cut-off levels were used: 0.5 2.5	Procalcitonin is NOT an indicator of bacterial coinfection in COVID-19 patients.
Ming et al^Citation7	None	Procalcitonin is NOT an indicator of bacterial coinfection in COVID-19 patients. (PCT is higher in patients with bacterial co-infection but the results were not statistically significant)
Cheng et al^Citation13	0.1 ng/mL	Procalcitonin (>0.1) is an indicator of bacterial coinfection in COVID-19 patients.
Heesom et al^Citation21	0.5 ng/mL	Procalcitonin can be used as an Antibiotic Stewardship tool to de-escalate the use of antibiotics.
Waris et al^Citation14	0.25 ng/mL	Procalcitonin (>0.25) is an indicator of bacterial coinfection in COVID-19 patients.
Hughes et al^Citation15	0.25 ng/mL	1- Procalcitonin (>0.25) is an indicator of bacterial coinfection in COVID-19 patients. 2- Procalcitonin can be used as an Antibiotic Stewardship tool to de-escalate the use of antibiotics.
Pink et al^Citation8	0.55 ng/m	1- Procalcitonin (>0.55) is an indicator of bacterial coinfection in COVID-19 patients. 2- Procalcitonin can be used as an Antibiotic Stewardship tool to de-escalate the use of antibiotics.
Peters et al^Citation16	3 cutoffs were used: <0.25 microg/L 0.25–0.49 microg/L ≥0.5 microg/L	Procalcitonin can be used as an Antibiotic Stewardship tool to de-escalate the use of antibiotics.
May et al^Citation4	2 cut-off levels were used: 0.5 ng/mL 0.25 ng/m	Increased procalcitonin levels does not rule in bacterial co-infection; however, low procalcitonin levels can rule out bacterial co-infection and limit antibiotic use. (Sensitive but not specific)
Heer et al^Citation17	Peak PCT>0.5 ng/dL	1- Procalcitonin is NOT an indicator of bacterial coinfection in COVID-19 patients. 2- Procalcitonin should NOT be used as an Antibiotic Stewardship tool to de-escalate the use of antibiotics.
Tang et al^Citation19	PCT >0.1 ng/mL	Procalcitonin (>0.1) is an indicator of bacterial coinfection in COVID-19 patients.
Garrido et al^Citation20	2 cut-off levels were used:0.3 ng/mL0.06 ng/m	Procalcitonin is NOT an indicator of bacterial coinfection in COVID-19 patients.
Roy et al^Citation18	0.25 ng/mL	1- Markedly elevated procalcitonin (>0.25) is an indicator of bacterial coinfection in COVID-19 patients. 2- Procalcitonin can be used as an Antibiotic Stewardship tool to de-escalate the use of antibiotics.

Table 4 Risk of Bias, Cohort Studies

	1	2	3	4	5	6	7	8	9	10	11
Moreno-García et al^Citation5	Yes	Yes	Cannot tell	Yes	Yes	Yes	Cannot tell	Yes	Yes	Yes	Yes
Richards et al^Citation3	Yes	Yes	Yes	Yes	Yes	Yes	Cannot tell	Yes	Yes	Yes	Yes
Basnet et al^Citation12	Yes	Yes	Yes	Yes	Cannot tell	Yes	Cannot tell	Cannot tell	Yes	Yes	Yes
Vanhomwegen et al^Citation1	Yes	Yes	Yes	Yes	Yes	Yes	Cannot tell	Yes	Yes	Yes	No
Ming et al^Citation7	Yes	Yes	Yes	Yes	No	Yes	Cannot tell	Yes	Yes	Yes	No
Heesom et al^Citation21	Yes	Yes	Yes	Cannot tell	No	Yes	Cannot tell	Yes	Yes	Yes	Yes
Waris et al^Citation14	Yes	Yes	Yes	Yes	Cannot tell	No	Cannot tell	Cannot tell	Yes	Yes	Yes
Hughes et al^Citation15	Yes	Yes	Yes	Cannot tell	Yes	Yes	Cannot tell	Cannot tell	Yes	Yes	Yes
Pink et al^Citation8	Yes	Yes	Yes	No	Yes	Yes	Cannot tell	Yes	Yes	Yes	Yes
Peters et al^Citation16	Yes	Yes	Yes	Cannot tell	Yes	Yes	Cannot tell	Yes	Yes	Cannot tell	Yes
May et al^Citation4	Yes	Yes	Yes	Cannot tell	Cannot tell	No	Cannot tell	Cannot tell	Cannot tell	Cannot tell	No
Heer et al^Citation17	Yes	Yes	Yes	Yes	Yes	Yes	Cannot tell	Yes	Yes	Yes	No
Tang et al^Citation19	Yes	Yes	Cannot tell	Yes	Yes	Yes	Cannot tell	Yes	Yes	Yes	Yes
Garrido et al^Citation20	Yes	Yes	Yes	Yes	Yes	Yes	Cannot tell	Yes	Yes	Yes	Yes
Roy et al^Citation18	Yes	Yes	Cannot tell	Yes	Yes	No	Cannot tell	Yes	Yes	Yes	Yes

Notes:

1. Did the study address a clearly focused issue?

2. Was the cohort recruited in an acceptable way?

3. Was the exposure accurately measured to minimize bias?

4. Was the outcome accurately measured to minimize bias?

5. Have the authors identified all important confounding factors?

6. Have they taken account of the confounding factors in the design and/or analysis?

7. Was the follow up of subjects complete enough?

8. Was the follow up of subjects long enough?

9. Do you believe the results?

10. Can the results be applied to the local population?

11. Do the results of this study fit with other available evidence?

Table 5 Risk of Bias, Case–Control Studies

	1	2	3	4	5	6	7	8	9
Atallah et al^Citation2	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
He et al^Citation6	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Roy et al^Citation18	Yes	Yes	Yes	Yes	Yes	Yes	Cannot tell	Yes	Yes

Notes:

1. Did the study address a clearly focused issue?

2. Did the authors use an appropriate method to answer their question?

3. Were the cases recruited in an acceptable way?

4. Were the controls selected in an acceptable way?

5. Was the exposure accurately measured to minimize bias?

6. Have the authors taken account of the potential confounding factors in the design and/or in their analysis?

7. Do you believe the results?

8. Can the results be applied to the local population?

9. Do the results of this study fit with other available evidence?

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